REMOTE PHYSIOLOGIC PARAMETER ASSESSMENT

METHODS AND PLATFORM APPARATUSES

OVERVIEW

[0001] Various aspects of the present disclosure are directed toward methods, systems and apparatuses that are useful in remotely assessing a physiologic parameter of a user using user data obtained by a scale.

[0002] Various aspects of the present disclosure are direct toward monitoring different physiological characteristics for many different applications. For instance, physiological monitoring instruments are often used to measure a number of patient vital signs, including blood oxygen level, body temperature, respiration rate and electrical activity for

electrocardiogram (ECG) or electroencephalogram (EEG) measurements. For ECG measurements, a number of electrocardiograph leads may be connected to a patient's skin, and are used to obtain a signal from the patient. Obtaining physiological signals can often require specialty equipment and intervention with medical professionals. For many applications, such requirements may be costly or burdensome. These and other matters have presented challenges to monitoring physiological characteristics.

[0003] Various aspects of the present disclosure are directed toward multisensory biometric devices, systems and methods. Aspects of the present disclosure include user- interactive platforms, such as scales, large and/or full platform-area or dominating-area displays and related weighing devices, systems, and methods. Additionally, the present disclosure relates to electronic body scales that use impedance-based biometric

measurements. Various other aspects of the present disclosure are directed to biometrics measurements such as body composition and cardiovascular information. Impedance measurements can be made through the feet to measure fat percentage, muscle mass percentage and body water percentage. Additionally, foot impedance-based cardiovascular measurements can be made for an ECG and sensing the properties of blood pulsations in the arteries, also known as impedance plethysmography (IPG), where both techniques can be used to quantify heart rate and/or pulse arrival timings (PAT). Cardiovascular IPG measures the change in impedance through the corresponding arteries between the sensing electrode pair segments synchronous to each heartbeat.

[0004] In certain aspects, the present disclosure is directed to apparatuses and methods including a weighing scale and assessment circuitry that is external to the weighing scale. The scale includes a platform for a user to stand on, data-procurement circuitry, processing circuitry, and an output circuit. The data-procurement circuitry includes force sensor circuitry and a plurality of electrodes integrated with the platform and configured for engaging the user with electrical signals and collecting signals indicative of the user's identity and cardio-physiological measurements while the user is standing on the platform. The processing circuitry includes a CPU and a memory circuit with user-corresponding data stored in the memory circuit. The processing circuitry is arranged with (e.g., electrically integrated with or otherwise in communication) the force sensor circuitry and the plurality of electrodes and configured and arranged to process data obtained by the data-procurement circuitry while the user is standing on the platform and therefrom generate cardio-related physiologic data corresponding to the collected signals. In various embodiments, the scale includes a user interface can either be integrated with the platform and the plurality of electrodes and/or can be integrated with external circuitry that is not located within the platform. The user interface outputs user-specific information for the user while the user is standing on the platform. The output circuit is configured to receive the user data and, in response, send the user data, including the data indicative of the user's identity and the generated cardio-related physiologic data, from the scale for reception at a remote location and to the user interface. For example, the output circuit sends a subset of the user data to the user interface. The subset of user data is indicative of a portion of available health information that is specific to the user and is based on the cardio-related physiologic data and an indication that the user data is available. The output circuit further sends the user data to the assessment circuitry that is not integrated within the scale in response to user input to the user interface that is indicative of a user selecting to view the user data, which is additional data from the subset of user data. The assessment circuitry receives and further assesses the user data and, in response, provides corresponding data for review which is correlated with the user data.

[0005] In various aspects, the subset of user data includes weight and a synopsis of the user data. The user interface can include a display that provides the subset of user data and the indication of the user data that is available on the display for the user to view, the indication including an icon for the user to select to view the user. The user interface includes or refers to interactive components of a device (e.g., the scale) and circuitry configured to allow interaction of a user with the scale (e.g., hardware input/output components, such as a screen, speaker components, keyboard, touchscreen, etc., and circuitry to process the inputs). The user interface can be or include a graphical user interface (GUI), a foot-controlled user interface (FUI), and/or voice input/output circuitry, each of which is further described herein. The user interface is integrated with the platform (e.g., internal to the scale) and/or is integrated with external circuitry that is not located under the platform, in various aspects.

[0006] The assessment circuitry can be integrated with external circuitry that is remotely located from the weighing scale. In specific aspects, the assessment circuitry validates the cardio-related physiologic data as concerning the user associated with a patient profile using the data indicative of the user's identity and automatically updates the patient profile to include a cardiogram measurement and the user's weight using the generated cardio-related physiologic data. For example, the weighing scale can be used to check a patient in, in specific embodiments. Specifically, the data-procurement circuitry and the processing circuitry of the scale provide a number of questions to the user including performing a question and answer session to identify symptoms and/or reasons the user is visiting a physician. The output circuit can output question and answer data in response to the question and answer session to the external circuitry, which receives the question and answer session data and automatically populate the data in the patient profile. The assessment circuitry can analyze data sent by the scale, such as prior to a physician seeing the patient. The assessment circuitry can determine at least one clinical indication using the cardio-related physiologic data and store the clinical indication in the patient profile for review by the physician. The question and answer session can be performed to identify symptoms and/or reasons the patient is visiting a physician and used to update, by the scale and the external circuitry, the patient profile to include answers from the question and answer session. The external circuitry can include an output circuit to output a signal to circuitry accessible by a physician responsive to the update of the user profile, the signal being indicative of completion of a check-in process.

[0007] In related aspects, the assessment circuitry receives and validates the user data as concerning a specific user associated with a user ID and determines at least one physiologic parameter of the user using the user data. Further, the assessment circuitry derives additional health information corresponding to the user data based on categories of interest and outputs the additional health information to the scale for display using the user interface of the weighing scale. The assessment circuitry can correlate the categories of interest to the at least one physiologic parameter by comparing statistical data of a sample census pertinent to the categories of interest and the at least one physiologic parameter. For example, categories of interest can be correlated to the physiologic parameter by comparing statistical data of a sample census pertinent to the categories of interest and values of the at least one physiologic parameter of the sample census.

[0008] In various aspects, the assessment circuitry provides a clinical indication corresponding to the user by processing the user data. The clinical indication includes indications selected from the group consisting of: pulse wave velocity, cardiac output, pre- ejection period, stroke volume, and a combination thereof. The assessment circuit controls access to a user profile of the user. For example, access to the clinical indication and the user data is allowed to or by a physician corresponding to the user for interpretation. Access to the clinical indication is not allowed to the user until the user provides an input indicative of interest and the physician provides a prescription for the clinical indication.

[0009] The assessment circuitry, in some aspects, can identify a risk that the user has a condition based on the reference information and the user data provided by the scale. The risk that the user has a condition includes a probability that the user has the condition and a severity of the condition based on risk factors within the user data. The assessment circuit outputs generic information correlating to the condition to the scale that is tailored based on the identified risk. In specific implementations, generic information is output to the weighing scale in response to the probability being greater than a first threshold value and the severity being greater than a second threshold value.

[0010] In specific embodiments, the assessment circuitry is used to securely pool and store data from a plurality of scales. For example, the assessment circuitry is external circuitry that is remotely located from the weighing scale. The external circuitry includes processing circuitry and memory circuitry, configured and arranged to receive the user data from the weighing scale. The external circuitry responds to received user data by replacing an identifier of the user data with an alias ID and storing the user data with the alias ID in a first database and identification of which scale and user that corresponds to the alias ID in a second database. The alias ID can includes a substitute value for the identifier that has no algorithmic relationship with the identifier and which can be irreversible. The external circuitry can pool user data from plurality of scales and correlating with a plurality of users, and periodically change the alias ID and update the first and the second database.

[0011] In related specific aspects, the scale identifies a risk that the user has a health condition using trigger data indicative of risks for a plurality of health conditions. The trigger data can include values of the physiological data that are indicative of the risks for the plurality of health conditions. Further, the scale outputs at least portions of the cardio- related physiologic data as user data in response to the identified risk. In such aspects, the assessment circuitry is external circuitry that is remotely located from the weighing scale, the external circuitry, including processing circuitry and memory circuitry, configured and arranged to receive the user data from the weighing scale and to: filter data from the Internet using the user data, and identify data related to the health condition based on the filter of the data from the Internet. The processing circuitry of the weighing scale can filter the cardio- related physiologic data using the trigger data and output the at least portion of the cardio- related physiologic data as user data, wherein the user data is indicative of the risk for the health condition. Further, the processing circuitry can identify the risk that the user has the health condition by comparing the cardio-related physiologic data to the trigger data, wherein the trigger data includes the values of the cardio-related physiologic data that indicate the user has a likelihood above threshold of having the health condition.

[0012] The external circuitry can pool user data from plurality of scales, and identify other users that have correlated user data and identify patterns of risks for conditions or diseases based on the correlation. Various correlations can be identified by grouping respective sets of user data into groups based on criteria selected from the group consisting of: symptoms, physiological parameter values, diagnosis, prescription drug usage, lifestyle habits, medical history, family medical history, and a combination thereof.

[0013] In specific aspects, the external circuitry can identify a subset of users of the plurality of users with correlations between user data sets based on the pooled used data. Based on prioritization data and normalization data, the external circuitry can identify and normalize user data from the user data sets of the subsets of users and provide the subsets of users with access to a social group via respective scales of the subset of users. For example, providing access to the social group can include selective access to the normalized user data from the user data sets. The subset of users of the plurality of users of one or more scales can be grouped into a social group based on a correlation between user data sets of the subset of the plurality of users, wherein the correlation is based on physiological parameter values obtained from the cardio-related physiologic data collected by the one or more scales and at least one data selected from the group consisting of: demographics, user goals, symptoms, diagnosis, prescription drug usage, lifestyle habits, medical history, family medical history, and a combination thereof. The external circuitry can provide social group data to the subset of users based on a relationship between the users of the social group, a number of users in the social group, and one or more of the following: level of familiarity between users, level of familiarity of users with physiological data, level of interest in physiological data, and a level of complexity of data displayed. [0014] The above discussion/summary is not intended to describe each embodiment or every implementation of the present disclosure. The figures and detailed description that follow also exemplify various embodiments.

Brief Description of Figures

[0015] Various example embodiments may be more completely understood in consideration of the following detailed description in connection with the accompanying drawings, in which:

[0016] FIG. la shows an apparatus consistent with aspects of the present disclosure;

[0017] FIG. lb shows an example of remotely determining physiologic parameters using an apparatus consistent with aspects of the present disclosure;

[0018] FIG. lc shows an example of a scale wireless communicating with external circuitry consistent with aspects of the present disclosure;

[0019] FIG. Id shows an example of apparatus comprised of a plurality of scales and external circuitry consistent with aspects of the present disclosure;

[0020] FIG. le shows an example scale communicatively coupled to external circuitry and various data types provided to a user, consistent with various aspects of the present disclosure;

[0021] FIG. If shows an example apparatus for pooling scale data, consistent with various aspects of the present disclosure;

[0022] FIG. lg shows an example process for pooling scale-data, consistent with various aspects of the present disclosure;

[0023] FIG. lh shows an example process for securely pooling scale data, consistent with various aspects of the present disclosure;

[0024] FIG. li shows an example apparatus for selectively providing scale-obtained data, consistent with various aspects of the present disclosure

[0025] FIG. lj shows an example process for providing scale-based social grouping, consistent with various aspects of the present disclosure;

[0026] FIG. Ik shows an example apparatus for providing a variety of services using pooled scale data, consistent with various aspects of the present disclosure;

[0027] FIG. 11 shows an example process for filtering data using pooled scale, consistent with various aspects of the present disclosure;

[0028] FIG. lm shows an example process for providing social grouping using pooled user data, consistent with various aspects of the present disclosure; [0029] FIG. In shows an example apparatus for updating a patient profile, consistent with various aspects of the present disclosure;

[0030] FIG. lo shows an example process for updating a patient profile, consistent with various aspects of the present disclosure;

[0031] FIG. lp shows current paths through the body for the IPG trigger pulse and Foot IPG, consistent with various aspects of the present disclosure;

[0032] FIG. lq is a flow chart illustrating an example manner in which a user-specific physiologic meter/scale may be programmed to provide features consistent with aspects of the present disclosure;

[0033] FIG. 2a shows an example of the insensitivity to foot placement on scale electrodes with multiple excitation and sensing current paths, consistent with various aspects of the present disclosure;

[0034] FIGs. 2b-2c show examples of electrode configurations, consistent with various aspects of the disclosure;

[0035] FIGs. 3a-3b show example block diagrams depicting circuitry for sensing and measuring the cardiovascular time-varying IPG raw signals and steps to obtain a filtered IPG waveform, consistent with various aspects of the present disclosure;

[0036] FIG. 3c depicts an example block diagram of circuitry for operating core circuits and modules, including for example those of FIGs. 3a-3b, used in various specific embodiments of the present disclosure;

[0037] FIG. 3d shows an exemplary block diagram depicting the circuitry for interpreting signals received from electrodes.

[0038] FIG. 4 shows an example block diagram depicting signal processing steps to obtain fiducial references from the individual Leg IPG "beats," which are subsequently used to obtain fiducials in the Foot IPG, consistent with various aspects of the present disclosure;

[0039] FIG. 5 shows an example flowchart depicting signal processing to segment individual Foot IPG "beats" to produce an averaged IPG waveform of improved SNR, which is subsequently used to determine the fiducial of the averaged Foot IPG, consistent with various aspects of the present disclosure;

[0040] FIG. 6a shows examples of the Leg IPG signal with fiducials; the segmented Leg IPG into beats; and the ensemble-averaged Leg IPG beat with fiducials and calculated SNR, for an exemplary high-quality recording, consistent with various aspects of the present disclosure; [0041] FIG. 6b shows examples of the Foot IPG signal with fiducials derived from the Leg IPG fiducials; the segmented Foot IPG into beats; and the ensemble-averaged Foot IPG beat with fiducials and calculated SNR, for an exemplary high-quality recording, consistent with various aspects of the present disclosure;

[0042] FIG. 7a shows examples of the Leg IPG signal with fiducials; the segmented Leg IPG into beats; and the ensemble averaged Leg IPG beat with fiducials and calculated SNR, for an exemplary low-quality recording, consistent with various aspects of the present disclosure;

[0043] FIG. 7b shows examples of the Foot IPG signal with fiducials derived from the Leg IPG fiducials; the segmented Foot IPG into beats; and the ensemble-averaged Foot IPG beat with fiducials and calculated SNR, for an exemplary low-quality recording, consistent with various aspects of the present disclosure;

[0044] FIG. 8 shows an example correlation plot for the reliability in obtaining the low SNR Foot IPG pulse for a 30-second recording, using the first impedance signal as the trigger pulse, from a study including 61 test subjects with various heart rates, consistent with various aspects of the present disclosure;

[0045] FIGs. 9a-b show an example configuration to obtain the pulse transit time (PTT), using the first IPG as the triggering pulse for the Foot IPG and ballistocardiogram (BCG), consistent with various aspects of the present disclosure;

[0046] FIG. 10 shows nomenclature and relationships of various cardiovascular timings, consistent with various aspects of the present disclosure;

[0047] FIG. 11 shows an example graph of PTT correlations for two detection methods (white dots) Foot IPG only, and (black dots) Dual-IPG method, consistent with various aspects of the present disclosure;

[0048] FIG. 12 shows an example graph of pulse wave velocity (PWV) obtained from the present disclosure compared to the ages of 61 human test subjects, consistent with various aspects of the present disclosure;

[0049] FIG. 13 shows another example of a scale with interleaved foot electrodes to inject and sense current from one foot to another foot, and within one foot, consistent with various aspects of the present disclosure;

[0050] FIG. 14a shows another example of a scale with interleaved foot electrodes to inject and sense current from one foot to another foot, and measure Foot IPG signals in both feet, consistent with various aspects of the present disclosure; [0051] FIG. 14b shows another example of a scale with interleaved foot electrodes to inject and sense current from one foot to another foot, and measure Foot IPG signals in both feet, consistent with various aspects of the present disclosure;

[0052] FIG. 14c shows another example approach to floating current sources is the use of transformer-coupled current sources, consistent with various aspects of the present disclosure;

[0053] FIGs. 15a-d show an example breakdown of a scale with interleaved foot electrodes to inject and sense current from one foot to another foot, and within one foot, consistent with various aspects of the present disclosure;

[0054] FIG. 16 shows an example block diagram of circuit-based building blocks, consistent with various aspects of the present disclosure;

[0055] FIG. 17 shows an example flow diagram, consistent with various aspects of the present disclosure;

[0056] FIG. 18 shows an example scale communicatively coupled to a wireless device, consistent with various aspects of the present disclosure; and

[0057] FIGs. 19a-c show example impedance as measured through different parts of the foot based on the foot position, consistent with various aspects of the present disclosure.

[0058] While various embodiments discussed herein are amenable to modifications and alternative forms, aspects thereof have been shown by way of example in the drawings and will be described in detail. It should be understood, however, that the intention is not to limit the disclosure to the particular embodiments described. On the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure including aspects defined in the claims. In addition, the term "example" as used throughout this application is only by way of illustration, and not limitation.

DETAILED DESCRIPTION

[0059] Aspects of the present disclosure are believed to be applicable to a variety of different types of apparatuses, systems, and methods involving remotely determining physiologic parameters of a user using user data obtained by a scale. In certain

implementations, aspects of the present disclosure have been shown to be beneficial when used in the context of a weighing scale with electrodes configured for engaging with the user and generating cardio-related physiologic data, such as data indicative of a BCG or ECG of a user. In some embodiments, the assessment circuitry determines the physiologic parameters, which can include clinical indicators that may not be displayed to the user. The assessment circuitry controls access to information by not allowing access to the clinical indicators to the user, without a prescription from a physician, while still allowing access to other data such as body weight, body mass index, heart rate, body fat percentage, and cardiovascular age. In other embodiments, the scale obtained data is used to automatically update a patient profile, check the patient in, determine risks and recommendations for the user, and connect the user to other people of similar risks or behavior. These and other aspects can be implemented to address challenged, including those discussed in the background above. While not necessarily so limited, various aspects may be appreciated through a discussion of examples using such exemplary contexts.

[0060] Accordingly, in the following description various specific details are set forth to describe specific examples presented herein. It should be apparent to one skilled in the art, however, that one or more other examples and/or variations of these examples may be practiced without all the specific details given below. In other instances, well known features have not been described in detail so as not to obscure the description of the examples herein. For ease of illustration, the same reference numerals may be used in different diagrams to refer to the same elements or additional instances of the same element. Also, although aspects and features may in some cases be described in individual figures, it will be appreciated that features from one figure or embodiment can be combined with features of another figure or embodiment even though the combination is not explicitly shown or explicitly described as a combination.

[0061] In accordance with a number of embodiments, physiologic parameter data is collected using an apparatus, such as a weighing scale or other platform that the user stands on. The user (e.g., co-workers, friends, roommates, colleagues), may use the apparatus in the home, office, doctors office, or other such venue on a regular and frequent basis, the present disclosure is directed to a substantially-enclosed apparatus, as would be a weighing scale, wherein the apparatus includes a platform which is part of a housing or enclosure and a user display to output user-specific information for the user while the user is standing on the platform. The platform includes a surface area with electrodes that are integrated and configured and arranged for engaging a user as he or she steps onto the platform. Within the housing is processing circuitry that includes a CPU (e.g., one or more computer processor circuits) and a memory circuit with user-corresponding data stored in the memory circuit. The platform, over which the electrodes are integrated, is integrated and communicatively connected with the processing circuitry. The processing circuitry is programmed with modules as a set of integrated circuitry which is configured and arranged for automatically obtaining a plurality of measurement signals (e.g., signals indicative of cardio-physiological measurements) from the plurality of electrodes. The processing circuitry generates, from the signals, cardio-related physiologic data manifested as user data.

[0062] The user data, in various embodiments, is processed to determine physiologic parameters of the user and other data, such as cardio-physiological data and wellness data. The physiologic parameters, in various embodiments, includes information that is regulated by a government agency, such as the Food and Drug Administration (FDA), and/or otherwise requires a prescription from a physician for the user to obtain. The other data, such as the cardio-physiological data and wellness data, by contrast, includes derived measurements that are "non-regulated" by agencies, such as the FDA. To obtain such information, a user may purchase a scale and use the scale over the counter and without a physician's prescription. The scale, if the user data is further processed, can provide the additional prescription (Rx) health information to the user, via the physiologic parameters, that may be beneficial for the user or the user's physician to access. However, the user may be unable to access the information without a prescription from a physician and/or could not purchase the scale in the first place without a prescription if the scale was enabled to provide the Rx health information. Embodiments in accordance with the present disclosure include processing the user data on assessment circuitry to determine physiologic parameters, which can include Rx health information. The assessment circuit can be integrated with the processing circuitry of the scale and under the platform upon which the user stands or can be integrated with external circuitry that is not located under the platform and includes output circuitry to communicate with the processing circuitry of the scale (e.g., is external to the scale). For example, the external circuitry can include a server and/or standalone central processing unit (CPU). In various embodiments, the assessment circuitry controls access to the Rx health information by allowing a physician to access to the information but not a user. The user is provided access to non-regulated data, such as other additional health

information, and granted access to the Rx health information in response to a prescription from the physician. Furthermore, the Rx health information is used to update a user profile, such as a user health profile at the physician's office.

[0063] In accordance with various embodiments, the assessment circuitry receives user data from a plurality of scales. Each scale provides data for one or more different users and/or can be located at different locations. The assessment circuitry identifies the users corresponding to the received user data, validates the user data as concerning the identified users, and correlates the user data with profiles based on identification of the respective plurality of users. The external circuitry provides physiologic parameters, such as diagnosis, conditions, and/or treatments, PWV, cardiac output, pre-ejection period and stroke volume by processing the data from the scales. In some specific aspects, the external circuitry controls access to the profiles by allowing access to physiologic parameters and other data to a physician and not allowing access to the physiologic parameters to the users. In various embodiments, the assessment circuitry allows access to other data to the user, without a prescription. For example, the assessment circuitry allows access by granting access to the respective profile or portions of the data in the profile and/or by sending the respective data to the scale (or another user device) for display. Example data that is non-regulated by an agency and can be provided to the user without a prescription includes body weight, body mass index, heart rate, body -fat percentage, and cardiovascular age. By controlling access to the physiologic parameters (e.g., Rx health information), the scale provides the advanced functions of determining the clinical indications while being sold over-the-counter and the user can access this data through their physician. The physiologic parameters can be used by the physician for further analysis and/or to provide health advice and/or diagnosis, such as medications.

[0064] In accordance with various embodiments, the user data is based on sensing, detection, and quantification of at least two simultaneously acquired impedance-based signals. The simultaneously acquired impedance-based signals are associated with quasi- periodic electro-mechanical cardiovascular functions, and simultaneous cardiovascular signals measured by the impedance sensors, due to the beating of an individual's heart, where the measured signals are used to determine at least one cardiovascular related characteristic of the user for determining the heart activity, health, or abnormality associated with the user's cardiovascular system. The sensors can be embedded in a user platform, such as a weighing scale-based platform, where the user stands stationary on the platform, with the user's feet in contact with the platform, where the impedance measurements are obtained where the user is standing with bare feet.

[0065] In certain embodiments, the plurality of impedance-measurement signals includes at least two impedance-measurement signals between the one foot and the other location. Further, in certain embodiments, a signal is obtained, based on the timing reference, which is indicative of synchronous information and that corresponds to information in a BCG. Additionally, the methods can include conveying modulated current between selected ones of the electrodes. The plurality of impedance-measurement signals may, for example, be carried out in response to current conveyed between selected ones of the electrodes. Additionally, the methods, consistent with various aspects of the present disclosure, include a step of providing an IPG measurement within the one foot.

Additionally, in certain embodiments, the two electrodes contacting one foot of the user are configured in an inter-digitated partem of positions over a base unit that contains circuitry communicatively coupled to the inter-digitated partem. As discussed further herein, and further described in U. S. Patent Application 14/338,266 filed on October 7, 2015, which is herein fully incorporated by reference for its specific teaching of inter-digitated partem and general teaching of sensor circuitry, the circuitry can obtain the physiological data in a number of manners.

[0066] In medical (and security) applications, for example, the impedance

measurements obtained from the plurality of integrated electrodes can then be used to provide various cardio-related information that is user-specific including, as non-limiting examples, synchronous information obtained from the user and that corresponds to information in a ballistocardiogram (BCG) and an impedance plethysmography (IPG) measurements. By ensuring that the user, for whom such data was obtained, matches other bio-metric data as obtained concurrently for the same user, medical (and security) personnel can then assess, diagnose and/or identify with high degrees of confidence and accuracy.

[0067] In various related aspects, the scale and assessment circuitry provide various additional (e.g., non-Rx) health information to the user in response various user inputs and/or the user data. The additional health information, in various embodiments, includes tables, information, and/or correlates to the cardio-related information that is determined using the assessment circuitry (e.g., physiologic parameters) and is non-RX health information. In various embodiments, the cardio-related information may indicate the user has and/or is at risk for a disorder, disease, and/or has a particular symptom. The additional health information is provided to the user that includes generic information for the disorder, disease, and/or particular symptom without specific information about the user and/or an indication that the user has and/or is at risk for the disorder, disease, and/or symptom. In a number of embodiments, the generic information is based on and/or correlated to specific user inputs, such as a category of interest (e.g., demographic of interest, disorder/disease of interest), among other inputs. In some embodiments, the scale instructs another user circuitry, such as a user device (e.g., cell phone, tablet, computing device, smart watch) to ask the questions, and in response to the user's input, the user device provides the responses to the scale and/or the external circuitry. Based on the inputs, categories of interest for the user are determined and used to generate the additional health information.

[0068] A user interface can be used to provide the questions and obtain the answers. The user interface is and/or includes a GUI, a FUI, and/or voice based input/output circuitry which is integrated with the platform of the scale (e.g., internal to the scale) or is integrated with external circuitry that is not located or integrated with the platform of the scale, as further described herein. Further, the user interface can include multiple user interfaces, one of which is integrated with the scale and one that is not, as further described herein. A user interface includes or refers to interactive components of a device (e.g., the scale) and circuitry configured to allow interaction of a user with the scale (e.g., hardware input/output components, such as a screen, speaker components, keyboard, touchscreen, etc., and circuitry to process the inputs). A user display includes an output surface (e.g., screen) that shows text and/or graphical images as an output from a device to a user (e.g., cathode ray tube, liquid crystal display, light-emitting diode, organic light-emitting diode, gas plasma, touch screens, etc.)

[0069] As used herein, a user device includes processing circuitry and output circuitry to collect various data (e.g., signals) and communicate the data to the scale and/or other circuitry. Example user devices include cellphones, tablets, standalone server, among other devices. The user device can be a wearable device that is worn by a user, such as on a user's wrist, head, or chest. Example wearable devices include smartwatches and fitness bands, smart glasses, chest heart monitors, etc. In other aspects, the user device further includes sensor circuitry or other circuit to collect physiologic data from the user, and, can optionally be in secured communication with the scale or other circuitry. For example, the user device includes smartwatches or fitness bands that collect heart rate and/or ECG and/or body temperature, medical devices, implanted medical devices, smartbeds, among other devices. Example physiologic data collected by user devices includes glucose measurements, blood pressure, ECG or other cardio-related data, body temperature, among other data. As used herein, the terms "user device" and "wearable device", can be interchangeably used.

[0070] In a number of a specific embodiments, the user stands on the scale. The scale collects signals using the data-procurement circuitry, and sends at least a portions of the signals to the external circuitry. The assessment circuitry processes the collected signals, sent as user data, and determines cardio-related information, which may include Rx information. During the processing by the assessment circuitry, the scale (and/or a user device) asks the user if the user is interested in receiving various health information and/or would like a table provided that is based on various demographics, disorders, and/or other categories of interest, such as by using voice input/output circuitry. In response to the user providing an input indicating they are interested, the scale asks the user to input categories of interest (demographics, disorders, symptoms, etc.). In some embodiments, the scale provides the inputs to the assessment circuitry and the assessment circuitry derives additional health information using the inputs and the user data. For example, the assessment circuitry can determine health information that is based on the demographics the user provides (e.g., particular sex, age, ethnicity) and various values and/or symptoms of a disorder/disease/symptom correlated to the cardio-related information of the user. As a particular specific example, the user can provide that they are interested in a table for males, 45-55, and African-American. The user data may indicate that the user has and/or is at risk for atrial fibrillation. In various embodiments, the assessment circuitry generates a table which includes general risk factors and/or symptoms for various heart-related conditions, which includes atrial fibrillation, for African-American males ages 45-55. The information provided does not include particular values for the user and/or any indication that the user has atrial fibrillation. In this manner, the scale does not provide Rx health information without a prescription from a physician and can be provided over-the-counter.

[0071] Additional or generic health information provided to the user can be tailored to the user based on the user data and the determined risk. For example, generic health information includes general information on the condition, potential symptoms, and suggestions, such as dietary, exercise and other considerations. Further, the generic health information is provided based on the severity of the condition (in general or user-specific) and a probability that the user has the condition. The assessment circuitry may not provide the generic health information, for example, for a condition that has a low severity (e.g., user has an ingrown toe-nail) and/or that the user has a low probability of having the condition (e.g. two percent probability). Thereby, the user is not provided with burdensome amounts of information and/or with information that is not interesting to the user. The user can set and/or adjust threshold values for the probability and/or the severity.

[0072] Furthermore, in various embodiments, user data from a plurality of different scales is combined to identify potential risks for conditions. For example, a plurality of users use different scales and the user data is combined in a user-specific knowledge database. The extemal circuitry compares the user data to the user-specific knowledge database, which includes other user's user data and conditions they have, to determine the risk. The user- specific knowledge database, in various embodiments, is dynamically updated overtime as more information is learned from different users. For example, the user-specific knowledge database stores data collected from a plurality of users. A first user is known to have a heart condition and has various parameters that are measured and the correlate to symptoms of the heart condition. A second user is not known to have the same heart condition but has similar parameter values as the first user. In such aspects (among others), the assessment circuitry can be integrated with external circuitry to pool the user data and use the information of the first user to determine or review a potential risk for the condition for the second user.

Furthermore, if the second user is subsequently diagnosed with a different (or same) heart disease than the first user, the user-specific knowledge database is updated with this information. Thereby, the user-specific knowledge database is updated with potential risk factors and parameter values associated with a condition in response to additional information from users of the scales.

[0073] The user data includes user information that the user may not want

compromised, accessed by others, and/or otherwise manipulated. Combining and storing the data in a user-specific knowledge database presents a number of data security risks including another person identifying whom the particular users are and health information about the users. Various embodiments include outputting secure user data from the scale to the external circuitry (e.g., having the assessment circuitry integrated therein). To secure the data, the processing circuitry of the scale removes user identification data from the user data and adds an identifier to the user data so that all data associated with the same user is associated with the same identifier. The identifier, in some embodiments, is encrypted and/or includes an alias identifier (e.g., a tokenization version of the identification of the user and the scale).

[0074] Aspects of the present disclosure involve securely communicating and storing user data using a scale-based user-physiological heuristic system. To secure the user data, the scale removes portion of the user data that identifies the user, adds a scale identifier and/or user identifier, respectively providing codes that uniquely identify the user and the scale, and optionally, which can be used to encrypt portions of the user data such, such as the user identifier. As a more specific embodiment, the external circuitry is an offsite server CPU (e.g., hosted by Amazon or Yahoo) which receives user data with the user/scale identification data, replaces this identification data with an alias ID while storing: (a) the user data with the alias ID in a first more-accessible database, and (b) the scale identifier and/or user identifier (with correspondence or correlation to the respective alias ID) in a second more-secure database that is not accessible without the requester of the access passing a higher-level access protocol. Such a higher-level access protocol, according to certain embodiments, is used to permit authenticated access such as regulatory

representatives used to validate user-specific medical studies and medical personnel (e.g., doctors) seeking to use the user-specific data for scale-specific diagnoses (e.g., obesity, arterial stiffness and cardio-arrhythmias) and related medical device/pharmacology prescriptions.

[0075] In various embodiments, external circuitry can pool user data from a plurality of scales in a user-specific knowledge database and, in some embodiments, identifies correlations between user data and potential patterns of conditions and/or diseases of users corresponding to the user data. For example, a plurality of users may use different scales and the user data is combined in a user-specific knowledge database. The external circuitry compares the user data within the user-specific knowledge database to determine various correlations and patterns. The user-specific knowledge database, in various embodiments, is dynamically updated overtime as more information is learned from different users. For example, the user-specific knowledge database stores data collected from a plurality of users. A first user is known to have a heart condition and has various parameters that are measured and the correlate to symptoms of the heart condition. A second user is not known to have the same heart condition but has similar parameter values as the first user. The external circuitry uses the information of the first user to determine or review a potential risk for the condition for the second user. Furthermore, if the second user is subsequently diagnosed with a different (or same) heart disease than the first user, the user-specific knowledge database is updated with this information. Thereby, the user-specific knowledge database is updated with potential risk factors and parameter values associated with a condition in response to additional information from users of the scales.

[0076] In various embodiments, the external circuitry groups respective sets of user data into groups. The groups are based on demographics, user goals, symptoms, physiological parameter values, diagnosis, prescription drug usage, lifestyle habits, medical history, family medical history, and a combination thereof. The correlation, in some instances, is provided to the user, without identifying specific other users, such that the user identifies how other users of a similar demographic reached their fitness goals. In other embodiments, the correlation includes users with a specific condition, disorder, and/or disease and causes of improvements or potential lack of improvement of symptoms of the condition, disorder and/or disease, such as lifestyle changes, prescription drugs, and/or change in exercise habits or geographic location. The pooled user data is used to educate users based on other user's successes, failures, and/or general results.

[0077] Various aspects of the present disclosure are directed to a user-specific scale- based enterprise system. The user-specific scale-based enterprise system includes at least one scale, the Internet (e.g., world-wide-web), a standalone user CPU, and one or more user devices, such as a smartwatch, fitness tracking device, smartphone, smart bed, among other devices. In various embodiments, the scale includes trigger data. The trigger data includes user data values and/or combinations of different data values with user demographic information that indicates that the user has a risk for a condition, such as a disorder or disease. In response to the trigger data and the scale-obtained data or other user data from the other devices indicating that the user has a risk for a condition, the scale and/or standalone user CPU filters the user data from the scale and the other user devices and filters data from the Internet to identify data that is relevant to the condition. In this manner, the enterprise system is used as a medical analytic driver that filters scale-obtained data, user device-obtained data, and data from the Internet to identify data related to the condition.

[0078] In response to the filters, the system can provide the user with various additional health information regarding the condition. Alternatively and/or in addition, the system provides a prompt to the user that indicates general information about the condition if the user is indicating some risk for the condition. The prompt asks if the user would like more information and in response to the user requesting more information, the enterprise system provides the aggregated user data to a physician for review and to confirm the diagnosis. The physician is provided access to the user data using the internet and/or external circuitry, such as server CPU that is accessible by the physician. In response to the physician confirming the diagnosis and/or correlation, the scale is modified with the confirmed diagnosis. The modification, in some embodiments, includes storing, on the scale, various correlation data (e.g., diagnosis data), adding additional devices and/or parameters to track (e.g., halter monitor, ECG tracking device, prescription drug titration, weight tracking and/or threshold values, exercise goals, stress test), and/or health information about the condition (e.g., articles), among other data. Furthermore, the standalone user CPU of the enterprise system, in some embodiments, is used to display various data to the user, such as generic health information, user-specific diagnosis data, blogs/forums of social groups, physician reports, and/or studies, among other information.

[0079] Embodiments of the present disclosure are directed to a platform apparatus and assessment circuitry, integrated with external circuitry, that provide various features including grouping users based on user-physiological heuristics applied to scale-obtained data and providing the grouped users with anonymous access to social groups, such as using a forum, blog and/or social network and/or social media. In various specific embodiments, the scale is configured to collect data for a plurality of users and identifies each respective user using scale-based biometrics, such as cardiogram characteristics. In specific embodiments, the external circuitry includes a server CPU that pools user data from a plurality of scales and is used, in connection with the scale, to provide the users with access to social groups. The access to social groups includes access to a forum, blog, and/or webpage of a social network (e.g., a social network or social media page) that connects users of the social group. The social groups are identified automatically by the assessment circuitry and/or external circuitry based on scale-obtained data. The assessment circuitry and/or external circuitry can determine the social groups by identifying various users with similar risk that user for a condition using the scale-obtained data, diagnosis, similar parameter values, user goals, and/or various other correlations. In various embodiments, the platform apparatus is configured to recognize multiple users and identifies the particular users to display the prompt to, using a scale-based biometric, such as a cardiogram characteristic. In other related embodiments, the scale prioritizes the various multiples users and outputs the data to identify social groups, and for other services, based on the priority of the user. The user inputs provided using the access to the social group can be used as feedback by the external circuitry to further refine various conditions and/or risks that the user may have.

[0080] Biometrics, as used herein, are metrics related to human characteristics and used as a form of identification and access control. Scale-based biometrics includes biometrics that are obtained using signals collected by the data-procurement circuitry of the scale (e.g., using electrodes and/or force sensors). Example scale-based biometrics include foot length, foot width, foot shape, toe print, weight, voice recognition, facial recognition, a passcode tapped and/or picture drawn with a foot of the user on the GUI of the user display, among other biometrics. In some specific embodiments, a scale-based biometric includes a toe- print (e.g., similar to a finger print) that is recognized using a toe-print reader on the FUI of the scale. The toe print can be used as a secure identification of the user. In other related embodiments, a biometric is identified using a user device that is in communication with the scale. For example the biometric can include a finger print identified using a tablet and/or a cellphone that is wired or wireless communication with the scale. And, a wearable device, such as a ring, wristband, and/or ankle bracelet can be used to positively identify a user, with or without biometrics.

[0081] The social groups are identified automatically by the external circuitry based on scale-obtained data. The external circuitry can determine the social groups by identifying various users with similar risk that user for a condition using the scale-obtained data, diagnosis, similar parameter values, user goals, and/or various other correlations. In various embodiments, the scale is configured to recognize multiple users and identifies the particular users to display the prompt to, using a scale-based biometric, such as a cardiogram characteristic. In other related embodiments, the scale prioritizes the various multiples users and outputs the data to identify social groups, and for other services, based on the priority of the user. The user inputs provided using the access to the social group can be used as feedback by the assessment circuitry to further refine various conditions and/or risks that the user may have.

[0082] In various instances, users group together to form discussions on various topics of interest. Health related issues for different people can follow similar patterns. For example, users with a particular condition may have similar symptoms. Particular symptoms may occur prior to the user being diagnosed or even recognizing the symptoms. In other instances, users with similar exercise or weight goals may follow similar exercise and/or eating plans. Users having similar experiences may benefit from being grouped together in a social group, such as on a social network, to discuss symptoms, successes, failures, among other information. As the user may not recognize symptoms, they may wait longer to see a physician and/or identify that they are having a problem. Earlier detection of health related issues is beneficial for recovery, treatment/control of symptoms, and prevention of further problems.

[0083] In accordance with various embodiments, scale-obtained data is pooled by external circuitry, having assessment circuitry integrated there with, to identify various correlations between different user data sets. In response to the identified correlations, identified users with the correlation are provided with access to a social group, such as a forum, blog, and/or a page of a social network. The access to the social group can include selective access to normalized user data from the different user data sets. For example, the assessment circuitry and/or external circuitry identifies and normalizes portions of the user data from the user data sets of the subsets of users with an identified correlation based on prioritization data and normalization data. The user's identities remain anonymous as the data includes data that is sensitive to the user and/or the discussions occurring on the page are sensitive to the user and the data is normalized. In this way, the user's identity is preserved while the user is participating in the social network.

[0084] In specific embodiments, the forum, blog and/or social network page automatically populates scale-obtained data from the subset of users. For instance, the forum, blog and/or social network page includes various reports and/or dashboards indicating user's successes and failures, treatments, and/or progress. The users are able to communicate about what has been helping them or not helping them to do better with symptoms of a condition, treatment, diagnosis, and/or their health goals.

[0085] In other specific embodiments, the social groups include intra-scale social groups and inter-scale social groups. Intra-scale social groups include users that use the same scale. Inter-scale social groups includes users that use different scale and/or at least two users that use different scales. With inter-scale social groups, the groups are identified by identifying correlations between the user data sets, such as various users with a risk for a, diagnosis, similar parameter values, user goals, and/or various other correlations. These and other aspects can be implemented to address challenges, including those discussed in the background above. While not necessarily so limited, various aspects may be appreciated through a discussion of examples using such exemplary contexts.

[0086] Aspects of the present disclosure are directed to a weighing scale and assessment circuitry that provide various features to check-in a patient's at a physician's office, clinic, hospital, and/or other health-related facilities. In some embodiments, the scale is not located at the health-related facility but in a consumer setting (e.g., dwelling or nursing home) and is used to pre-check in the patient and/or suggest a visit to the physician, as described herein. The scale, such as a body weight scale, provides the feature of checking-in a patient by collecting scale-obtained data including cardio-physiological measurements from a user while the user is standing on the platform of the scale and outputting the scale-obtained data to assessment circuitry. In various related aspects, the scale asks the user for various symptoms and/or reasons for visiting the physician's office, clinic, hospital, and/or other health-related facilities. The assessment circuitry uses the scale-obtained data by validating the scale obtained-data as corresponding to a medical profile and automatically updating the medical profile of the user using the scale-obtained data. In various aspects, the assessment circuitry provides additional optional features such as determining clinical indications using the scale-obtained data, providing an indication to staff that the user is checked-in, providing access to the staff to the scale-obtained data and/or clinical indications, and/or providing an alert in response to the scale-obtained data being indicative of an emergency and/or particular condition of the user. As previously described, the assessment circuitry can be integrated with the scale and/or with external circuitry.

[0087] With changes to the healthcare system and increasing government regulation on data documentation, data entry for medical records of patients of physicians and hospitals is increasingly. Data entry can be time consuming, use both human and computer resources, and can result in lower patient care as the physicians/nurses become frustrated and impatient with the changing systems and requirements. In accordance with a number of embodiments, physiological parameter data is collected using an apparatus, such as a weighing scale or other platform that the user stands on while at checking in and/or waiting at physician's office, hospital, urgent care, emergency room, nursing home, physical therapist, and/or other relevant venue. The scale, in various embodiments, is used to check the user in and/or automatically update a patient profile associated with the user without a nurse, physician and/or other personal manually entering the data.

[0088] In accordance with various embodiments, the external circuitry, having assessment circuitry thereon, receives user data from a plurality of scales. Each scale provides data for one or more different users and/or can be located at different locations (e.g., different physicians, different rooms at an office, or different locations). The scales may be located at the respective user's dwellings, commercial settings (e.g., health center, fitness facility), and/or health centers. The external circuitry and/or assessment circuitry identifies the users corresponding to the received user data, validates the user data as concerning the identified users associated with specific patient profiles, and automatically updates the specific patient profiles with the user data. The external circuitry and/or assessment circuitry (and/or the scale) provides clinical indications, such as diagnosis, conditions, and/or treatments, PWV, cardiac output, pre-ejection period and stroke volume by processing the user data from the scales. The external circuitry and the scales can be used to update a plurality of different patient profiles and reduces data entry by physicians and nursing staff. Such a system can be used in a hospital, in a large doctor's office, for doctors that have multiple locations, nursing homes, etc.

[0089] In other embodiments, a physician and/or other health professional can review the scale data for patients as a service during a visit at physician and/or remotely. The scale can be located at the dwelling of the user (e.g., home, nursing home, assisted care center) and/or a commercial settings. The scale, responsive to user data being indicative of a health condition, can offer a service for the physician to review the data and/or for the patient to visit the health professional. In response to user input that activates the service (e.g., indicate an interest and, optionally, provide a weighted value), the scale outputs the user data to external circuitry that is accessible by the health professional. If the user already is a client of the physician, the external circuitry and/or assessment circuitry identifies the user and stores the user data in a patient profile. If the user is a new client, the external circuitry and/or assessment circuitry generates a new patient profile for the user with the information provided.

[0090] Turning now to the figures, FIG. la shows an apparatus consistent with aspects of the present disclosure. The apparatus includes a platform 101 and a user display 102. The user, as illustrated by FIG. la is standing on the platform 101 of the apparatus. The user display 102 is arranged with the platform 101. As illustrated by the dashed lines of FIG. la, the apparatus further includes processing circuitry 104, data-procurement circuitry 108, and physiologic sensors 111. That is, the dashed lines illustrate a closer view of components of the apparatus.

[0091] The physiologic sensors 111, in various embodiments, include a plurality of electrodes integrated with the platform 101. The electrodes and corresponding force-sensor circuitry 109 are configured to engage the user with electrical signals and to collect signals indicative of the user's identity and cardio-physiological measurements while the user is standing on the platform 101. The physiological sensors 118 further include a plurality of force sensors, such as strain gauges, as discussed further herein. Although the embodiment of FIG. la illustrates the force sensor circuitry 109 as separate from the physiological sensors 111, one of skill in the art may appreciate that the force sensor circuitry 109 are physiological sensors. For example, the signals are indicative of physiologic parameters of the user and/or are indicative of or include physiologic data, such as data indicative of a BCG or ECG and/or actual body weight or heart rate data, among other data. The user display 102 is arranged with the platform 101 and the electrodes to output user-specific information for the user while the user is standing on the platform 101. The processing circuitry 104 includes CPU and a memory circuit with user-corresponding data 103 stored in the memory circuit. The processing circuitry 104 is arranged under the platform 101 upon which the user stands, and is electrically integrated with the force sensor circuitry 109 and the plurality of electrodes (e.g., the physiologic sensors 111). The data indicative of the identity of the user includes, in various embodiments, user-corresponding data, biometric data obtained using the electrodes and/or force sensor circuitry, voice recognition data, images of the user, input from a user's device, and/or a combination thereof and as discussed in further detail herein. For example, the scale can capture voice sounds from the user speaking, and the user data indicative of the identity includes the voice sounds captured.

[0092] The user-corresponding data includes information about the user that may or may not be obtained using the physiologic sensors 111, such as demographic information or historical information. Example user-corresponding data includes height, gender, age, ethnicity, exercise habits, eating habits, cholesterol levels, previous health conditions or treatments, family medical history, and/or a historical record of variations in one or more of the listed data. The user-corresponding data can be obtained directly from the user (e.g., the user inputs to the scale) and/or from another circuit (e.g., a smart device, such a cellular telephone, smart watch and/or fitness device, cloud system, etc.).

[0093] In various embodiments, the processing circuitry 104 is electrically integrated with the force sensor circuitry 109 and the plurality of electrodes and configured to process data obtained by the data-procurement circuitry 108 while the user is standing on the platform 101. Although embodiments are not so limited and the processing circuitry 104 can be in communication with the force sensor circuitry 109 and the plurality of electrodes to obtain the data. The processing circuitry 104, for example, generates cardio-related physiologic data corresponding to the collected signals and that is manifested as user data. Further, the processing circuitry 104 generates data indicative of the identity of the user, such as a user ID and/or other user identification metadata. The user ID can be, for example, in response to confirming identification of the user using the collected signals indicative of the user's identity.

[0094] The user data (e.g., physiologic data) collected by the scale include the raw signals, bodyweight, body mass index, heart rate, body -fat percentage, cardiovascular age, among other data. In various embodiments, the processing circuitry 104, with the user display 102, displays at least a portion of the user data to the user. For example, user data that is not-regulated is displayed to the user, such as user weight. Alternatively and/or in addition, the user data is stored. For example, the user data is stored on the memory circuit of the processing circuitry (e.g., such as the physiologic data stored on the physiological user data database 107 illustrated by FIG. la). The processing circuitry 104, in various embodiments, correlates the collected user data (e.g., physiologic user-data) with user- corresponding data, such as storing identification metadata that identifies the user with the respective data.

[0095] In some embodiments, the scale collects physiologic data from other devices, such as medical devices, user devices, and/or wearable devices. The data can include glucose measurements, blood pressure, ECG or other cardio-related data, body temperature, lifestyle or demographic data, among other physiologic and user data.

[0096] In a number of embodiments, the processing circuitry 104 and/or the scale includes an output circuit 106. The output circuit 106 receives the user data and, in response, sends the user data, including the data indicative of the user's identity and the generated cardio-related physiologic data, from the scale for reception by assessment circuitry 181 and to provide data to user via a user interface. The user interface, as previous described, is or includes a graphical user interface (GUI), a foot-controlled user interface (FUI), and/or voice input/output circuitry. The user interface can be integrated with the platform 101 (e.g., internal to the scale) and/or can be integrated with external circuitry that is not located under the platform 101. In some embodiments, the user interface is a plurality of user interfaces, in which at least one user interface is integrated with the platform 101 and at least one user interface is not integrated with the platform 101. Example user interfaces include input/output devices, such as display screens, touch screens, microphones, etc.

[0097] A FUI is a user interface that allows for the user to interact with the scale via inputs using their foot and/or via graphic icons or visual indicators near the user's foot while standing on the platform. In specific aspects, the FUI receives inputs from the user's foot (e.g., via the platform) to allow the user to interact with the scale. The user interaction includes the user moving their foot relative to the FUI, the user contacting a specific portion of the user display, etc.

[0098] A GUI is a user interface that allows the user to interact with the scale through graphical icons and visual indicators. As an example, the external circuitry includes a GUI, processing circuitry, and output circuitry to communicate with the processing circuitry of the scale. The communication can include a wireless or wired communication. Example external circuitry can include a wired or wireless tablet, a cellphone (e.g., with an application), a smartwatch or fitness band, smart glasses, a laptop computer, among other devices. In other examples, the scale includes a GUI and voice input/output circuitry (as further described below) integrated in the platform 101. The user interact with the scale via graphical icons and visual indicators provided via the GUI and voice commands from the user to the scale.

[0099] Voice input/output circuitry (also sometimes referred to as speech input/output) can include a speaker, a microphone, processing circuitry, and other optional circuitry. The speaker outputs computer-generated speech (e.g., synthetic speech, instructions, and messages) and/or other sounds (e.g., alerts, noise, recordings, etc.) The computer-generated speech can be predetermined, such as recorded messages, and/or can be based on a text-to- speech synthesis that generates speech from computer data. The microphone captures audio, such a voice commands from the user and produces a computer-readable signal from the audio. For example, the voice input/output circuitry can include an analog-to-digital converter (ADC) that translates the analog waves captured by the microphone (from voice sounds) to digital data. The digital data can be filtered using filter circuitry to remove unwanted noise and/or normalize the captured audio. The processing circuitry (which can include or be a component of the processing circuitry 104) translates the digital data to computer commands using various speech recognition techniques (e.g., partem matching, partem and feature matching, language modeling and statistical analysis, and artificial neural networks, among other techniques).

[00100] In specific embodiments, the output circuit 106 provides for display by a FUI 180 of the scale. The FUI 180 is arranged with the platform 101 and the data-procurement circuitry 108. The FUI outputs user-specific information to the user while the user is standing on the platform. For ease of reference, the following disclosure refers to the FUI 180 as displaying data and using a user display. However, embodiments in accordance with the present disclosure are not so limited. For example, the FUI 180 can provide data via computer generated voice messages, haptic responses, and/or other sounds. In various embodiments, the scale includes one or more speaker components to provide the data to the user. Thereby, the FUI 180 can include a projection of sound via the speaker components.

[00101] A FUI 180 allows for the user to interact with the scale via inputs using their foot. A FUI includes or refers to a user interface that receives inputs from the user's foot (e.g., via the platform) to allow the user to interact with the scale. The user interaction includes the user moving their foot relative to the FUI 180, the user contacting a specific portion of the user display, etc. In various embodiments, the control of the FUI 180 can be provided to a separate user device, such a user device that has previously been or is paired with the scale and that is detected by the scale. As a specific example, the scale provides a cellphone with control functions to control the display of the FUI in response to detecting the cellphone is within a threshold distance. Example GUIs include input/output devices, such as display screens, touch screens, microphones, etc. The instruction, in various embodiments, directs the user to remain still and/or look forward (e.g., "hold your head up and look forward"). In response to the instruction, the scale collects physiologic data from the user. And, in response to the collection of physiological data and/or verification that the user has a specific/current posture, the processing circuitry, and the user display and/or a speaker, provide an alert to the user. The alert indicates that the user may lower their head, such as indicating that the user can look at the user display of the apparatus, and/or the user may move.

[00102] The output circuit 106 sends a subset of the user data to the user interface (e.g., FUI 180, GUI, and/or voice input/output circuitry). The subset of user data is indicative of a portion of available health information that is specific to the user and is based on the cardio- related physiologic data. Further, the subset of user data includes an indication that the user data is available. In specific embodiments, the subset of user data provided and/or displayed using the user interface includes weight and a synopsis of available user data. In a more specific embodiment, the indication of available user data includes an icon for the user to select on the FUI 180 (using their foot) to view the user data. The output circuit 106 can send the user data to assessment circuitry 181 that is not integrated with the scale in response to a user input to the user interface that is indicative of a user selecting to view the user data. The user data includes additional data from the subset of user data. Although the present embodiment illustrates the scale having a FUI, embodiments are not so limited. For example, the scale can include a GUI that is internal to the scale or can be in communication with a user device having a GUI that is used to provide data to the user. The user device may include a cellphone or a tablet that is in wireless or wired communication with the scale. In other embodiments and/or in addition, the scale include voice input/output circuitry to provide data to the user and/or obtain data from the user via computer-generated speech.

[00103] The assessment circuitry 181 is configured to receive and further assess the user data (as further described herein). The assessment circuitry 181 , based on the assessment, can provide data for review. The data provided is correlated with the user data. The assessment circuitry 181 can be integrated with external circuitry 112 and/or be the external circuitry 1 12. The external circuitry 1 12 is remotely located from the weighing scale and can include output circuitry, processing circuitry, and memory circuitry. In various embodiments, the output circuit 106 displays on the user interface (e.g., the FUI 180) the user's weight and the data indicative of the user's identity and/or the generated cardio- related physiologic data corresponding the collected signals. The external circuitry 1 12 is at a remote location from the scale and is not integrated with the scale. The communication, in various embodiments, includes a wireless communication and/or utilizes a cloud system.

[00104] As described further herein, an algorithm to determine the physiologic data from raw signals/ user data can be located on the scale, on another device (e.g., external circuitry 112, cellphone), and on a Cloud system. For example, the Cloud system can learn to optimize the determination and program the scale to subsequently perform the determination locally. The Cloud system can perform the optimization and programming for each user of the scale.

[00105] In various embodiments, the external circuitry 112 and/or assessment circuitry 181 receives the user-data, validates the user data as concerning a specific user associated with a user ID, and determines at least one physiologic parameter of the user using the user data. As discussed in further detail herein, the validation can be based on the data indicative of the user's identity. For example, the data indicative of the user's identity can be the user ID and/or can be associated with the user ID (e.g., is mapped to and/or otherwise correlated to). The external circuitry 112 and/or assessment circuitry 181, in some embodiments, communicates the determined physiologic parameter back to the scale and/or another user device for display to the user. Alternatively and/or in addition, the external circuitry 112 and/or assessment circuitry 181 controls access to the physiologic parameter, as discussed further herein.

[00106] The physiologic parameter, in various embodiments, includes PWV, BCG, cardiac output, pre-ejection period, stroke volume, arterial stiffness, respiration, and/or other Rx health information. The user data, in some embodiments, includes the raw force signals, bodyweight, heartrate, balance, tremors, body mass index and/or percentage, among other non-regulated physiologic data.

[00107] Although the present examples embodiments provided above are in reference to external circuitry 112 performing the determination, embodiments in accordance with the present disclosure are not so limited. For example, the processing circuitry 104 can determine the physiologic parameter while the user is standing on the platform 101.

[00108] In accordance with various embodiments, although not illustrated by FIG. l a, the apparatus includes an additional sensor circuitry that is external to the scale. The additional sensor circuitry can include a communication circuit and is configured and arranged to engage the user with electrical signals and collect therefrom signals indicative of an ECG of the user. The sensor circuitry, which may include and/or be correlated with processing circuitry configured to derive an ECG from the collected signals. The sensor circuitry communicates the ECG to the external circuitry 112 and/or assessment circuitry 181 and the scale can communicate a BCG to the external circuitry 112 and/or assessment circuitry 181.

[00109] The external circuitry 1 12 and/or assessment circuitry 181 receives the user data, validates the user data as concerning a specific user associated with a user ID, and determines at least one clinical indication of the user using the user data. The clinical indication (e.g., physiological parameter) in various embodiments, includes PWV, BCG, cardiac output, pre-ejection period, stroke volume, arterial stiffness, respiration, and/or other Rx health information.

[00110] As discussed in further detail herein, the validation is based on the data indicative of the user's identity. For example, the data indicative of the user's identity is the user ID and/or is associated with the user ID (e.g., is mapped to and/or otherwise correlated to). The external circuitry 112 and/or assessment circuitry 181, in some embodiments, communicates the determined clinical indication back to the scale and/or another user device for display to the user. Alternatively and/or in addition, the external circuitry 1 12 and/or assessment circuitry 181 control access to the clinical indication, as discussed further herein.

[00111] In accordance with a number of embodiments, the scale and the external circuitry 1 12 and/or assessment circuitry 181 provide additional health information to the user. The scale, for example, outputs user input data that provides an indication that the user is interested in additional (non-Rx) health information and various categories of interest. The categories of interest, in number of embodiments, include demographics of interest, symptoms of interest, disorders of interest, diseases of interest, drugs of interest, treatments of interest, etc. The additional health information, in some embodiments, is derived by the external circuitry 1 12 and/or assessment circuitry 181 and provided to the scale that correlates to the category of interest and a physiological parameter of the user. As previously described, the scale can (alternatively and/or in addition to a FUI or GUI) have a voice input/output circuitry that can obtain be used obtain the categories of interest from the user via voice comments and inputs user information in response (e.g., a speaker component to capture voice sounds from the user and processing circuitry to recognize the voice commands and/or speech).

[00112] Although the present examples embodiments provided above are in reference to external circuitry 112 performing the determination, embodiments in accordance with the present disclosure are not so limited. For example, the processing circuitry 104 determines the clinical indication while the user is standing on the platform 101.

[00113] FIG. lb shows an example of remotely determining physiologic parameters using an apparatus consistent with aspects of the present disclosure. The apparatus illustrated by FIG. lb can include the apparatus, including the platform 101 and user display 102, as previously illustrated and discussed with regard to FIG. la. As illustrated, the apparatus includes a platform, a user display configured and arranged with the platform and the plurality of electrodes to output user-specific information for the user while the user is standing on the platform, data-procurement circuitry 108, and processing circuitry 104. The data-procurement circuitry 108 includes force-sensor circuitry and a plurality of electrodes (e.g., the physiologic sensors) which are integrated with the data-procurement circuitry 108.

[00114] In various example processes, as illustrated by FIG. lb, the scale at block 114 waits for a user to stand on the platform. User-corresponding data 103 is input and/or received prior to the user standing on the scale and/or in response to. In response to the user standing on and/or approaching the scale, the apparatus can obtain identification data to identify the user. Example identification data, as discuss further herein with regard to FIG. 2a, includes the time of day, length of foot or other shape of foot, toe print, spoken words from the user, weight, height, facial features, etc. At block 116, the apparatus, using the processing circuitry 104, confirms identification of the user when the user is standing on the platform and/or as the user approaches the platform. The identification, in various embodiments, is based on the identification data and/or user data. For example, the processing circuitry 104 compares the identification data to stored user-corresponding data 103 to confirm identification of the user. Further, in some embodiments, additional user- corresponding data is obtained in response to the user standing on and/or approaching the platform.

[00115] In response to the user standing on the scale, the scale collects signals indicative of cardio-physiological measurements (e.g., force signals and impedance signals). The processing circuitry 104, at block 117, processes the signals to generate cardio-related physiologic data manifested as user data and outputs the user data to the external circuitry 112 and/or assessment circuitry, as previously described. In various embodiments, the processing includes adding (and later storing) data with a time stamp indicating a time at about when the physiologic parameter data is obtained.

[00116] The external circuitry 112 and/or assessment circuitry, at block 1 18, receives the user data, validates the user data as corresponding to the user using the user ID, and determines at least one physiologic parameter using the user-data. Example physiologic parameters includes PWV, BCG, respiration, arterial stiffness, cardiac output, pre-ej ection period, stroke volume, and a combination thereof. The external circuitry 112 and/or assessment circuitry then outputs the physiologic parameter. The output can be to the scale for display, such as illustrated at block 1 19 and/or to a memory circuit corresponding to the external circuitry 112. The scale, in various embodiments, updates the stored user- corresponding data 103 and/ physiologic user data 107 of the user as stored on the memory circuit of the processing circuitry 104 of the scale, at 120. [00117] In accordance with a number of embodiments, the scale including the processing circuitry provides a number of questions to the user. The questions can be provided via a speaker component of the scale outputting computer generated natural voice (via a natural language interface), displaying the questions on the user display, and/or outputting the questions to another user-device. In various embodiments, the questions include asking the user if the user is interested in additional health information and if the user has particular categories of interest. In various embodiments, the categories of interest include a set of demographics, disorders, diseases, and/or symptom that the user is interested, and/or other topics. The scale provides the input to the external circuitry 112 and the external circuitry 112 derives the additional health information for the user. The additional health information can include a table that corresponds to the categories of interest and/or corresponds to the physiologic parameter and/or clinical indications determined without providing any specific values and/or indication related to the physiologic parameter. The user is provided the additional health information by the external circuitry 112 and/or assessment circuitry outputting the information to the scale and/or another user-device, and the scale and/or other user-device displays the information. In various embodiments, the information can be printed by the user to bring to a physician. In various related-aspects, the scale using the processing circuitry 104 generates the additional health information instead of the external circuitry 1 12 and/or assessment circuitry. As previously described, the scale can have a voice input/output circuitry used to provide questions to the user and/or to obtain answers to the questions (e.g., a speaker component to capture voice sounds from the user and processing circuitry to recognize the voice commands and/or speech).

[00118] The additional health information is generated, in various embodiments, by comparing and/or correlating the categories of interest to raw data obtained by the data- procurement circuitry 108. In various embodiments, the correlation/comparison include comparing statistical data of a sample census pertinent to the categories of interest and the at least one physiologic parameter. The statistical data of a sample census includes data of other users that are correlated to the categories of interest. In such instances, the additional health information can include a comparison of data measured while the user is standing on the platform to sample census data (e.g., may contain prescription (Rx) information). In other related embodiments, the correlation/comparison includes comparing statistical data of a sample census pertinent to the categories of interest and values of the least one physiologic parameter of the sample census. In such instances, the additional health information includes average physiologic parameter values of the sample census that is set by the user, via the categories of interest, and may not include actual values corresponding to the user (e.g., does not contain Rx information).

[00119] For example, if the categories of interest are demographic categories, the additional health information can include various physiologic parameter values of average users in the demographic categories and/or values of average users with a clinical indication that correlates to a physiologic parameter of the user. Alternatively and/or in addition, the additional health information can include general medical insights related to the categories of interest. For example, "Did you know if you are over the age of 55 and have gained 15 pounds, you are at risk for a particular disease/disorder?" The scale can ask the user if the user would like to include this factor or disease in their categories of interest to dynamically update the categories of interest of the user.

[00120] Various categories of interest, in accordance with the present disclosure, include demographics of the user, disorders, diseases, symptoms, prescription or non-prescription drugs, treatments, past medical history, family medical history, genetics, life style (e.g., exercise habits, eating habits, work environment), among other categories and combinations thereof. In a number of embodiments, various physiological factors can be an indicator for a disease and/or disorder. For example, an increase in weight, along with other factors, can indicate an increased risk of atrial fibrillation. Further, atrial fibrillation is more common in men. However, symptoms of various disorders or disease can be different depending on categories of interest (e.g., atrial fibrillation symptoms can be different between men and women). For example, in women, systolic blood pressure is associated with atrial fibrillation. In other instances, sleep apnea may be assessed via an ECG and can be correlated to weight of the user. Furthermore, various cardiac conditions can be assessed using an ECG. For example, atrial fibrillation (AFIB) can be characterized and/or identified in response to a user having indistinguishable or fibrillating p-waves, and indistinguishable baseline/inconsistent beat fluctuations. Atrial flutter, by contrast, can be characterized by having indistinguishable p-wave, variable heart rate, having QRS complexes, and a generally regular rhythm. Ventricular tachycardia (VT) can be characterized by a rate of greater than 120 beats per minute, and short or broad QRS complexes (depending on the type of VT). Atrio-Ventricular (AV) block can be characterized by PR intervals that are greater than normal (e.g., a normal range for an adult is generally 0.12 to 0.20 seconds), normal -waves, QRS complexes can be normal or prolong shaped, and the pulse can be regular (but slow at 20-40 beats per minute). For more specific and general information regarding atrial fibrillation and sleep apnea, reference is made herein to https://wwwxlevelandclinicmededxonVmedicalpubs/diseasemanage ment/cardio fibrillation/ and http://circ.ahajournals.org/content/118/10/1080.full, which are fully incorporated herein for their specific and general teachings. Further, other data and demographics that are known and/or are developed can be added and used to derive additional health information.

[00121] For example, the categories of interest for a particular user can include a change in weight, age 45-55, and female. The scale obtains raw data using the data-procurement circuitry 108 and the categories of interest from the user. The scale outputs the raw data and categories of interest to the external circuitry 112 and/or assessment circuitry and the external circuitry 112 and/or assessment circuitry correlates the categories of interest to the raw data and derives additional health information therefrom. Further, the external circuitry 112 and/or assessment circuitry, over time, historically collects and correlates the categories of interest of the user and data from the data-procurement circuitry. The external circuitry 112 and/or assessment circuitry, in various embodiments, sends the data to a physician and/or additional health information to the user (to print and/or otherwise view).

[00122] In a number of embodiments, the external circuitry 112 and/or assessment circuitry determines additional physiologic parameters and/or data, such as further clinical indications, of the user using the determined physiologic parameter. For example, the determined physiologic parameter can include an ECG and the external circuitry 112 and/or assessment circuitry can determine a BCG using the ECG. Alternatively and/or in addition, the external circuitry 112 and/or assessment circuitry can determine a health status of the user using the determined physiologic parameter, such as a condition or treatment.

[00123] The scale can be used by multiple different users. A subset or each of the different users can have data output to external circuitry and/or assessment circuitry and can receive additional health data, related to different categories of interest. For example, each of a plurality of users have previously or current entered different categories of interest. The scale can store an indication of the categories of interest and as associated with each respect user. The scale and/or external circuitry can selectively track particular data based on the different categories of interest and provide the additional health data, which can be updated over time, responsive to recognizing a particular user.

[00124] The scale can be used in different settings and/or modes, such as a consumer mode, a professional mode, and a combination mode. A consumer mode includes a scale as used and/or operated in a consumer setting, such as a dwelling. As a specific example, a scale is located in a dwelling with five different people. Each of the five different people use the scale, and three of the five people have previously provided inputs to the scale that indicate different categories of interest. Prior to providing additional health information to a user, the identity of the respective user is verified via the scale using a scale-based biometric. Responsive to identifying the user, the scale identifies the particular categories of interest corresponding to the user, outputs all or portions of the data to the external circuitry. The external circuitry and/or assessment circuitry generates the additional health information based on the categories of interest and the user data, and outputs the same to the scale to provide to the user. As users in a consumer mode may be familiar with one another (e.g., live together), the identification of the user by the scale can be based on weight, body-mass- index, and/or other data. Although embodiments are not so limited and the identification can be based on other biometrics and/or passcodes.

[00125] In other instances, the scale is used in a professional setting, such as a medical office, and/or in a professional mode. A professional mode includes an operation of the scale as used and/or operated in a professional setting, such as a doctor's office, exercise facility, nursing home, etc. In a professional mode, the scale is used by different users that may not be familiar with one another. The different users may have services with the professional to track and/or aggregate data from a user device or other peripheral device and/or to provide health information. A peripheral device includes or refers to circuitry that is not integrated within the scale and can communicate with the scale via a wired or wireless connection. In some instances, a user can be provided additional health information as service while waiting for the professional, such as while waiting to see a doctor. The scale receives the additional health information from the external circuitry and either displays the additional health information using a user interface of the scale and/or via direct communication (e.g., WiFi, Bluetooth, NFC) with a user device (e.g., cellphone, tablet) that is within a threshold distance of the scale. Similar to the consumer mode, the scale can selectively provide the services by verifying the identity of the user using a scale-based biometric. The

identification can include a higher-level biometric and/or identification than the consumer mode.

[00126] As a specific professional mode example, a scale is located at a doctor's office and is used to obtain data from multiple patients (e.g., 10 in a day, 500 in a year). When a patient checks-in, they stand on the scale and the scale-obtained data is output to external circuitry for document retention and/or other purposes. A subset (or all) of the patients have activated a service with doctor that corresponds with and/or includes providing additional health information while the user is waiting and/or based on categories of interest. For example, a user indicates an interest in learning more about AFIB, which the scale outputs to external circuitry along with user data obtained by the scale. The external circuitry generates additional health information correlated with AFIB and the user data. For example, the additional health information includes various risks factors for AFIB and identifies lifestyle changes that can reduce the risk factors. The external circuitry communicates the additional health information to the scale via an Internet (or direct communication) connection and the scale outputs the additional health information to a cellphone of the user via an NFC or Bluetooth communication. The scale, in the professional mode, may be used to obtain data from more users than a scale used in a consumer setting.

[00127] The scale can also be in a combination consumer/professional mode. A combination consumer/professional mode includes a scale as used and/or operated in a consumer setting for purposes and/or uses by a professional, and/or in a professional setting for purposes and/or uses by the consumer (e.g., use by the consumer outside of the professional setting and/or in addition to). As a specific example, a scale is located at a user's dwelling and used by multiple family members. A first user of the family is diagnosed with a heart-related condition and the doctor may offer a service to review data from the scale (and optionally another user device) of the first user. When the other family members stand on the scale, the scale operates in the consumer mode. The other family members may or may not have the service activated for the doctor to review data and the scale operates via the consumer mode. When the first user that is diagnosed with heart- related condition stands on the scale, the scale recognizes the user and operates in a professional mode or a combination mode. For example, the scale outputs aggregated data from the scale to external circuitry that is accessible by the doctor of the first user.

[00128] Data provided to the user and/or the professional can default to be displayed on the user interface of the scale, the GUI of the user device, and/or a GUI of other external circuitry depending on the use of the scale. In a consumer mode and/or combination consumer/professional mode, data can default to display on the user interface of the scale. The defaulted display of data can be revised by the user providing inputs to display the data on the GUI of a user device or a GUI of another external circuitry (e.g., a standalone CPU) and/or automatically by the scale based on past scale-based actions of the user. As a specific example, a first user provided a user input to the scale to display data on the GUI of the user device multiple times (e.g., more than a threshold number of times, such as five times). In response, the scale adjusts the defaulted display and output data to the GUI of the user device. The display on the user interface of the scale and/or GUI of the user device (or other external circuitry) can include an indication of available additional health information, requests for categories of interest, and/or the additional health information, among other displays. In a professional mode, the scale is not owned by the user. The user may be uninterested in synchronizing their user device with the professional's scale. The display may default to the GUI of the user device to display an option to synchronize, and/or to override the synchrony. Alternatively, the display may default to the user interface of the scale to display an option to synchronize and, responsive to user verification or authority to synchronize, defaults to display on the GUI of the user device. During the combination consumer/professional mode, portions of scale-obtained data for a particular user may default to display on external circuitry, such as a standalone or server CPU that is accessible by the professional.

[00129] FIG. lc shows an example of a scale wireless communicating with external circuitry consistent with aspects of the present disclosure. The scale is configured to monitor signals and/or data indicative of physiologic parameters of the user while the user is standing on the platform 101 and communicate the signals and/or data to the external circuitry 112.

[00130] As discussed above, a scale in various embodiments includes a platform 101 , a user display 102, processing circuitry 104 include a plurality of electrodes, and output circuitry. The output circuitry is configured and arranged to send user data to the external circuitry 112 for assessment at a remote location. The external circuitry 112 is not integrated within the scale. The scale communicates user data wirelessly (and/or via the cloud 121) to and from the external circuitry 1 12 (which has integrated assessment circuitry). For example, the external circuitry 112 can determine at least one physiologic parameter. In some embodiments, the external circuitry 1 12 optionally controls access to the physiologic parameter by storing the parameter in a database corresponding with and/or integrated with the external circuitry 112. Alternatively and/or in addition (such as, in response to determining the user can access the parameter) the external circuitry 1 12 outputs the physiologic parameter to the scale for display and/or storage.

[00131] In various embodiments, the scale outputs user input data that provides an indication that the user is interested in additional health information and various categories of interest. As previously discussed, the categories of interest can include demographics of interest, symptoms of interest, disorders of interest, diseases of interest, drugs of interest, treatments of interest, etc. The additional health information can be derived by the external circuitry 112 and provided to the scale that correlates to the category of interest and a physiologic parameter of the user. [00132] For example, as illustrated by FIG. lc, the user provides user input/outputs to the scale via the user interface (e.g., FUI, GUI, and/or voice input/output circuitry) that can include the categories of interest. The scale obtains signals using the data-procurement circuitry and outputs user-weight to the user. Further, the scale outputs scale-based physiological raw data (e.g., the collected signals manifested as user data indicative of the user's identity and cardio-physiological measurements). As illustrated, the output can include a wireless communication to the external circuitry 112 using a cloud system 121. The external circuitry 112 validates the raw data as concerning a specific user and determines at least one physiologic parameter. In various embodiments, the external circuitry 112 determines clinical indications of the user. Further, the external circuitry 112 generates additional health information by correlating the raw data with the categories of interest and outputs the additional health information. For example, the external circuitry 112 outputs the addition health information to the scale and/or another user circuitry using the cloud system 121 and/or another wireless communication.

[00133] The external circuitry 112 can validate the received user data as corresponding to a particular user and correlates the received user data with a profile of the user based on identification metadata within the received user data and/or based on identification of the user using the user data. For example, in some embodiments, the processing circuitry of the scale correlates the user-corresponding data with the user data such that the user data includes identification metadata. The external circuitry 112 then identifies the user, validates the user data as corresponding to the user, and identifies the profile corresponding to the user using the identification metadata within the user data. The profile, in various embodiments, is a user health profile, such as a medical history file.

[00134] In some embodiments, the external circuitry 112 controls access to the user profile and/or the data. In some embodiments, the control of access includes allowing access to the physiologic parameter and the user data to a physician corresponding to the user for information. The control can include not allowing access to the physiologic parameters to the user. In various embodiments, the user is allowed to access the user data in the profile and the scale can display portions of the user data and/or other non-regulated data.

Additionally, the external circuitry 112 and/or assessment circuitry may not allow access to the profile and/or any data corresponding to the profile to non-qualified personal, such as other users. In various embodiments, the user is allowed access the physiologic parameter in response to interpretation by the physician and a prescription from the physician to access the physiologic parameter. Further, in some embodiments, a demographic model and/or other report is provided to the user in response to the physiologic parameter. For example, the user may not be allowed to view the physiologic parameter but is provided generic information corresponding to other users with similar physiologic parameter value. The user data may be collected and determined but the user is not allowed access to the features (and the related information is not display ed/displayable to the user), such as access to the user data or service related to the user data until government clearance is obtained. For example, the scale collects and stores the user data but does not display or otherwise allow the user access to the user data until clearance is obtained for each feature, which retrospectively enables the feature and/or service, at which time the features are accessible and the related information is display ed/displayable to the user (the display is unblocked thereby retrospectively enabling access). Alternatively and/or in addition, the feature and/or service is not provided until a weighted value is received (e.g., payment).

[00135] The access is controlled, in various embodiments, using a verification process. For example, in response to verifying identification of the physician and/or the user, access to particular data can be provided. The verification can be based on a user sign in and password, a password, biometric data, etc., and/or identification of the user using the scale (in which, the relevant data is sent to the scale or another user device in response to the identification).

[00136] In various embodiments, the physiologic parameter is provided as an additional service. For example, the user can obtain the information and/or have their physician interpret the information for a service fee. The service fee can include a one-time fee for a single interpretation, a monthly or yearly service fee, and/or can be a portion of a health care insurance fee (e.g., the user can purchase a health care plan that includes the service). In such embodiments, the physician corresponding to the user can access the physiologic parameter and/or other user data in response to verification that the user has enabled the service and verification of the identity of the physician.

[00137] The remote processing and/or controlled access, for example, allows a physician corresponding with the data to access the physiologic parameter for interpretation. For example, the physician can give a prescription to the user to access all information in the user profile. In response to the prescription, the extemal circuitry 112 and/or assessment circuitry allows the user to access the physiologic parameter. Further, the physician can prescribe medicine to the user based on the profile and the extemal circuitry 112 can provide an indication to the user that a prescription for medicine is ready. In various embodiments, the user data is compared against historical user data for the same user and used to analyze if the user's condition/treatment and risk is getting better or worse over time. The physician may provide instructions or further explanation for the user, which can be sent and displayed using the scale and/or another user-device. Such information can include life-style suggestions, explanation for how to use the prescribed medicine and/or why it is prescribed, and/or other advice, such as symptoms that the user should watch for. For instance, the physiologic parameter may suggest that the user has a heart condition and/or disorder. The physician may prescribe medicine to the user and/or provide potential symptoms that the user should watch for and/or should go to the physician's office or an emergency room if the symptoms arise. The scale and controlled access to prescription (Rx) health information is used to remotely monitor health of the user and/or provide physician services.

[00138] In various embodiments, the data is collected and determine but the user is not allowed access to features, such as access to the data or service related to the data until government clearance is obtained. For example, the scale collects and stores the historical but does not display or otherwise allow the user access to the data until clearance is obtained for each feature, which retrospectively enables the feature and/or service. Alternatively and/or in addition, the feature and/or service is not provided until a weighted value is received (e.g., payment).

[00139] In accordance with various embodiments, although not illustrated by FIG. lc, the apparatus includes an additional sensor circuitry that is external to the scale. The additional sensor circuitry can include a communication circuit and is configured and arranged to engage the user with electrical signals and collect therefrom signals indicative of an ECG of the user. The sensor circuitry, which may include and/or be correlated with processing circuitry configured to derive an ECG from the collected signals. The sensor circuitry communicates the ECG to the external circuitry 112 and/or assessment circuitry and the scale can communicate a BCG to the external circuitry 112 and/or assessment circuitry.

[00140] In various embodiments, the apparatus includes additional scales. For example, the external circuitry 112 can receive user data from a plurality of scales. In some embodiments, one or more of the scales are located at a physician's office, such as the physician corresponding with the user. The external circuitry 112 can receive user data from the scale located at the physician's office and can calibrate the user data from the scale at the physician's office with the user data from the scale corresponding the user. In this way, data obtained from both scales are relevant to one another. [00141] FIG. Id shows an example of apparatus including a plurality of scales and external circuitry consistent with aspects of the present disclosure. As illustrated, the apparatus includes a plurality of scales 128-1, 128-2... 128-P (herein generally referred to as "the scales 128") and external circuitry 1 12. Each scale can include the scale, including the platform and user display, as previously illustrated and discussed with regard to FIG. l a. Thereby, each scale includes a platform, data-procurement circuitry including force-sensor circuitry and plurality of electrodes which are integrated with the data-procurement circuitry, processing circuitry to receive collected signals from the data-procurement circuitry and, in response, derive and output user-data to the external circuitry 1 12. The user-data, in various embodiments, is automatically sent from the scales 128 to the external circuitry 1 12. As previously described, assessment circuitry can be integrated with the external circuitry.

[00142] In various embodiments, the apparatus is used to remotely determine and control access to physiologic parameters (e.g., Rx health information) of a plurality of users. The scales 128, for example, correspond to the plurality of users. For example, each scale at block 114 waits for a user to stand on the platform. User-corresponding data 103 is input and/or received prior to the user standing on the respective scale and/or in response to. In response to the user standing on the respective scale, the respective scale collects signals indicative of an identity of the user and cardio-physiological measurements. The processing circuitry, at block 117, processes the signals and, in response, derives and outputs user data to the external circuitry 1 12.

[00143] As illustrated, the external circuitry 1 12 validates the received user data as corresponding to a particular user and correlates the user data with a specific user/user profile, determine physiologic parameters, and optionally control access to the physiologic parameters. In various embodiments, the external circuitry includes computer-readable instructions executed to perform the various functions. For example, as illustrated by FIG. Id, the external circuitry includes correlation logic 123 to correlate the user data, physiologic parameter logic 124 to determine parameters, and access control logic 125 to control access, as described further herein.

[00144] The external circuitry 112 receives the user data that corresponds to the plurality users from the plurality of scales 128. The respective user data can be received at overlapping times and/or separate times. In response to receiving the user data, the external circuitry 1 12 and/or assessment circuitry, in various embodiments, identifies the respective plurality of users based on the user data and validates the user data as corresponding to the users and, at block 129, correlates the received user data with profiles of the respective plurality of users based on the identification of the users. In various embodiments, the users can be identified using identification metadata within the user data (e.g., user IDs). In a number of embodiments, the external circuitry 112 and/or assessment circuitry provides (e.g., determines) the physiologic parameters and/or clinical indications by processing the user data at block 130. The external circuitry 112 and/or assessment circuitry provides the physiologic parameters and/or clinical indications, in some embodiments, by updating the profile of the user with the user data and/or the physiologic parameter (s) at block 131. Alternatively, in some embodiments, the physiologic parameter(s) and/or clinical indications are output to the respective scale.

[00145] In various related embodiments, the external circuitry 1 12 and/or assessment circuitry determines additional health information and provides the additional health information to the scale for display to the user. The additional health information is indicative of the clinical indication and correlates to the categories of interest provided by the user. The categories of interest are be provided at a different time, the same time and/or from the scale. In various embodiments, the additional health information is based on historical user data.

[00146] In accordance with various embodiments, at block 132, the external circuitry 1 12 and/or assessment circuitry optionally controls access to the user profile, as previously described. Further, in some embodiments, a demographic model and/or other report is provided to one or more users in response to the physiologic parameter and/or categories of interest input by the user.

[00147] The controlled access can include a filter associated with the external circuitry and/or assessment circuitry (and/or the scale). For example, the user is not allowed to access the scale-obtained data that includes health information regulated by a government agency by way of a filter that disables scale-obtained physiological data, where such (FDA regulated) scale-obtained physiological data is blocked when it correlates with cardio-based diagnostic data stored in the user profile, whether obtained directly by the scale or provide externally by a physician and/or third-party device or entity. The filter, as used herein, includes circuitry and/or computer-readable medium (e.g., a module) that blocks access to the user if the data is scale-obtained physiological data and the user has not diagnosed or otherwise prescribed access to the data, for example. Scale-obtained physiological data includes the clinical indications determined using the scale-obtained data. For example, the filter includes and/or accesses a list of the scale-obtained physiological data that includes physiologic parameters (such as PWV, BCG, respiration, arterial stiffness, cardiac output, pre-ejection period, stroke volume), diagnosis, conditions, risk factors, among other health information that is regulated by the FDA. In some embodiments, the filter includes an AND gate, such as a three-way AND gate that blocks access to the data if the user wants access to the data, the data is scale-obtained physiological data, and the user is not diagnosed with a condition associated with the data or prescribed to access the data.

[00148] In various embodiments, the filter is achievable as follows. The user requests access to data in the profile. A determination is made as to whether the requested data falls into the category of scale-obtained physiological data. In response to determining the requested data is not scale-obtained physiological data, the user is provided access to the data. In response to determining the requested data is scale-obtained physiological data, a determination is made as to whether the user has been diagnosed with a condition associated with the requested data and/or if the user has been prescribed access to the requested data by a physician. If the user has not been diagnosed or prescribed access, the user is not allowed to access the requested data. In response to determining the user has been diagnosed or prescribed access, the user is provided access to the requested data. A condition associated with the request data includes, for instance, a condition that results in the scale-obtained physiological data and/or the scale-obtained physiological data is otherwise indicative of the condition. The diagnosis is obtained by the scale (e.g., stored in a user profile), and/or provided externally by a physician and/or third-party device/entity. For example, the profile is associated with a diagnosis and used to access the requested data.

[00149] In other embodiments, the filter is achievable as follows. The user requests access to data in the profile. A determination is made as to whether the user has been diagnosed with a condition associated with the requested data and/or if the user has been prescribed access to the requested data by a physician. In response to determining the user has been diagnosed or prescribed access, the user is provided access to the requested data. If the user has not been diagnosed or prescribed access, a determination is made as to whether the requested data falls into the category of scale-obtained physiological data. In response to determining the requested data is not scale-obtained physiological data, the user is provided access to the data. In response to determining the requested data is scale-obtained physiological data, the user is not allowed to access the requested data. Further, embodiments in accordance with the present disclosure are not limited to the examples provided and the filter blocks access to the requested data in a variety of manners. For example, the filter allows and/or blocks access to requested data based on a determination of physician approval (e.g., diagnosis or prescription) and categorization of the requested data as scale-obtained physiological data.

[00150] In various embodiments, the clinical indication is provided as an additional service. For example, the user can obtain the information and/or have their physician interpret the information for a service fee. The service fee can include a one-time fee for a single interpretation, a monthly or yearly service fee, and/or can be a portion of a healthcare insurance fee (e.g., the user can purchase a health care plan that includes the service). In such embodiments, the physician corresponding to the user can access the clinical indications and/or other user data in response to verification that the user has enabled the service and verification of the identity of the physician.

[00151] In accordance with various embodiments, the one or more scales 128 have the capability to send raw force signals using wireless communications and/or over the Internet. The raw force signals are sent to the external circuitry 112, which may be an online database, where advanced processing is performed using processing resources that may be more powerful than the scale. The external circuitry 112 processes the force signals to determine the physiologic parameters. The user may access the one or more the physiologic parameters corresponding to the user via a prescription from a physician and/or a prescription service. The service provider can, for example, allow the user's physician to access the physiologic parameter and other data for interpretation in response to the user paying a service fee. In response to the service fee, the physician can interpret the data and may prescribe access to the data, among other things. The external circuitry 112 and/or online database/site can track user data for a plurality of users and from a plurality of scales and can correlate the user data with a profile of the respective user (e.g., using the access database 127 containing correlations or permissions to user profiles and the user-profile database 126 containing the user profiles and corresponding user data). The profile of the user can be updated over time. Access to each respective profile is controlled and only allowed to the user's physician. The user's physician can be identified upon establishing the profile with the service provider and/or initializing the scale. For example, the user can purchase a scale over the counter and not pay for the service. The scale and the service provider track the relevant data over time and allow access in response to a fee.

Alternatively, the service provider may discard the information (not determine clinical indications) until the service is established.

[00152] FIG. le shows an example scale communicatively coupled to external circuitry and various data types provided to a user, consistent with various aspects of the present disclosure. The scale as illustrated by FIG. le includes the scale illustrated by FIG. la and/or FIG. lb.

[00153] The various data types provided to the user, in some embodiments, are used to monitor AFIB. AFIB, for example, causes additional problems, such as sleep deprivation and depression. Further, as discussed above, it has been recently discover that AFIB is more directly correlated to obesity and, in particular, to recent weight gains. As illustrated by FIG. le, at block 133, excess weight is reported by the scale. The excess weight, in some embodiments, includes an indication that the user is obese based on a user weight measured using the scale, and a height and age input by the user. In various embodiments, the scale provides an indication of a recent increase of weight over a threshold value. In accordance with a number of embodiments, the scale provides suggestions to the user, such as goals for losing weight.

[00154] The excess weight causes, for some users, sleep apnea. As such, at block 134, sleep apnea is reported to the scale by a sleep-circuit sensor, by a user, and/or as part of physician provided diagnosis/reports data. The sleep-circuit sensor includes, in various embodiments, a smart bed or other user sensor circuitry (e.g., cell phone laying on the bed, Fitbit®, etc.) that measures cardiogram data and/or movement data while the user is sleeping. In various embodiments, whether or not the user has sleep apnea is unknown by the scale. In such embodiments, the scale can display an advertisement for a sleep-circuit sensor to the user using the FUI. Further, the scale, in some specific embodiments and in response to reporting of sleep apnea input to the scale, displays an advertisement for prescription medicine for sleep apnea, treatments for sleep apnea, and/or a physician or study for sleep apnea, among other advertisements.

[00155] In various embodiments, sleep apnea causes sleep deprivation. At block 135, in response to reporting of sleep apnea and/or an advertisement for a sleep-circuit sensor, the scale provides sleep deprivation suggestions to the user. The sleep deprivation suggestions, in some embodiments, include suggestions to see a physician for sleep apnea, exercise advice, or dietary advice, among other suggestions. Sleep deprivation causes various other problems, such as heart problems, tiredness and slow metabolism (which correlate to the excess weight of the user), and/or leads to prescription medication. Further, sleep deprivation causes depression. At block 136, in response to the sleep deprivation suggestions, the scale provides depression suggestions to the user, such as using the FUI. The suggestions include prescription medications suggestions, exercise advice, suggestions to see a physician, among other suggestions. Further, the scale, in some embodiments, provides advertisements for specific depression prescription medication, physician specializing in depression or trials for depression, and/or exercise or dietary programs, among other advertisements. Depression, in various embodiments, causes tiredness and slow metabolism and results in prescription medication.

[00156] Further, in some embodiments, depression causes sleep cycle and eating problems. For example, a user that is depressed may stay up late and which may result in eating additional snacks. At block 137, in response to the depression suggestions and/or reports of sleep cycle or eating issues input to the scale, the scale provides sleep cycle and eating suggestions. For example, another user wearable device, in some embodiments, reports the sleep cycle or eating issue to the scale. As a specific embodiment, a user may wear a wearable device (e.g., Fitbit ®) to track various data, such as cardiogram data, exercise data, and sleep cycle data. Further, the user inputs eating habits to the wearable device. The wearable device, in such embodiments, communicates the sleep cycle and eating habit data to the scale. The sleep cycle and eating suggestions, in various

embodiments, include suggestions to improve the user's sleep cycle (e.g., indication of hours sleeping, exercise advice, dietary advice, such as a time of the day to stop eating), dietary advice, exercise advice, among other lifestyle advice (e.g., stop watching television one hour before bed). Sleep cycle and eating issues cause, in various embodiments, the excess weight of the user. Further, excess weight is correlated to tiredness and slow metabolism.

[00157] In various embodiments, the scale and various user data is used to monitor AFIB of the user and various related problems of AFIB. Various scale-based suggestions and advertisements are provided to the user, such as using the FUI, to assist in monitoring the user's condition, monitoring symptoms or related problems, and educating the user on symptoms, related problems, and the correlation thereof. Further, physician provided diagnosis/reports data is used to refine the monitoring of the condition and provide feedback to the user. The excess weight causes and/or increases the risk, for some users, AFIB.

Further, a recent increase in weight that is over a threshold amount can also include an increased risk for AFIB. The scale is used to monitor BCG, IPG, PWV, and other cardio- indicators of AFIB (e.g., rhythm disturbance, amplitude variations in BCG and/or IPG).

[00158] FIG. If shows an example apparatus for pooling scale data, consistent with various aspects of the present disclosure. The apparatus includes one or more scales, reference information 138, and user-specific knowledge database 139. Each scale (or one or more of the scales) collects user data that is indicative of cardio-related measurements and outputs the user data to external circuitry 1 12. The external circuitry 112 includes assessment circuitry, the reference information 138 and/or the user-specific knowledge database 139 and/or is in communication with the same. The external circuitry 112, in various embodiments, matches the scale-based user data to risks correlating to one or more physiologic/medical conditions using the reference information 138 and/or the user-specific knowledge database 139, as described in further detail herein. The risk-based data includes a probability that the user has the condition and, in some embodiments, additionally includes a severity of the condition. The severity includes a general severity of the condition (e.g., an ingrown toenail is generally not severe) and/or a user specific severity of the condition (e.g., how severe the condition is for the user and tailored to user data obtained from the user). Each scale includes a platform and a user display, and can optionally include a scale as illustrated and further described by FIG. la including the processing circuitry 104, output circuit 106, data-procurement circuitry 108, force sensor circuitry 109, and physiologic sensors 111. In a number of embodiments, the processing circuitry 104 and/or the scale includes an output circuit 106. The output circuit 106 receives the user data and, in response, sends the user data from the scale for reception at a remote location (e.g., to external circuitry 112 for assessment). In various embodiments, the output circuit 106 displays on the user display 102 the user's weight and the data indicative of the user's identity and/or the generated cardio-related physiologic data corresponding the collected signals.

[00159] The external circuitry 112 (and/or assessment circuitry), in various

embodiments, includes a processing circuitry, output circuitry, and a memory circuit including reference information 138. The reference information 138 includes data and statistics of a variety of conditions, symptoms, parameters values indicative of conditions, assessment data of people experiencing the condition, government provided health information and/or databases, and a combination thereof. The reference information 138 is stored in a structured database and/or in an unstructured database. In some embodiments, the reference information 138 includes the user-specific knowledge database 139. The user- specific knowledge database 139 includes pooled user data from a plurality of scales that is updated over time. Data from the scales is pooled in the user-specific knowledge database 139 and, in some embodiments, is used to identify trends, risks, and/or parameter values associated with and/or indicative of particular conditions.

[00160] The external circuitry 112 and/or assessment circuitry receives the user data and identifies a risk that the user has a condition using the reference information 138 and the user data provided by the scale. The risk is identified by comparing the user data to the reference information 138 (and/or the user-specific knowledge database 139) and identifying a match. The risk of a condition, as previously discussed, includes a probability that the user has the condition and a severity of the condition.

[00161] In response to identifying the risk, the external circuitry 112 (and/or assessment circuitry) derives and/or identifies and outputs generic health information correlating to the condition to the scale. The generic health information is tailored to the user based on the identified risk. As previously discussed, the generic health information includes information on risk factors for the condition, symptoms of the condition, and suggestions. The generic health information does not indicate that the user has the condition or the risk of the condition identified, in a number of embodiments. In various embodiments, the generic health information includes advertisements, such as advertisements for physician

specializing in the condition, prescription medication, health groups, etc.

[00162] In various embodiments, the generic health information is output to the scale based on multiple thresholds. For example, the external circuitry 112 outputs the generic health information to the scale in response to the probability of the user having the risk being greater than a first threshold and the severity of the condition being greater than a second threshold. In some embodiments, the threshold is only that the probability is greater than a threshold and does not include the severity being greater than a second threshold. Further, the user, in some embodiments, can adjust the thresholds to tailor the information provided based on their needs and/or amount of information that they would like to receive.

Alternatively and/or in addition, the generic health information is output to another user device. For example, the scale enables the output to another user device in response to a verified scale-based biometric that authorizes the communication, as discussed in further detail herein.

[00163] The scale and/or other user device can be used as feedback in response to the identified risk. For example, the external circuitry 112 (and/or assessment circuitry), in response to the identified risk, determines questions to ask the user and/or additional tests to perform and outputs the number of questions to the scale to ask the user and/or the additional tests to perform. The questions include asking if the user has a diagnosis from a doctor, asking if the user is experiencing particular symptoms, and asking the user for family medical information. The scale, using the processing circuitry 104 and the user display 102, provides the number of questions to the user (including asking if the user has a symptom occurring). The scale outputs the response to the questions (e.g., the answers as input to the scale by the users) to the external circuitry 112 and the external circuitry 112 verifies and/or adjusts the risk using the responses to the questions. For example, in various embodiments, a user may not realize they are experiencing a symptom (e.g., heart rate is raised and/or difficulty breathing). The questions ask the user about potential symptoms of the condition identified (e.g., associated with the risk) and is used to revised the risk determined. The user is provided with generic health information about the condition that may include the various symptoms to assist the user in recognizing the symptoms and discussing the same with their physician. In specific embodiments, the questions are provided and/or the answers are obtained using voice input/output circuitry, as previously described.

[00164] In a number of embodiments, the scale asks the user about diagnosis from a physician. For example, the user may have been diagnosed with heart failure and the user inputs this knowledge to the scale. The scale outputs the response to the external circuitry and the external circuitry 112 identifies misdiagnosis information associated with the condition. For example, in some instances, when a user is diagnosed with condition Y, they actually have condition X. The external circuitry (and/or assessment circuitry) determines and outputs generic misdiagnosis information to the scale. The generic misdiagnosis information includes or refers to rates of misdiagnosis for the condition the user is diagnosed with and potential other conditions or causes of the misdiagnosis. The misdiagnosis information may not identify or state that the user is misdiagnosed or at risks for misdiagnosis but rather provides general statistics and identification of the causes of the misdiagnosis. The misdiagnosis information can be based on historical data, clinical data, and/or pooled scaled-data from a plurality of scales.

[00165] In other related embodiments, the external circuitry 112 (and/or assessment circuitry), in response to the identified risk, determines additional tests or measurements to be performed. In various embodiments, the scale is used to perform the additional test and/or other circuitry is used. For example, the external circuitry 112 determines and outputs a test, to the scale, for the scale to perform. The scale, including the data- procurement circuitry, performs the test and outputs results to the external circuitry 112. Using the results, the external circuitry 112 verifies and/or adjusts the risk. Furthermore, the user data and/or results from the test are used to update the user-specific knowledge database 139. Alternatively and/or in addition, the external circuitry 112 determines an additional user device to perform the test. The external circuitry 112 provides an advertisement for the additional user device to the scale to display to the user.

[00166] Although the present examples embodiments provided above are in reference to external circuitry 112 performing the determination, embodiments in accordance with the present disclosure are not so limited. For example, the processing circuitry 104 of the scale and/or assessment circuitry (integrated with the scale or with the external circuitry 112) can determine the risk by accessing the reference information 138 or the feedback information while the user is standing on the platform 101.

[00167] In various specific embodiments, in response to the user standing on and/or approaching the scale, the scale obtains identification data to identify the user. Example identification data, as discuss further herein with regard to FIG. 2a, includes the time of day, length of foot or other shape of the foot, toe print or toe tapped password, spoken words from the user, weight, height, facial features, etc. The apparatus, using the processing circuitry 104, confirms identification of the user when the user is standing on the platform and/or as the user approaches the platform. The identification, in various embodiments, is based on the identification data and/or user data. For example, the processing circuitry 104 compares the identification data to stored user-corresponding data 103 to confirm identification of the user. Among the examples discussed below, in certain embodiments the scale is designed to access scale-obtained bio-metric data (e.g., foot size or shape, expected heartrate of the user at a certain time of day, weight, toe-print and wave shapes of the user's cardiograph such as QRS complex, BCG characteristics, range of beat-to-beat fluctuation, etc.). Exemplary embodiments of the scale are designed to use the bio-metric/ identification data to distinguish (or sufficiently identify) users who stand on or approach the scale and, in response, the scale correlates scale-obtained data with a user profile corresponding to the identified user.

[00168] FIG. lg shows an example of various communication and feedback provided using a scale-based user-physiological heuristic system consistent with aspects of the present disclosure. Although the embodiment of FIG. lg illustrates one scale, the scale-based user- physiologic heuristic system includes a plurality of scales in communication with external circuitry. The external circuitry includes processing circuitry and a memory circuit. In various embodiments, the memory circuit of the external circuitry stores various reference information 138. In other embodiments, the reference information 138 is external to the external circuitry and the external circuitry accesses the various reference information 138.

[00169] As discussed above, a scale in various embodiments includes a platform 101 , a user display 102, processing circuitry include a plurality of electrodes, and output circuitry. The output circuitry is configured and arranged to send user data to the external circuitry for assessment at a remote location. Using the user data from the scale, the external circuitry compares the user data to the various reference information 138 to identify one or more risks that the user has a condition. In response to a match, the external circuitry identifies a risk and outputs generic health information to the scale that is based on the identified risk.

[00170] In various embodiments, the reference information 138 includes statistical data of a sample census pertinent to the categories of interest and the at least one physiological parameter. The statistical data of a sample census includes data of other users that are correlated to condition. In such instances, the risks identification includes a comparison of data measured while the user is standing on the platform to sample census data (e.g., may contain Rx information).

[00171] The external circuitry can provide additional feedback information to the scale. For example, in response to the identified risk, an additional test to perform is identified by the external circuitry for the scale (or another user device) to perform. In some

embodiments, the scale performs the additional test and outputs the results to the external circuitry. Using the results, the external circuitry revises and/or verifies the identified risk. Alternatively and/or in addition, in response to the identified risk, the external circuitry provides a number of questions to the scale to provide the user. The questions include questions to determine symptoms the user is having, medical history, diagnosis information, etc. For example, the scale can provide the questions to the user and output the responses back to the external circuitry. Using the responses, the external circuitry verifies and/or adjusts the risk identified.

[00172] The external circuitry can update a user-specific knowledge database 139 using various user information. The external circuitry and/or the scale updates the user-specific knowledge database 139 with the user data, the test results, and the responses to the questions. For example, the responses to the questions may identify a diagnosis the user has from a doctor and/or additional symptoms the user is experiencing. This information is used to dynamically update the user-specific knowledge database 139 and potentially revise (e.g., increase or decreases) risks identified by the external circuitry. For example, the external circuitry validates the received user data/user information as corresponding to a particular user (associated with an alias ID as further described herein) and correlates the received user data with other user data stored in the user-specific knowledge database 139. The external circuitry then updates the user-specific knowledge database 139 with the user data and/or other feedback data obtained.

[00173] For example, in a number of embodiments, the scale including the processing circuitry provides a number of questions to the user in response to input from the external circuitry. The questions can be provided via a speaker component of the scale outputting computer generated natural voice (via a natural language interface), displaying the questions on the user display 102, and/or outputting the questions to another user-device. The scale provides the input to the external circuitry and the external circuitry verifies or revises the risk identified. Further, the external circuitry updates the user-specific knowledge database 139.

[00174] A risk of a user for a condition can be identified and/or adjusted based on demographics of the user, disorders, disease, symptoms, prescription or non-prescription drugs, treatments, past medical history, family medical history, genetics, life style (e.g., exercise habits, eating habits, work environment), among other categories and combinations thereof. In a number of embodiments, the scale is designed to obtain physiological factor(s) of a particular user of the scale wherefrom the scale helps to identify/diagnose/prescribe a disease and/or disorder correlating to the physiological factor(s) and/or to other user-specific attributes. For example, an increase in weight, along with other factors, can indicate an increased risk of atrial fibrillation and particularly for certain types of demographics (e.g., obese women over the age of 70 and with a history of anxiety). As the scale is designed to assess and track the body weight the user and the scale includes or has access to a memory circuit (database) with the user's demographics/physiological profile (e.g., age, weight, diet, medications, activities, pharmaceutical prescriptions, etc.), the scale is also designed to obtain cardio-based physiological factors of the user and to use these cardio-based physiological factors as an automated research tool to assess risks and data indicative of the user having or being prone to have identifiable diseases and/or disorders correlating to these physiological factors.

[00175] Information associated with or resulting from these automated scale-prompted activities, is made available to the user of the scale and, as may be permitted by or on behalf of the user, is selectively shared with other user-specified individuals or entities.

Accordingly to various exemplary embodiments, the scale is designed to use and provide such information based on how the user has configured and/or has already used the scale. As discussed above, the scale may be used for obtaining such generic health information that would be specific to the user and this may include life-style suggestions based on the user's scale-obtained physiological parameters and/or stored user-profile data, suggested user- specific prescription medicine and/or reasons on why should be prescribed, and/or other advice such as symptoms for which the user has been, or should be, on the lookout. For instance, the user data may suggest that the user has a heart condition and/or disorder. The scale efforts (and/or the scale's display) may suggest generic health information suggests prescription medicine to the user to ask their physician about and/or provides potential symptoms that the user should watch for and/or should go to the physician's office or an emergency room if such symptoms were to arise.

[00176] In accordance with various other related embodiments, the feedback provided to the user includes advertisements for various tools, resources, medications, and/or devices. For example, in response to identifying the user is at risk for developing pneumonia, an advertisement for decongestants and/or other medications is displayed to the user. Further, in response to the user being at risk for atrial fibrillation, an advertisement for a health facility (e.g., gym), a physician specializing in heart issues, and/or weight loss program is displayed to the user. Further, the advertisements provided to the user, in some

embodiments, are correlated to the risk and/or input user goals. For example, the user may be training for a marathon and the scale identifies that the user is at risk for athletic asthma. The user is then provided an advertisement for a prescription medication for athletic asthma that is tailored to athletes, training programs for marathons, that may specialize in athletes with asthma, and/or devices that track progress in training and/or track the asthma for the user (e.g., Fitbit or other user device), among other advertisements. Example advertisements include physicians specializing in conditions, devices used to track progress in training, weight loss and/or symptoms, programs to assist with training and/or other health issues (e.g., gyms, weight loss programs, training programs), prescription medication, nonprescription medication, exercise equipment, food delivery services, and/or research programs, among other advertisements.

[00177] The advertisement provided, in some embodiments, are thereby tied to the risk or the condition, are based on user inputs, correlate to user goals, and/or correlated to demographic information of the user, or a combination thereof. For example, based on the user data obtained, the extemal circuitry identifies that the user is at risk for a heart disease. The user has provided inputs to the scale indicating that the user is training for a marathon and that the user is over fifty years old. The external circuitry identifies the risk and identifies a prescription medication associated with the heart disease that is targeted for athletes and/or people over fifty years old. The extemal circuitry outputs the advertisement to the scale for display to the user.

[00178] The scale, in various embodiments, receives the advertisement (or other generic health information) and discerns where and/or how to display the advertisement. For instance, the scale includes a user display (e.g., a foot-controlled user display) that has limited space. Based on the amount of data, the height of the user, and/or past user responses, the scale discerns whether to display the advertisement on the scale or output the advertisement to another user device. For example, the scale displays a synopsis, a subset of the total data, and/or an indication of an advertisement on the user display of the scale which includes an icon for the user to select to view more information. In response to the user selecting the icon, the scale outputs the advertisement to another user device, such as the user's smartphone and/or displays the advertisement on the user display. Alternatively, in response to the user selecting the icon, the scale displays another one or more icons for the user to select which device to display the advertisement on. Based on the user inputs, the scale automatically displays subsequent feedback, generic health information, and/or advertisements based on how the user responds in the past and/or over time. For example, if the user continuously displays the advertisement on their smart phone, the scale outputs the advertisement to the user's smartphone. By contrast, if the user does not indicate an interest in particular advertisements, the scale does not display the advertisements. The scale displays or outputs the generic health information and/or advertisements in response to verifying a scale-based biometric, in various embodiments.

[00179] The system can include additional scales than illustrated. For example, the external circuitry receives user data from a plurality of scales located at a variety of locations. The user data, in various embodiments, is automatically sent from the scales to the external circuitry. The external circuitry is configured to identify risk for various users using the data from the plurality of scales, output generic health information, and updated the user- specific knowledge database.

[00180] For example, the external circuitry receives the user data that corresponds to the plurality users from the plurality of scales. The respective user data is received at overlapping times and/or separate times. In response to receiving the user data, the external circuitry, in various embodiments, identifies the respective plurality of users based on the identifiers and/or other identifying data and, correlates the received user data with profiles of the respective plurality of users. In a number of embodiments, the external circuitry identifies (e.g., determines) risks for each of the users for having conditions by comparing the user data with reference information. The external circuitry outputs the generic health information to the scales that is tailored to each respective user based on the risk for the condition. The external circuitry further instructs the scales to collect feedback data, including symptoms experiences, demographic information, medical history information etc., and uses the feedback data to revise and/or verify the risk. In some embodiments, the feedback data and the user data is used to update a user-specific knowledge database 139, which is used to refine the identified risks for other users.

[00181] In accordance with various embodiments, the external circuitry and/or online database/site can track user data for a plurality of users and from a plurality of scales and correlates the user data and feedback data with various conditions in a user-specific knowledge database 139. The correlation are used to further refine the identification of risks for other users and/or for subsequent identifications.

[00182] The scale can be used by multiple different users. A subset or each of the different users can have data output to external circuitry and can receive generic health information in response to an identified risk for a condition. The scale and/or external circuitry can store the user data and identify the one or more risks based on reference information. Based on the risk and tailored specifically to the respective user, the external circuitry generates and outputs generic health information to the scale. In response, the scale provides the user access to the generic health information. The scale and/or external circuitry can selectively track particular data and obtain additional data to the user to refine the risk and generate updated generic health information. In some embodiments, the scale and/or external circuitry generate the generic health information with or without user interest. For example, the external circuitry generates the generic health information and outputs to the scale without the user indicating an interest. The scale can querying the user to indicate availability of the generic health information and to obtain a user input to activate a service for access to the generic health information. The user may not be provided with the generic health information until the user provides an input indicating interest in the data and/or otherwise activates a corresponding service.

[00183] As described in the above-provided examples, the generic health information can be provided as a service and/or calculated and stored until the service is activated. In some embodiments, the user may never access the data and stops using the scale (e.g., deactivates an account). In other embodiments, the user deactivates the particular service (e.g., stops providing the weighted value that activates the service) that provides access to the generic health information. The scale and/or external circuitry, in such embodiments, may store the user data, including the risk, generic health information, and subsequently tracked data, with or without user identifying information for future use (e.g., retains previous processed data and can provide to other people or the user for weighted values). For example, the external circuitry may provide user data for research purposes (while removing user identifying information) and/or the user may subsequently re-activate the service or obtain another scale. In the event that a user deactivates a service, the scale may periodically provide a reminder to the user of the availability of generic health information, such as by outputting an email message, a text message to a cellphone, and/or displaying a messaged on a user interface of the scale.

[00184] As previously described, the scale can be used in different setting and/or modes, such as a consumer mode, a professional mode, and a combination mode. As a specific consumer use example, a scale is located in a dwelling with five different people. Each of the five different people use the scale, and two of the five people have previously provided inputs to the scale that indicate an interest in generic health information. Prior to providing the generic health information to a user, the identity of the respective user is verified via the scale using a scale-based biometric. Responsive to identifying the user, the scale identifies the user has indicated interest in the generic health information (e.g., activates a service) and outputs all or portions of the data to the external circuitry.

[00185] As another specific consumer use example, a first user has previously identified an interest in the generic health information and, when the user stands on the scale, the scale identifies the first user using a scale-based biometric. The scale provides the first user with the generic health information, such as by displaying the data on the user interface of the scale or outputting to another user device. A second user stands on the scale (that has previously identified generic health information and tracking of data for diagnosis purposes (e.g., with a prescription from a physician) for the second user) and, responsive to identifying the second user using a scale-based biometric, the scale provides the generic health information and provides potential prescription data responsive to a prescription from a physician. The scale, in some embodiments, outputs a request to the external circuitry for the prescription and the external circuitry may output a response on an estimated time for receiving the prescription and/or the availability or unavailability of the prescription at that time. The scale provides an indication of the estimated time and/or unavailability of access to the prescription level data responsive to not receiving the prescription. In response to receiving the prescription from the external circuitry, the scale provides the user with access to the prescription level data. A third (or more) user that has not yet provided an indication of an interest stands on the scale. In response, the scale recognizes (or not) the third user, the scale provides the third user with the reminder of the availability of generic health information and prompts the user to input an interest in the same. As users in a consumer mode may be familiar with one another (e.g., live together), the identification of the user by the scale can be based on weight, body-mass-index, and/or other data. Although embodiments are not so limited and the identification can be based on other biometrics and/or passcodes.

[00186] As a specific professional mode example, a scale is located at a doctor's office and is used to obtain data from multiple patients (e.g., 10 in a day, 500 in a year). When a patient checks-in, they stand on the scale and the scale-obtained data is output to external circuitry for document retention and/or other purposes. A subset (or all) of the patients have activated a service with doctor that corresponds with and/or includes providing generic health information while the user is waiting and/or based on categories of interest. For example, a user is diagnosed by the physician with AFIB at a prior time and the physician provides a prescription to review specific data about AFIB, which the scale outputs to external circuitry along with user data obtained by the scale. The external circuitry generates generic health information correlated with AFIB and the user data. For example, the generic health information includes various risks factors for AFIB and identifies lifestyle changes specific to the user that can reduce the risk factors.

[00187] The scale can also be in a combination consumer/professional mode. As a specific example, a scale is located at a user's dwelling and used by multiple family members. A first user of the family is diagnosed with a heart-related condition and the doctor may offer a service to review data from the scale (and optionally another user device) of the first user. When the other family members stand on the scale, the scale operates in the consumer mode. The other family members may or may not have the service activated for the doctor to review data and the scale operates via the consumer mode. When the first user that is diagnosed with heart-related condition stands on the scale, the scale recognizes the user and operates in a professional mode or a combination mode.

[00188] Data provided to the user and/or the professional can default to be displayed on the user interface of the scale, the GUI of the user device, and/or a GUI of other external circuitry depending on the use of the scale. In a consumer mode and/or combination consumer/professional mode, data can default to display on the user interface of the scale. The defaulted display of data can be revised by the user providing inputs to display the data on the GUI of a user device or a GUI of another external circuitry (e.g., a standalone CPU) and/or automatically by the scale based on past scale-based actions of the user. As a specific example, a first user provides a user input to the scale to display data on the GUI of the user device multiple times (e.g., more than a threshold number of times, such as five times). In response, the scale adjusts the defaulted display and outputs data to the GUI of the user device. The display on the user interface of the scale and/or GUI of the user device (or other external circuitry) can include an indication of available generic health information and/or the generic health information, among other displays. In a professional mode, the scale is not owned by the user. The user may be uninterested in synchronizing their user device with the professional's scale. The display may default to the GUI of the user device to display an option to synchronize, and/or to override the synchrony. Alternatively, the display may default to the user interface of the scale to display an option to synchronize and, responsive to user verification or authority to synchronize, defaults to display on the GUI of the user device. During the combination consumer/professional mode, portions of scale-obtained data for a particular user may default to display on external circuitry, such as a standalone or server CPU that is accessible by the professional.

[00189] In various embodiments, the external circuitry uses the user-specific knowledge database 139 to identify users with correlations. The correlation, in some embodiments, includes patterns and/or trends, risks, and/or parameter values associated with and/or indicative of particular conditions that are common between different users. For example, the external circuitry identifies other users that have correlated user data and identify patterns of risks for conditions or diseases based on the correlation. Identifying correlated user data, for instance, includes grouping respective sets of user data into groups based on various criteria. The criteria includes symptoms, physiological parameter values, diagnosis, prescription drug usage, lifestyle habits, medical history, family medical history, and a combination thereof.

[00190] Based on the correlated user data sets, the external circuitry in some

embodiments groups the users into a social group and generates a forum, blog, and/or webpage for the users of the social group to access. The users are notified of the availability of a social group via a prompt provided using the user interface (e.g., FUI, GUI, and/or voice input/output circuitry) of the scale the next time the user stands on the scale (and the scale recognizes the user using a scale-obtained biometric) and/or on a user interface of another user device. The prompt includes an indication that a social group is available. In various embodiments, the prompt provides a direct link to the generated forum, blog and/or webpage. In a specific embodiment, the user accesses the social group by clicking the direct link on the GUI or FUI of the scale and/or on the user interface of another user device. Further, the identity of the users remains anonymous and/or the user can select a code-name.

[00191] In various embodiments, the forum, blog, and/or webpage includes reports and/or dashboards automatically generated and displayed by the external circuitry using the user-specific knowledge database 139. The reports and/or dashboards include rankings of the user based on scale-obtained data, progress (e.g., increases or decreases in physiological parameters, weight, etc.), diagnoses, symptoms, treatments receiving, and other scale- obtained data. For example, a progress report includes increases and/or decreases in physiological parameters and/or weight of the users of the social group and identifies potential causes of the increase or decrease (e.g., correlations based on scale-obtained data and/or data from other user devices).

[00192] The external circuitry (and/or assessment circuitry) can identify and normalize user data from the user data sets of the subset of users (with the identified correlation) based on prioritization data and normalization data. The access to the social group includes selective access to the normalized user data. Normalized user data includes portions of user data from the user data sets selected using the priority data that is normalized using the normalization data. The prioritization data and/or normalization data can be default values and/or based on user input. For example, the user can provide inputs to the scale to adjust a priority level, indicate to not display particular data, adjust a sensitivity level, and/or adjust normalization values. When the user verifies an interest in participating in the social group, the user can view how their normalized user data is seen by others in the social group, such as via a FUI of the scale and/or a GUI of another device.

[00193] Prioritization data includes or refers to a prioritization of different categories of user data, including but not limited to scale-obtained physiological data, demographic data, lifestyle data (e.g., user habits include eating, drinking, smoking, sleeping, exercise, prescription medication, etc.), and diagnosis data. The categories of data can include data of different sensitivity and/or specificity levels. For example, the prioritization data can include numerical values (e.g., 1-10), binary indicators (e.g., include in social groups or not, or priority or not), and/or other ways to differentiate or group the different categories of the user data. In some specific aspects, the prioritization data can be specific to the correlation identified, and thus, a specific categories of user data may have different priorities for different uses. Particular user data may be relevant (e.g., be a risk, a symptom, a way to reduce a risk or symptom, a way to improve a goal or impact a goal) to a particular correlation. As a specific example, exercise habits and age can be relevant to arterial stiffness or declining arterial compliance as they can impact the risk for the health condition and/or improvements in the risk (e.g., lower risk). The user may adjust all or portions of the prioritization data. For example, the user may select different sensitivity or specificity values, which can impact the prioritization data and/or set the prioritization data. [00194] The normalization data includes or refers to a numerical value or other privacy value to different categories of data. For example, the normalization data can include numerical values to normalize particular user data to and/or normalization of privacy of different categories of user data.

[00195] In specific examples, user data that is provided to sets of users in a social group is normalized for privacy purposes and for sensitivity for the user. Specific users may not want their identity shown and/or may be sensitive to displaying values (such as weight or diagnosis) to different users. The user data maybe referred to as "user-sensitive data". To protect the user's privacy and ease their comfort in using social groups, the data that users are provided access to is normalized. The normalization values can include default values and/or can be adjusted based on user input. For example, the user can view how their data is displayed in the social group prior to providing other users with access and can further adjust the normalization. Particular user data can adjusted to a numerical scale (e.g., 1-10) and/or not all of the data is displayed (e.g., don't show that the user is diagnosed with a condition). In other aspects, the user data can be normalized in other ways and/or in combination. For example, instead of displaying a user's weight, the social group is provided access to a scaled version (e.g., 1-10 or 1-100) and a percentage change in the user's weight over a period of time. As another example, instead of displaying the specific diagnosis of the users (e.g., AFIB), the user is indicated as having an arrhythmia condition. The user can adjust the data displayed to the social group overtime, such as when the user becomes more comfortable with the social group. When the particular user accesses the user data in the social group, other user's data is normalized based on the particular user's selection and/or based on the other users' selections.

[00196] In various specific examples, the normalized user data can include numerical values to indicate a general value (e.g., high or low) for the user data. As a specific example, the normalized user data can include body fat (or body-mass-index (bmi)) on a range of 1- 100, with 1 being a low value and 100 being a high value, and a display of a percentage change in body fat in a period of time. Normalized user data includes or refers to user data, including scale-obtained physiological data and optionally other data (e.g., demographic or lifestyle data) that is normalized using the privacy data and normalization data. The range can, for instance, be based on average values for similar demographic users (e.g., high, medium, and low body fat values for a user of the same or demographic similar sex and age). As another example, normalized user data can include resting heartrate on a range of 1-10 or 1-100, and, optionally, include an indication of improvement in resting heartrate such as a percent change in a period of time. In other embodiments, the normalized user data can include actual weight values or weight on a range (e.g., a scaled ranged) (of 1-10 or 1-100) with no user identification and with a percent change in a period of time. In related embodiments, the normalized user data can include an amount of exercise or types of exercise in a period of time. The amount can be normalized within a range or scale of numerical values, such as 1-10 and 1-100, with one being no exercise and with 10 or 100 including a recommended (or above a recommended) amount of exercise. Further, the amount of exercise can include a number of exercise sessions in the period of time, the total time exercise, and/or an amount of time per exercise sessions. In other specific and related embodiments, the amount of exercise can include a number of steps per week that is scaled in a range (1-10 or 1-100) with the highest value (10 or 100) of the range including the user reaching above a goal. Other normalized user data can include a number of times the user stands on the scale and/or a number of times the user performs an exercise test using the scale (e.g., the scale instructs the user to exercises and identifies recovery parameters). The number of times can be presented as actual values (e.g., 10 times this week) or normalized (e.g., 1-10 or 1-100). The various user data can include weight-relevant parameters and can include various combinations as described through the present disclosure. Examples include BCG, ejection rate or indications thereof, variability in heart beats, and arrhythmia conditions or indicators.

[00197] As another specific example, loss of muscle mass and function, whether the cause is age-related sarcopenia or otherwise, can be assessed with weight changes and other user-specific physiologic indicators, including but not limited to PWV (pulse wave velocity) and body-fat and diet measurements/changes that are suggestive/indicative of abnormalities often associated with aging and/or related causes of physiologic declinations. In various embodiments, the scale identifies that the user has reached middle age and has one or more other factors for declining arterial compliance and/or muscle-loss issues. The scale, in response, provides the user with articles, journals, and access to a social group to motivate and psychologically influence the user to change particular lifestyle habits to mitigate or prevent such issues which would otherwise evince (e.g., arterial/muscle) compliance declines. The normalized user data for the social group can include body fat, weight, and/or PWV (as normalized on a scaled range of 1-10 or 1-100) and percent change over time. Further, the normalized user data can include identification of changes in diet and correlation with the change in body fat, weight, and/or PWV. The change in diet can be normalized to include general (and not specific detail) detail, such as changes or values of calorie, fat, and sugar intake.

[00198] In connection with the above-described embodiments and other embodiments described herein, the system incorporates communication circuitry that can vary. For example, the scale includes communication circuitry, external circuitry includes

communication circuitry and/or a user device includes communication circuitry. The external circuitry can include a server or standalone CPU with communication circuitry, among other circuitry. The user device can be a smart device having communication circuitry. A smart device is an electronic device, generally connected to other devices or networks via different wireless protocols such as Bluetooth, NFC, Wi-Fi, 3G, etc., that can operate to some extent interactively and autonomously. The smart device can include communication circuitry and GUI, such as keyboards and touchscreens which are controlled by circuitry typically programmed for the smart device. Examples include a tablet, a smartphone, a smartwatch, a laptop computer, etc.

[00199] In various embodiments, the scales act as hubs for user data and collects user data from a plurality of user devices and sources. The user devices include devices such as smartphones, smartwatches or fitness watches, exercise tracking devices, heart monitors and other medical devices (e.g., implanted and non-implanted medical devices), smart beds, among other devices. The data can include glucose measurements, blood pressure, ECG or other cardio-related data, body temperature, among other physiologic data. The user device includes processing circuitry and, optionally sensor circuitry, configured to collect data from the user. The correlations, in such embodiments, are based on data from user devices, data from the scale, and/or a combination thereof. The scale aggregates the data from the various devices and outputs the data in response to a scale-based biometric. The scale can incorporate a web server (URL) that allows secure, remote access to the collected data. For example, the secure access can be used to provide further analysis and/or services to the user.

[00200] In specific aspects, prior to communicating data between the scale and the user device, the scale can perform time synchronization. When using data from both the scale and another device, time-based (e.g., phase) inaccuracies between user data sets from the other device and the scale can impact assimilation and/or combined use of the two sets of user data. For example, lack of time synchrony can cause issues such as cardiac parameters from each device not coordinating, and/or being inaccurate, and/or not identifying the correct data to output. For example, a user exercises while wearing a user device (e.g., a wearable device) that monitors one or more physiological parameters, and the user device outputs the physiological parameters to a scale for further processing. The time (e.g., phase) used by the user device can cause a resulting physiological parameter (e.g., waveform) to be inaccurate. The scale and the user device (or other user devices) can be time-synchronized based on the frequency and/or timing (e.g., phase) of signals or waveforms. Time-synchronizing includes or refers to synchronizing two waveforms (e.g., signals from the scale and the user device) based on a frequency and a timing, sometimes referred to as "a phase angle". In specific embodiment, time-synchronized waveforms have the same frequency and same phase angle with each cycle and/or share repeating sequences of phase angles over consecutive cycles.

[00201] As a specific example of time synchronization, while the user is standing on the scale, the scale recognizes a nearby user device (e.g., within a threshold) and prompts the user to pair the remote user-physiologic device and scale. The user authorizes the pairing (e.g., selects an icon on the FUI or otherwise provides an indication of an interest) by providing an indication of interest to the scale (e.g., select an icon, provide a voice command, or perform an action). In specific embodiments, the user device and scale can be time-synchronized by tapping the user device, such as a wearable device, cellphone, and/or tablet to the scale. The scale synchronizes via strain gauges of the scale and accelerometer of the user device, as previously described. In other specific embodiments, the scale provides a command to the user device, which is placed on the scale and/or tapped on the scale, the scale detects the vibration frequency and timing (e.g., phase). This can be used to give secure identification and time synchronization, as previously described.

[00202] In a number of specific embodiments, the user activates a time-synchronization service/feature of the scale. For example, the user stands on the scale and identifies the user device, including how to synchronize the two devices, using a user interface (e.g., FUI of the scale, external GUI in communication, etc.) The scale authorizes the communication and/or the synchronization by recognizing the user using a scale-based biometric and based on authorization data from the user device, in some specific embodiments. In response to the synchronization, the scale outputs a message requesting a time value from the user device. The user device, in response to the message, outputs a response message with an indication of the time value. The response message can include the user device vibrating (at a respective frequency and timing). The scale detects the vibration at a frequency and timing, and can determine the vibration frequency and timing. The determined vibration frequency and timing can be used to time-synchronize the scale with the user device based on a time difference. A time difference between the scale and the user device can include a difference in relative time (e.g., phase) according to the scale and relative time (e.g., phase) according to the user device. The scale can time-synchronize by outputting a message to the user device to adjust its timing based on the time difference and/or to match the timing of the scale.

[00203] As previously described, the time-synchronization can occur responsive to a user dropping and/or tapping the user device on the scale. The user device may include a built-in accelerometer and the user dropping or tapping the user device on the platform of the scale (with or without standing on the scale) can activate the time-synchrony. In various embodiments, the time-synchrony is activated in response to the user device being within a threshold distance from the scale. In other embodiments, the user is standing on the scale and/or within a threshold distance, and the scale outputs a messaged to the user device to vibrate to trigger the time-synchronization, as previous discussed. Further, via NFC, Bluetooth, and/or wireless communication, the time-synchrony can occur through direct communication between the scale and the user device. In some specific embodiments, the time-synchrony occurs in response to verification that the user device (and/or the scale) has recognized the user within a threshold period of time. The verification can be used to mitigate or prevent accidental synchronization and can be used in combination with a user dropping or tapping the user device on the scale and/or the user device being within a threshold distance from the scale.

[00204] In other specific embodiments, the scale time-synchronizes with the user device by docking the user device with the scale and/or via acoustic sounds. For example, the user device may be a user device that includes a photoplethy configured to obtain a

photoplethysmogram. The photoplethy can be time-synchronized by docking (e.g., placing on the platform and/or connecting) the user device with the scale and using a light source of the scale to flash a pattern to calibrate the photoplethy (e.g., flashing LED lights via one or more LEDs embedded in the platform of the scale). Further, the user device can be acoustically calibrated by outputting sounds from the platform (e.g., "pips" and "chirps").

[00205] The scale can include a mechanical mass that can be triggered by the user device to calibrate the system. In response to a command from the user device, for example, a mechanical input is input to circuitry of the scale using the mechanical mass. The scale can pick apart the mechanical input separately from a cardiac parameter (e.g., BCG) and use the mechanical input to measure a phase latency of the system.

[00206] In accordance with a number of embodiments, the scale identifies one or more of the multiple users of the scale that have priority user data. The user data with a priority, as used herein, includes an importance of the user and/or the user data. In various

embodiments, the importance of the user is based on parameter values identified and/or user goals, such as the user is an athlete and/or is using the scale to assist in training for an event (e.g., marathon) or is using the scale for other user goals (e.g., a weight loss program).

Further, the importance of the user data is based on parameter values and/or user input data indicating a diagnosis of a condition or disease and/or a risk of the user having the condition or disease based on the scale-obtained data. In some embodiments, user(s) with cardio- related physiologic data with threshold priority have data sent to the external circuitry for various purposes, include forming social groups. In specific embodiments, the priority is based on prioritization data (as previously described).

[00207] For example, the scale-obtained data of a first user indicates that the user is overweight, recently had an increase in weight, and has a risk of having AFIB (e.g., potentially has a medical issues). The first user is identified as a user corresponding with priority user data. A second user of the scale has scale-obtained data indicating an increase in recovery parameters (e.g., time to return to baseline parameters) and the user inputs an indication that they are training for a marathon. The second user is also identified as a user corresponding with priority user data. The scale displays indications to the user with the priority user data, in some embodiments, on how to use the scale to communicate the user data to external circuitry for further processing, correlation, and/or other features, such as social network connections. Further, the scale, in response to the priority, displays various feedback to the user, such as user-targeted advertisements and/or suggestions. In some embodiments, only users with priority user data have data output to the external circuitry to determine correlations, such as risks, although embodiments in accordance with the present disclosure are not so limited.

[00208] In some embodiments, one or more users of the scale have multiple different scale-obtained biometrics used to authorize different communication modes. The different scale-obtained biometrics are used to authorize communication of different levels of user data, such as the different user-data types and sensitivity values as illustrated in the above- table. For example, in some specific embodiments, the different scale-obtained biometrics include a high security biometric, a medium security biometric, and a low security biometric, as discussed in further detail herein. Although the different communications are referred to as "modes", one of skill in the art may appreciate that the communication by the scale in the different modes may not (or may) include different media and channels. The different communication modes can include different devices communicated to and/or different data that is communicated based on sensitivity of the data and/or security of the devices.

[00209] In a specific example, a low security biometric includes estimated weight (e.g., a weight range), and a toe tap on the FUI. Example medium security biometrics includes one or more of the low security biometric in addition to length and/or width of the user's foot, and/or a time of day or location of the scale. For example, as illustrated by FIG. 6 and 18a- 18c, the scale includes impedance electrodes that are interleaved and engage the feet of the user. The interleaved electrodes assist in providing measurement results that are indicative of the foot length, foot width, foot shape, and type of arch. An example high security biometric can include a ECG-to-BCG timing relationship, foot shape, toe tapped password and/or toe print, alone or in various combinations. In some specific embodiments, a scale-based biometric includes a toe-print (e.g., similar to a finger print) that is recognized using a toe-print reader on the FUI of the scale. The toe print can be used as a secure identification of the user.

[00210] Further, a specific user, in some embodiments, may use the scale at a particular time of the day and/or authorize communication of data at the particular time of the day, which is used to verify identity of the user and authorize the communication. The location of scale, in some embodiments, is based on Global Positioning System (GPS) coordinates and/or a Wi-Fi code. For example, if the scale is moved to a new house, the Wi-Fi code used to communicate data externally from the scale changes. Example high security biometrics include one or more low security biometrics and/or medium security biometrics in addition to cardiogram characteristics and, optionally, a time of day and/or heart rate. Example cardiogram characteristics include a QRS complex, and QRS complex and P/T wave, weight, BCG characteristics, and other cardio-related data.

[00211] The social grouping, in specific embodiments, is provided as a hierarchy of service. A service, as used herein, includes a function and/or action performed using the platform system and uses and/or is in response to scale-obtained data. A hierarchy of services include different services enabled in response to user selection and activation of subscription levels. The subscription levels have different weighted values that activate the subscription level. Further, each subscription level is associated with one or more services. For example, the scale-obtained data from the particular scale drives a physiological related prompt for a service.

[00212] The weighted values of the subscription levels, in some embodiments, is based on the value of the service or corresponding data to the user, the user-sensitivity and/or regulation of the corresponding data, the value of the corresponding data to the service provider/provider of the scales, value of the corresponding data to the requester. In various embodiments, the value of the service and/or corresponding data is determined based on a level of security of the data, a level of technical detail of the data, and/or a likelihood of diagnosing the user based on the data. The requester of the data provided by the service, in various embodiments, includes a third party, such as a researcher, physician, government entity, and/or other entity. The different subscription levels have different weighted values that, in some embodiments, increase with the levels of subscription.

[00213] In a number of specific embodiments, social groupings are provided as services in a plurality of different subscription levels. For example, in a first subscription level, a user is provided access to a social group based on exercise interest and/or goals or other consumer related interest. At a second subscription level, a user is provided access to physiological social group, which is based on scale-obtained data and/or diagnosis of the scale-obtained data by a physician. At a third subscription level, a user is provided access to the (more) professional social group. For example, a physician participates in the professional social group with other users and/or actively tracks progress of the user.

Alternatively and/or in addition, the physician uses the professional social group to perform a study and/or experiment.

[00214] In some embodiments, the social groups are intra scale and/or intra scale. The social grouping of an intra scale includes grouping the users of the scale and providing various reports, updates, alerts, and/or forums for the users of the group to interact. The forum, in some embodiments, includes a private (or public) page of a social network webpage that the users of the group access and communicate. A private page, for instance, is only accessible by the users of the group and/or persons authorized by users of the group. In other embodiments, the social groupings are inter scale. For example, an external circuitry, such as a server CPU, may receive user data (with user identifying data removed) from a plurality of scales and identifies various users with correlated user data. The users with correlated user data, such as demographic data and/or scale-obtained data, are grouped by the external circuitry without user input. The external circuitry outputs an indication of an available social group to the scales of the users with the correlated user data and each scale displays, using the FUI, an alert of an available social group. The user accesses the social grouping using the FUI and/or a standalone CPU that is in communication with the scale. For example, in response to an alert, the user selects an interest in the social grouping using the FUI. The scale outputs the indication and a link to a webpage or application associated with the social group (or information on how to access the social grouping) the standalone CPU, such as a user's smartphone or tablet. The webpage includes, in some embodiments, a page of a social network, an application or portal for the user to log-in to, a forum, etc. In various embodiments, data is tracked for users of the social group and reports are provided, such as rankings of the users in the group, progress of the users, new observations, and/or information learned. Alternatively and/or in addition, the users of the group are provided a forum to discuss various health issues, successes, failures, exercise, eating, etc.

[00215] As a specific example, a scale is used by a family training for a marathon. Each member of the family uses the scale to track various physiological parameters, including cardiogram related characteristics, recovery parameters, weight, body-mass-index, and exercise results. The family is grouped into an intra scale social grouping and provided with alerts when reports of progress and/or rankings are available for the family. In another specific example, multiple scales are used by different users located at different locations that have indicators for atrial fibrillation, are female, are over-weight, and are over the age of sixty -years old. The users are grouped into an inter scale social grouping and provided with an alert of an available social grouping. In response to at least a subset of the users selecting an interest in the social grouping, the subset of users are provided with a link to a webpage, portal, application, and/or forum. The subset of users access the link and are connected one another. In various embodiments, user data (with user identifying data removed) is displayed to the social group so that users can view other users' success and/or failures.

[00216] The user-specific knowledge database 139 includes pooled user data from a plurality of scales that is updated over time. Thereby, data from the scales, in some embodiments, is used to identify trends, risks, and/or parameter values associated with and/or indicative of particular conditions. In response to the update, the social groups are revised. For example, a user may have previously had access to a first social group and later does not as the correlation is removed. Further, inputs to the forums, blogs, and/or webpages are used to update the user-specific knowledge database 139.

[00217] In various embodiments, the external circuitry receives the user data and identifies a risk that the user has a condition using the reference information and the user data provided by the scale. The risk is identified by comparing the user data to the reference information (and/or the user-specific knowledge database 139) and identifying a match. The risk of a condition, as previously discussed, includes a probability that the user has the condition and a severity of the condition. Further, the risk is used to correlate the user with other users to form social groups.

[00218] In response to identifying the risk, the external circuitry derives and/or identifies and outputs generic health information correlating to the condition to the scale. The generic health information is tailored to the user based on the identified risk. As previously discussed, the generic health information includes information on risk factors for the condition, symptoms of the condition, and suggestions. The generic health information does not indicate that the user has the condition or the risk of the condition identified, in a number of embodiments.

[00219] In various embodiments, the scale and/or other user devices is used as feedback in response to the identified risk. For example, the external circuitry, in response to the identified risk, determines questions to ask the user and/or additional tests to perform and outputs the number of questions to the scale to ask the user and/or the additional tests to perform and based on the filter of the physiological data and/or the Internet. The questions can include asking if the user has a diagnosis from a doctor, asking if the user is

experiencing particular symptoms, and asking the user for family medical information. The scale, using the processing circuitry and the user display, provides the number of questions to the user (including asking if the user has a symptom occurring). The scale, using the processing circuitry and the output circuit, outputs the response to the questions to the external circuitry and the external circuitry verifies and/or adjusts the risk using the responses to the questions. For example, in various embodiments, a user may not realize they are experiencing a symptom (e.g., heart rate is raised and/or difficulty breathing). The questions ask the user about potential symptoms of the condition identified (e.g., associated with the risk) and is used to revise the risk determined. In specific embodiments, the scale uses voice input/output circuitry (or alternatively a GUI or FUI) to provide questions to the user and/or to obtain answers to the questions, as previously described. The user is provided with generic health information about the condition that may include the various symptoms to assist the user in recognizing the symptoms and discussing the same with their physician.

[00220] In a number of embodiments, the scale asks the user about diagnosis from a doctor. For example, the user may have been diagnosed with heart failure and the user can input this knowledge to the scale. The scale outputs the response to the external circuitry and the external circuitry identifies misdiagnosis information associated with the condition. For example, in some instances, when a user is diagnosed with condition Y, they actually have condition X. The external circuitry determines and outputs generic misdiagnosis information to the scale.

[00221] In other related embodiments, the external circuitry (and/or assessment circuitry, as previously described), in response to the identified risk, determines additional tests or measurements to be performed. In various embodiments, the scale is used to perform the additional test and/or other circuitry is used. For example, the external circuitry determines and outputs a test, to the scale, for the scale to perform. The scale, including the data- procurement circuitry, performs the test and outputs results to the external circuitry. Using the results, the external circuitry verifies and/or adjusts the risk. Furthermore, the user data and/or results from the test are used to update the user-specific knowledge database 139.

[00222] Although the present example embodiments provided above are in reference to external circuitry performing the determination, embodiments in accordance with the present disclosure are not so limited. For example, the processing circuitry 104 can determine the risk by accessing the reference information 111 or the feedback information while the user is standing on the platform 101.

[00223] FIG. lh shows an example process for pooling scale-data, consistent with various aspects of the present disclosure. An apparatus for pooling the scale-data can includes one or more scales 128, external circuitry 112 and user-specific knowledge database 139. In various embodiments, the apparatus optionally include reference information. The scale collects user data that is indicative of cardio-related measurements and outputs the user data to external circuitry. The external circuitry includes the reference information and/or the user-specific knowledge database 139 and/or is in communication with the same. The one or more scales secure the user data for communication by removing data that identifies the user from the user data, adding an identifier that is indicative of the identity of the scale and the user to the user data, and optionally encrypting portions of the user data, such as the identifier. The external circuitry or scale, in various embodiments, replaces the identifier with an alias ID that is independent of the identifier, stores the user data in the user-specific knowledge database 139 (e.g., a first database) and stores identification of which scale corresponds to the respective alias ID in another database 182 (e.g., a second database).

[00224] In such embodiments, the external circuitry 112 pools user data from a plurality of scales in a user-specific knowledge database 139. As previously discussed, the user data includes data that is sensitive to the user and/or that the user would otherwise not want compromised (e.g., user-sensitive data). To prevent the user-sensitive data from being compromised and/or the identity of the user being learned, the processing circuitry of the scale removes portions of the user data that identifies the user and adds an identifier that is indicative of the scale and the user to user-sensitive data corresponding to each respective user. The remove portions, in some embodiments, includes a user ID, user name, date of birth, location, and a combination thereof. The identifier, in various embodiments, includes a scale ID and a user ID. Alternatively, the identifier includes an alias ID, as discussed further herein. For example, the scale ID remains the same for each user of the scale and identifies the scale. The user ID, by contrasts, is different for each user of the scale and identifies the respective user profile corresponding to the scale. The identifiers (scale ID or user ID), in some embodiments, includes numeric and/or alphabetic assignment and/or is based on identifying data, such as an Internet Protocol (IP) address of the scale and/or a social security (or part thereof) number of the user. In other embodiments, the external circuitry receives the user-sensitive data and, in response, replaces the identifier with an alias ID. For example, the external circuitry creates an alias ID corresponding to each identifier and, for certain types of access requests, provides the alias ID in place of the identifier.

[00225] The external circuitry stores the user data with the alias ID in the user-specific knowledge database 139 and stores identification of the scale and user that correspond to the alias ID in another database. For security purposes, the alias ID is encrypted and access to the encrypted alias ID can be restricted. The scale and/or the external circuitry, in various embodiments, encrypt the identifier and/or the alias ID. In various embodiments, the user- sensitive data is sent over time. Thereby, the first database includes historical data for the user. The alias ID, in some embodiments, is associated with a generic user profile such that user-sensitive data with the alias ID is associated with the same generic user profile over time. As may be appreciated by one of ordinary skill, user data and user-sensitive data may be used interchangeably throughout the present disclosure.

[00226] An alias ID, as used herein, is data that is independent of the identifier (e.g., not invertible back to the identifier). In some embodiments, the alias ID is formatted as the identifier is. That is, the alias ID is used in place of the identifier that identifies the user and the scale and that appears in the same format. Further, the alias ID includes a substitute value for the identifier that has no algorithmic relationship with the identifier and is not reversible. The alias ID is provided in place of the identifier for certain types of access requests. The alias ID can be used in place of the identifier for accessing the user data unless the user data is requested by an authorized user (such as, the user corresponding to the user data and/or a physician for a fee). The system stores the user data in the user-specific knowledge database 139 with the alias IDs, and stores an association of each alias ID to a scale and user in another database. The system may maintain the association between the alias ID and the user data, regardless of the form of the user data. The association can remain the same whether the user data is decrypted, formatted, encrypted or the re-encrypted using a different encryption scheme.

[00227] An output of the system provides the alias ID in place of the identifier for accesses to the user data unless the user data is specifically requested by an authorized user. The alias IDs are independent of the user data in that the identifier that indicates

identification of the user and the scale cannot be derived directly from the alias IDs. This independence can be implemented using a variety of alias ID creation techniques such as a randomly generated identifier, a sequentially generated identifier, or a non-invertible derivation of the transaction card identifier. The aliases may also be uniquely associated with exactly one scale and one user. In some instances, the user, administrator, or another application using the invention may configure the format of the alias IDs. For example, the user may designate that the alias IDs should be formatted to each contain six capital letters or to each contain nine digits (the numbers "6" and "9" being merely illustrative). In another embodiment, the user may designate a portion of the identifier that is retained and used as a portion of the alias ID. In one such example, the system uses the first number of an identifier as the first number of its corresponding alias.

[00228] For example, the alias ID can be generated as a hash value. In some

embodiments, the external circuitry 112 generates a hash value for each identifier or encrypted identifier. The external circuitry 112 uses this hash value for searching, sorting, and similar database-related processes. For instance, the hash value may represent alphanumeric, numeric, or other limited values. The hash value may also represent a compression of the identifier. Additionally, the external circuitry may format the hash value further by using another hash algorithm, such as first using Secure Hash Algorithm (SHA-1) and then using Media Digest Algorithm (MD5). Once the hash value has been created, a database application may use the hash when accessing the database. For example, to search for identification of a user of user data in the second database, the system determines the identifier hash value for use in finding records that correspond to the hash value. This method can be particularly beneficial when large amounts of user data are accessed during initialization or bulk modification of the database and also can increase the security of the database-related processes. This hash creation method is useful to numerous applications, including applications outside of data aliasing. [00229] In various embodiments, the identifier and/or portions of the user data are encrypted. The scale and/or the external circuitry 112 encrypt the data using a suitable encryption scheme. Examples of encryption schemes that can be used include, but are not limited to, AES, Data Encryption Standard (DES), and International Data Encryption Algorithm (IDEA). The system formats the resulting encrypted data so that the data conforms to a desired database format. For example, many encryption schemes generate a binary string that can be difficult to read, remember, and store. In one embodiment, the binary string is converted to a readable form using uuencode, base64, or similar conversion methods. For example, in some embodiments, the scale encrypts the identifier and/or the user data. Further, if the user data is not encrypted by the scale, the external circuitry encrypts the data, (e.g., a secret) and, optionally, serves as ab encryption key for decrypting the indication and/or user data.

[00230] The encryption scheme can include an asymmetric or symmetric key and the user data and/or the identifier is encrypted using an asymmetric or symmetric key cryptography. For example, the scale may not allow the ability to add additional applications or software to the circuitry (or the user may choose not to) and, thus, is more secure than if additional applications or software were added. In such embodiments, a symmetric key is used.

[00231] In various embodiments, a symmetric key is used by each scale using symmetric encryption. The key is randomly assigned by the scale instead of derived using a single key. A table of identifiers to keys is stored at the external circuitry (e.g., the second database). With symmetric encryption, the key and/or other data is encrypted by changing the data in a particular way. For example, the data is encrypted by shifted each letter or number by a number of places. Both the scale and the external circuitry know the symmetric key used to decode the data. Thereby, the symmetric key is a shared secret (e.g., piece of data known to the scale and to the external circuitry). The shared secret is known by the external circuitry before or at the start of the communication session.

[00232] Alternatively, an asymmetric key is used, which is sometimes referred to as a public key. With asymmetric key cryptography, there are two keys: a private key and a public key. The scale contains the only instance of the private key, which is kept secret, and the public key is provided to the external circuitry. Any message encrypted using the private key is decrypted using the matching public key and any message encrypted using the public key is decrypted by using the private key. The external circuitry contains a list of identifiers to public key mappings. The proof-of-identity supplied by the scale in the exchange is its identifier, as well as information to show authenticity and freshness of the message encrypted with its private key. To verify the user data, the external system looks up the public key and identifies that only the private key on the scale would create a message matching the known public key.

[00233] In various embodiments, to increase security, the external circuitry stores user data only in response to a hardware security key in the user data. For example, the scale includes a hardware token and the external circuitry verifies authorization of the user data based on the hardware security key generated using the hardware token.

[00234] The external circuitry can change the alias IDs periodically, in response to an event, and/or in response to access of the user data. For example, each time the scale communicates user data to the external circuitry, the alias ID is changed and the external circuitry associates previously received user data with subsequent user data. The user- specific knowledge database 139 and the other database containing the alias IDs are updated with the changed alias IDs.

[00235] The other database can be used to identify the scale and user. For example, the external circuitry uses the other database to identify the scale and user corresponding to the alias ID. The identification, in some instances, is to provide a notification and/or additional data to the user through the scale. For example, in various embodiments, the user-specific knowledge database 139 is used to identify correlated user data and identify various pattems of risks or conditions or diseases based on the correlation. The user, in some embodiments, is notified of a potential correlation. The notification is displayed on the user display of the scale and/or another user device. In some embodiments, the external circuitry outputs the correlations that includes user data with alias IDs. For example, output data may not identify that the user has such a problem or correlation but rather generic correlations of user data with alias IDs. The output data, optional, identifies pattems of risk for conditions or diseases based on the correlation (without actually identifying the user has the condition or disease but indicating correlation). Further, based on the correlation, the user can receive an advertisement, such as an advertisement for a physician, prescription drug, health program, and/or social network group, as discussed further herein.

[00236] Although the present embodiments disclose the external circuitry replacing the identifier with an alias ID, embodiments are not so limited. For example, the scale, in some embodiments, removes the identifying information and adds an alias ID. In such embodiments, the external circuitry pools the user data with the alias IDs in the first database and may not include a second database. That is, the external circuitry may not have the knowledge of the identification of the scale and user that correspond with the user data. Rather, the external circuitry only correlates the user data with specific generic user (non- identifiable) using the alias ID. Alternatively, the scale may separately send the correlation of the alias ID with the scale and the user to the external circuitry for storage in the second user database.

[00237] Certain embodiments involve use of the scale for user data that is highly sensitive with user data that is less sensitive (e.g., user body weight, birthdate, body-mass indications). The scale includes a default mode (and/or user-configured setting based on inputs from the scale internal or off-scale GUI) in which the less-sensitive user data is not encrypted and a user-data secure mode in which the highly-sensitive user data is encrypted (or encoded such as being provided with the alias ID). For example, the external circuitry 112 determines whether the data received is encrypted using an acceptable method. Using one such method, the external circuitry 1 12 compares the format of the data received with the encrypted form of the user data and the unencrypted form of the user data (e.g., the length or content of the received data). According to another method, the external circuitry 112 receives an indication of the data format along with the data, such as a data bit or byte that indicates the format of the user data. Various other methods may also be used, such as determining the source of the data.

[00238] When the identifier of the user and the scale is encrypted, the external circuitry 112 decrypts the data in order to identify if previous user data corresponding to the user has been received. A decryption algorithm may be implemented using several methods. Several encryption schemes use a key to both encrypt and decrypt data. A key can be retrieved (such as from the other database 182) for each piece of encrypted data and/or otherwise received from the scale and/or another source. The control of the key through another source, permits the user or another application to maintain flexibility in how the data is encrypted if, for example, the user or application determines that the key should be changed for security or other reasons. While control of the key provides flexibility, it also introduces the possibility of user error. For example, if the user provides the wrong key, the decryption output would be unusable. This is particularly troublesome when performing operations on large amounts of data, such as when the encryption key is changed by the user. The key entered by the user can be verified to match the key that was used to encrypt the data. This may be accomplished by a number of different methods, such as storing an encrypted version of the key or a hash value of the key and comparing the stored version of the key to the encrypted version or hash value of the subsequently entered key. [00239] Further, in various embodiments, the external circuitry 112 encrypts the data when stored in the first and/or second database (e.g., databases 139 and 182). The encryption, in some embodiments, includes an independent encryption from any scale-based encryption (e.g., uses a different key /key combination and/or scheme).

[00240] In accordance with various embodiments, a user interface (such as the user interface of the scale and/or a user interface of the external circuitry 112) sends an enable signal to circuitry corresponding to a physician and/or a third party. The enable signal includes a decryption key or other decode key. Using the decryption key or other decode key, the circuitry corresponding to the physician and/or third party decodes the user data obtained by the scale and provides the data for user-specific diagnosis purposes, studies, and/or other research. In a number of embodiments, using the key and/or a subscription system, the user is reimbursed by the physician and/or third party for access and/or use of the user data. For example, in some embodiments, the user is provided a weighted value for access to their user data by the physician to perform a study and to use to educate other patients. In some embodiments, circuitry of a physician is provided with the respective key to access the user data, while circuitry of a third party is provided with a key that provides identification of where/how to provide the weighted value (e.g., Apple Pay™) and/or portions of the user data without user identification information.

[00241] As previously discussed, in some embodiments, the external circuitry 112 generates alias IDs for association with user data. Typically, the alias ID is randomly generated, but it also can be generated by other means, such as a sequential generation or by generating a hash value of the user data. The system then stores the alias ID and user data, which is optionally encrypted, in a user-specific knowledge database 139 and stores the correlation of the alias ID with the scale and the user in another database 182. In an example embodiment, the user of the external circuitry 1112 determines the format of the alias IDs. In another embodiment, the alias IDs have the same format as the original identifier. For example, if the identifiers are sixteen digits long, the alias ID is also sixteen digit identifiers.

[00242] After the encrypted data and the alias identifier are generated, the external circuitry 112 provides access to the user data with alias ID, in various embodiments. The access, in some embodiments, includes the external circuitry 112 providing portions of the data to other circuitry for analytic purposes and/or to a particular scale. Typically, when user data is requested, the external circuitry 112 provides the user data with the alias IDs instead of the identifiers. In this manner, user data can be used without supplying the original identification of users/scales that correspond to the user data. [00243] The external circuitry 112 (and/or the scales 128), in various embodiments, periodically changes one or more alias IDs and updates the other database 182. For example, the external circuitry 112 assigns a new alias ID to user data corresponding to a specific user each time the scale sends user data to the external circuitry 112. Thereby, if previous data is compromised, such as by a security hacker, subsequent user data is more difficult to correlate to the previously compromised data than if the alias IDs remained the same. The external circuitry 112 identifies that the subsequent user data is correlated with a generic user and previously provided user data based on a correlation of the old alias ID with the new alias ID. For example, the user-specific knowledge database 139 as previously discussed, includes generic user profiles corresponding with the alias IDs. The alias IDs of the generic user profiles, in some embodiments, are updated in response to the changes in alias IDs. Alternatively, the correlation between the old alias ID and changed alias ID is stored in the other database 182 and used to identify correlations of subsequent user data with historical user data.

[00244] For example, the external circuitry 112 updates the user-specific knowledge database 139 to include the subsequent user data. The user-specific knowledge database 139 may include a plurality of user data that is organized into a plurality of generic user profiles, such that data corresponding to the same user is stored in a single generic user profile. That is, the external circuitry 112 updates the user-specific knowledge database 139 with additional user data received over time and, optionally, revised various correlations, as discussed further herein.

[00245] In various embodiments, the external circuitry 112 (and/or assessment circuitry integrated therewith) identifies various correlations between the user data stored in the user- specific knowledge database 139 and associated with different users. For example, the external circuitry 112 identifies other users that have correlated user data and identify patterns of risks for conditions or diseases based on the correlation. Identifying correlated user data, for instance, includes grouping respective sets of user data into groups based on various criteria.

[00246] The external circuitry 112 can include and/or be in communication with a database storing reference information. The reference information can be stored in a structured database and/or in an unstructured database. In some embodiments, the user- specific knowledge database 139 is a portion of the reference information.

[00247] In various embodiments, the correlations are used to provide generic health information to the user. For example, the external circuitry 112 identifies which scale a particular user data set corresponds to that has an identified correlation or risk using the other database 182. The external circuitry 112, in various embodiments, identifies generic health information to provide the user and outputs the generic health information to the scale. The generic health information is displayed to the user, such as using the scale display or another user device depending on user preferences. For example, in response to identifying the user is standing on the scale using a scale-based biometric, the scale displays an indication that generic health information is available to the user and/or a synopsis of the generic health information and to log-in to their smartphone or other user device to view the generic health information.

[00248] The external circuitry 112 can revise correlations identified using the pooled user data in the user-specific knowledge database 139 over time. For example, over time, the scale obtains additional data from the existing users and the additional users. The external circuitry 112 dynamically revises and updates correlations of the user-specific knowledge database 139 based on the additional user data received from the plurality scales and additional scales added to the system. As a specific example, the external circuitry 112 receives the user data and identifies a risk that the user has a condition using the user- specific knowledge database 139 and/or reference information and the user data provided by the scale. The risk is identified by comparing the user data to the reference information and pooled user data and identifying a match. In some embodiments, the external circuitry 112 and/or the scale updates the database 139 with the user data, the test results, and the responses to the questions. For example, the responses to the questions may identify a diagnosis the user has from a doctor and/or additional symptoms the user is experiencing.

[00249] For example, the scale can provide a number of questions to the user in response to input from the external circuitry 112. The questions can be provided via a speaker component of the scale outputting computer generated natural voice (via a natural language interface), displaying the questions on the user display, and/or outputting the questions to another user-device. The scale provides the input to the external circuitry 112 and the external circuitry 112 verifies or revises the risk identified and updates the user-specific knowledge database 139. For example, as previously described, the scale uses voice input/output circuitry to provide questions to the user and/or to obtain answers to the questions.

[00250] FIG. li shows an example process for securely pooling scale data, consistent with various aspects of the present disclosure. The scales and external circuitry shows an example of scale-based user-physiological heuristic system comprised of a plurality of scales and external circuitry consistent with aspects of the present disclosure. As illustrated, the system includes a plurality of scales 128-1, 128-2... 128-P (herein generally referred to as "the scales 128") and external circuitry 1 12. Each scale can include the scale, including the platform and user display, as previously illustrated and discussed with regard to FIG. l a.

[00251] As previously discussed, the scales 128 communicate secure user data by removing portions of the user data that identifies the respective users and adding an identifier that identifies the user and the scale. The identifier and/or the user data is optionally encrypted by the scale prior to outputting the data. In various embodiments, the external circuitry 1 12 includes computer-readable instructions executed to perform the various functions. For example, as illustrated by FIG. li, the external circuitry 112 includes data storing logic 141 to securely store the user data, correlation logic 197 to identify correlations between user data sets, and access control logic 143 to control access and output of user data, as described further herein. The external circuitry 112 receiving the user data and, using the data storing logic 141 , replaces the identifier with an alias ID, stores the user data with the alias ID in a user-specific knowledge databases 139 and identification of which scale and user corresponds to the respective alias ID in another database 182.

[00252] In various embodiments, the system is used to securely communicate and store pooled user data such that the identities of the users are not compromised and correlations between user data sets are identified. The scales 128, for example, correspond to the plurality of users. Each scale is configured to collect data for one or more users and verifies identity of the user based on scale-obtained biometrics. For example, each scale, at block 114, waits for a user to stand on the platform of the respective scale. User-corresponding data 103 is input and/or received prior to the user standing on the respective scale and/or in response to. In response to the user standing on the respective scale, the respective scale collects signals indicative of an identity of the user and cardio-physiological measurements. The processing circuitry, at block 117, processes the signals and, in response, verifies identity of the user based on a scale-based biometric and derives user data. The processing circuitry further removes user data that identifies the user, such as date of birth, location data, user name, physical address, physician name, and adds an identifier that identifies the scale and the user. The identifier, for example, is used to output data to the scale (such as an IP address) and the scale can identify the specific user using the identifier. For example, the identifier includes an IP address of the scale or is indicative of the IP address of the scale and a generic identifier for the user (such as, user A or user 1) that the scale uses to identify the user. In some embodiments, the scale stores the generic identifier in the user profile correlated with the user.

[00253] As illustrated, the external circuitry 1 12 securely store the user data. As previously described, the secure storage, in various embodiments, includes replacing the identifier with an alias ID, storing the user data with the alias ID in a user-specific knowledge database 139, and storing identification of which scale and user corresponds to the respective alias ID in another database 182, at block 145. Based on the alias ID, at block 147, the external circuitry 112 correlates the user data with a generic user profile. The generic user profile is a profile associated with the alias ID and can include user data previously received, in some embodiments.

[00254] The external circuitry 112 can identify correlations between the user data in the generic user profiles. For example, at block 151 , the external circuitry 1 12 identifies various correlations between the user data stored in the user-specific knowledge database 139 and associated with different users.

[00255] In a number of optional embodiments, the external circuitry 112 outputs generic health information to the scales and/or stores the generic health information in the generic health profile for the scale to later access. For example, the generic health information is identified based on the user data matching a correlation identified from the user-specific knowledge database 139.

[00256] Optionally, at block 153, the external circuitry 112 (and/or assessment circuitry) controls access to data in the generic user profiles. The control of access includes allowing the scale to access generic health information and/or other user data with alias IDs in response to verification of identification of the scale and the user using a scale-based biometric. The user data can be provided for analytics and/or for educational purposes to users of the scales, for research, and/or for other purposes as the user data does not identify the specific users and/or the scales. For example, in some embodiments, the external circuitry 112 may output the data to the scale and the scale, via integrated assessment circuitry, controls the access to the data.

[00257] FIG. lj shows an example process for providing scale-based social grouping, consistent with various aspects of the present disclosure. A scale-based user-physiologic heuristic social grouping system can be used to provide the social groupings. The scale- based user-physiologic heuristic social grouping system includes a plurality of scales 128 and external circuitry 1 12. Each scale is configured to monitor signals from a plurality of users, correlate the respective data with the appropriate user using scale-based biometrics, and communicate the signals and/or data to the external circuitry.

[00258] The external circuitry 112 receives the user data from the scale and stores the user data with an alias ID replacing identifying information in the user-specific knowledge database 139, as previously described. The user data is collected and stored by the external circuitry 112 over time. For example, the external circuitry 112 validates the received user data as corresponding to a particular user associated with an alias ID based on the identifier and correlates the received user data with other user data stored in the user-specific knowledge database 139 and associated with the alias ID. The external circuitry 112 then updates the user-specific knowledge database 139 with the user data and/or other feedback data obtained. In response to not identifying the identifier (in the second database), the external circuitry 112 generates a new alias ID for the respective scale and user. Further, the external circuitry 112 stores an indication of which scale and user corresponds to the alias ID in another database 182. Alternatively and/or in addition, the scale outputs user data with an alias ID. In some embodiments, the scale outputs the correlation of the alias ID with a respective scale and user to the external circuitry 112.

[00259] After the encrypted data and the alias identifier are generated, the external circuitry 112 provides access to the user data with alias ID, in various embodiments. The access, in some embodiments, includes the external circuitry 112 grouping the users into social groups based on identified correlations between user data sets and providing portions of the user data to the social group, such as a report and/or dashboard, as previously discussed. The social group can be accessed using the Internet (e.g., the social network 183), such as a webpage that contains a blog, forum, and/or social network page and/or an application that is accessed. The external circuitry 112 provides the user data with the alias IDs instead of the identifiers. In this manner, user data can be used without supplying the original identification of users/scales that correspond to the user data. Further, the users of the social group are anonymous and are identified by the alias IDs.

[00260] As previously discussed, the external circuitry 112 can identify various correlations between the user data stored in the user-specific knowledge database 139 and associated with different users. The correlation can includes patterns and/or trends, risks, and/or parameter values and/or various demographic information and user goals. In various specific embodiments, the patterns and/or trends, risks, and/or parameter values are associated with and/or indicative of particular conditions. For example, the external circuitry 112 identifies other users that have correlated user data and identified patterns of risks for conditions or diseases based on the correlation.

[00261] In various embodiments, the risks identified are used to provide generic health information to the user. For example, the external circuitry 112 identifies the scale and user that the particular user data is associated with and outputs data, such as the generic health information, to the identified scale. The external circuitry 112 identifies which scale a particular user data set corresponds to that has an identified correlation or risk using the other database 182. The identification can includes identification of the scale, and, optionally, a specific user. The external circuitry 112 can identify generic health information to provide the user and outputs the generic health information to the scale. The generic health information is displayed to the user, such as using the scale display or another user device depending on user preferences.

[00262] The external circuitry 112 can revise correlations identified using the pooled user data in the user-specific knowledge database 139 over time. For example, over time, the scale obtains additional data from the existing users and the additional users. The external circuitry 112 dynamically revises and updates correlations of the user-specific knowledge database 139 based on the additional user data received from the plurality scales and additional scales added to the system. For example, the external circuitry 112 receives the user data and identifies a risk that the user has a condition using the user-specific knowledge database 139 and/or reference information and the user data provided by the scale. The risk is identified by comparing the user data to the reference information and pooled user data and identifying a match. The risk of a condition, as previously discussed, includes a probability that the user has the condition and a severity of the condition. As specific examples, the external circuitry 112 and/or the scale updates the user-specific knowledge database 139 with the user data, the test results, and the responses to questions provided to the user. Additionally and/or alternatively, a user enters various information into the blog, forum, and/or webpage, which is used to update the user-specific knowledge database 139. For example, a user may indicate they are trying a new prescription medication and they are seeing increased results in physiological parameters. The external circuitry verifies this, by viewing the user's scale-obtained data. This information is used to dynamically update the user-specific knowledge database 139 and potentially revises (e.g., increase or decreases) risks identified by the external circuitry 112.

[00263] In accordance with the present disclosure, a risk for a condition is identified and/or adjusted based on demographics of the users, disorders, disease, symptoms, prescription or non-prescription drugs, treatments, past medical history, family medical history, genetics, life style (e.g., exercise habits, eating habits, work environment), among other categories and combinations thereof, and based on user data in the stored user database. The risk is provided to a scale, for example, in response to a request. In a number of embodiments, various physiological factors are an indicator for a disease and/or disorder. For example, an increase in weight, along with other factors, can indicate an increased risk of atrial fibrillation. Further, atrial fibrillation is more common in men. In some instances, symptoms of a particular disorder can be different for different categories of interest (e.g., symptoms of atrial fibrillation can be different between men and women). For example, in women, systolic blood pressure is associated with atrial fibrillation. In other instances, sleep apnea may be assessed via an ECG and is correlated to weight of the user. Furthermore, various cardiac conditions can be assessed using an ECG. For example, atrial fibrillation can be characterized and/or identified in response to a user having no p-waves, no QRS complex, and no baseline/inconsistent beat fluctuations.

[00264] As a specific example, the external circuitry 112 receives the user data that corresponds to the plurality users from the plurality of scales 128. The respective user data is received at over-lapping times and/or separate times. In response to receiving the user data, the external circuitry 112 identifies the respective plurality of users based on an identifier and/or other identifying data and, correlates the received user data with generic profiles of the respective plurality of users based an already generated alias ID and/or a newly generated alias ID. In a number of embodiments, the extemal circuitry 112 identifies (e.g., determines) risks for conditions or diseases by comparing the user data with reference information. The extemal circuitry 1 12 identifies that a particular user is at risk for the condition or disease, identifies the respective user and scale using the second database, and outputs the generic health information to the scale that is tailored to each respective user based on the risk for the condition (such as, by using assessment circuitry). The extemal circuitry 1 12 further instructs the scale to collect feedback data, including symptoms experiences, demographic information, medical history information etc., and uses the feedback data to revise and/or verify the risk. In some embodiments, the feedback data and the user data is used to update a user-specific knowledge database 139, which is used to refine the identified risks.

[00265] Such generic health information includes life-style suggestions, suggested prescription medicine and/or why it is prescribed, and/or other advice, such as symptoms that the user should watch for. For instance, the user data may suggest that the user has a heart condition and/or disorder. The generic health information suggests prescription medicine to the user to ask their physician about and/or provides potential symptoms that the user should watch for and/or should go to the physician's office or an emergency room if the symptoms arise.

[00266] FIG. Ik shows an example apparatus for providing a variety of services using pooled scale data, consistent with various aspects of the present disclosure. Specifically, FIG. Ik shows an example of a user-specific scale based enterprise system consistent with aspects of the present disclosure. As illustrated, user-specific scale based enterprise system includes at least one scale 189, the Internet (e.g., world-wide-web) 149, a standalone user CPU 185, and one or more user devices, such as a smartwatch 187, fitness tracking device, smartphone 186, smart bed, among other devices.

[00267] As previously discussed, the scale 189 collects user data that is highly sensitive, such as cardiogram data and data indicative of disorders and disease, and other user data, such as demographic information and weight. The scale 189 displays data, such as user weight, prompts or notification, and other information using a user interface 191, such as a FUI. The one or more user devices include devices that collect various user data, such as exercise data, food intake or liquid intake data, sleep data, cardiogram data, among other information. The standalone user CPU 185 includes a user device that include additional processing resources and/or a user display that is easier for the user to view data than the scale or other user devices. Thereby, the standalone user CPU 185, and other user devices form a robust graphical user interface (R-GUI) 184 for the user to view various data. In some embodiments, the standalone user CPU 185 includes a personal computer, a laptop, a tablet, and/or a smartphone.

[00268] In various embodiments, the scale 189 includes trigger data. The trigger data includes user data values and/or combinations of different data values with user

demographic information that indicates that the user has a risk for a condition, such as a disorder or disease. In response to the trigger data and the scale-obtained data or other user data from the other user devices indicating that the user has a risk for a condition, the scale prompts the user to determine if the user would like additional health information. The prompt is display on the user display 102 of the scale 189 and/or using the R-GUI 184. For example, a synopsis of the prompt is displayed on the user display of the scale 189 and further information is display using the R-GUI 184 if the user is interested.

[00269] For example, the aggregated data from the scale 189 and the one or more user devices, in various embodiments, is compared to trigger data to determine if the user is at risk for a condition. The trigger data is stored directly on a memory circuit of the scale 189 and/or is stored on a memory circuit of the standalone user CPU 185 (and accessible by the scale). The trigger data includes values of various user data that indicate the user has a likelihood about a particular threshold of having and/or being at risk for a condition. In response to a match with the trigger data, the scale indicates a potential risk to the user and prompts the user to indicate if they would like more information via the user interface. In response to the user indicating they would like further information, the enterprise system filters the user data for data correlated with the condition and filters the Internet for various data regarding the condition and/or matching the filtered user data.

[00270] In response to the user selecting the prompt and indicating that they would like additional information, the scale 189 and/or standalone user CPU 185 filters the user data from the scale 189 and the other user devices 186, 187 and filters data from the Internet 149 to identify data that is relevant to the condition. In this manner, the enterprise system is used as a medical analytic driver that filters scale-obtained data, user device-obtained data, and data from the Internet to identify data related to the condition.

[00271] In response to the filter, the user and/or the scale, in various embodiments, are used to further assess the condition of the user and/or obtain additional information. The assessment includes the user assessing, using the scale user interface 191 or the R-GUI 184. For example, in response to the filter, the enterprise system identifies various addition information. The additional information include various generic health information, articles, blogs/forums or social groupings, and other data identified based on the filter of the Internet using the data that correlates with the condition and the trigger data. The user views the additional information using the interface 191 and/or R-GUI 184. The scale is used to further assess the condition of the user by performing additional tests (e.g., body-mass- index, QRS complex over time) and/or asking the user questions.

[00272] The enterprise system can provide a prompt to the user that indicates general information about the condition and the user has some risk for the condition. The prompt asks if the user would like more information and in response to the user requesting more information, the enterprise system provides the aggregated user data to a physician for review and to confirm the diagnosis. The physician is provided access to the user data using the internet 149 and/or external circuitry 112, such as server CPU that is accessible by the physician. In response to the physician confirming the diagnosis and/or correlation, the scale 189 is modified with the confirmed diagnosis. The external circuitry 1 12, in various embodiments, can be or include the assessment circuitry, as previously described. Additionally, the scale can prompt the user to ask about other likely symptoms, prompt for further tests, such as breath hold, valsalva, etc.

[00273] The modification, in some embodiments, includes storing, on the scale 189, various correlation data (e.g., diagnosis data), adding additional devices and/or parameters to track (e.g., halter monitor, ECG tracking device, prescription drug titration, weight tracking and/or threshold values, exercise goals, stress test), and/or health information about the condition (e.g., articles), among other data. Furthermore, the standalone user CPU 185 of the enterprise system, in some embodiments is used to display various data to the user, such as generic health information, user-specific diagnosis data, blogs/forums of social groups, physician reports, and/or studies, among other information. Further, the modification can include configuring the scale to perform additional tests and/or to track particular parameters based on a confirmed diagnosis and/or identified risk (to monitor the risk for the condition and/or encourage progress).

[00274] In various embodiments and environments, a single scale can be used by multiple different users. A subset or each of the different users can have user devices that can be synchronized to the scale and/or can be in communication and display scale-obtained data or aggregated user data via a GUI of the user device. The multiple users may synchronize their respective user devices to the common scale (or to multiple scales).

Additionally, one or more of the user may have activated a service involving outputting aggregated data to the external circuitry for a variety of purposes, such as the social groups, physician reports, generic health information, etc., as described above in connections with various embodiments directed to filtering the user data for data correlated with the condition and filtering the Internet for various data regarding the condition and/or matching the filtered user data, and the scale can store an indication of the activation. The scale can selectively output aggregated data and/or portions thereof to different sources, such as the user device (for viewing on a GUI of the user device) and/or the external circuitry, responsive to identifying different biometrics to authorize the respective communication. The different biometrics can include a hierarchy of biometrics that correspond to communication of different levels of sensitivity of user data. In specific embodiments, the scale can verify that the user device has identified the user within a threshold period of time prior to

synchronizing and/or communicating scale-obtained data.

[00275] Further, the scale can perform different levels of security on the user data prior to communicating externally from the scale. The different levels can be a function of the sensitivity of the user, with higher sensitivity user data having greater amounts of security techniques and/or resulting in a lower likelihood of identifying the user then lower sensitivity user data. Alternatively and/or in addition, the different levels of security can be implemented as a function of the identification of the external circuitry /user device and/or respective security measures of the external circuitry and/or user device. As an example, data output to a first user device which has previously been identified and verified by the user may have lower amounts of security performed than the same data output to a second user device which has not previously been identified. The data output to the second user device may, for example, be encrypted and cannot be viewed until the user enters a password and/or code. In other examples, the amount of security depends on security measures of the user device and/or external circuitry and/or accessibility of the user device and/or external circuitry. As an example, user data output to a first user device which is not connected to the Internet may have lower amounts of security performed than the same user data output to a second user device which is connected and is used by the user to browse the Internet (thus subject to security risks). As another example, user data output to server circuitry that is accessible from other circuitry for querying purposes may have higher security performed than user data output to a standalone external circuitry (or another server circuitry) that does not allow other devices to query the external circuitry (and/or has other security measures in place, such as firewalls, encryption on stored data, data masking, defense in depth, anti-virus techniques, hashing, intrusion detection systems, logging and auditing, multi-factor authentication, password and/or other authentication security, finger print analysis, vulnerability scanners, physical security, virtual private network, timed access control, intrusion protection system, sandboxing, etc.) For example, a first external circuitry with a defense in depth system in place may have lower security measures performed on user data communicated thereto than a second external circuitry that has a firewall and anti-virus software.

[00276] FIG. 11 shows an example process for filtering data from a user-specific scale- based enterprise system, consistent with aspects of the present disclosure. As illustrated the user-specific scale based enterprise system includes a scale 189, standalone CPU 188, and various user devices (e.g. , smartwatch 187, smartphone 186, and smartcup 190). The user- specific scale based enterprise system is used as a medical analytic driver that provides data by filtering the user data based on trigger data and filtering data from the internet based on the filtered user data and trigger data.

[00277] The scale is configured to monitor signals and/or data indicative of physiologic parameters of the user while the user is standing on the platform (e.g., collect scale-based/ obtained data 165). The user device further monitors signals and/or data indicative of physiologic parameters of the user. Both the scale and the user device collect user data of varying user sensitivities. For example, the scale 189 collects user data, such as cardiogram data and data indicative of disorders and disease, and other user data, such as demographic information and weight. The user devices collect user data such as exercise data, food intake or liquid intake data, sleep data, cardiogram data, among other information.

[00278] In various embodiments, the scale and the user device are time synchronized prior to obtaining the user data. As previously discussed, the scale and user device can be time synchronized while the user is standing on the scale and/or by tapping the user device on the scale to time synchronize via the force sensor circuitry (e.g., strain gauges) of the scale and a built-in accelerometer of the remote-user physiologic device.

[00279] The standalone user CPU 188, and other user devices form a R-GUI for the user to view various data. The scale 189 includes a GUI, such as a FUI. In various embodiments, using the scale-based and/or obtained user data 165, such as user demographic data, various reports or dashboards are displayed using the FUI and/or the GUI. The reports/dashboards includes displays of various scale-obtained parameter values and/or progress. The control of the FUI or GUI can be provided the user device, such a user device that has previously been or is paired with the scale and that is detected by the scale. As a specific example, the scale provides a cellphone with control functions to control the display of the FUI in response to detecting the cellphone is within a threshold distance.

[00280] As previously discussed, the scale (and/or standalone CPU 188) includes trigger data. The scale-based/obtained user data 165 is compared to the trigger data to determine if the user has or is at risk for a condition. In various embodiments, the aggregated data from the scale and the one or more user devices is compared to the trigger data, although embodiments are not so limited. In response to the trigger data and the scale-obtained data or other user data from the other user devices indicating that the user has a risk for a condition, the scale prompts the user to determine if the user would like additional health information. In response to the user selecting the prompt indicating they are interested in additional information, the scale 189 and/or standalone user CPU 188 filters the user data from the scale 189 and the other user devices 187, 186, 190 and filters data from the Internet 163 to identify data that is relevant to the condition using a scale-enterprise filter circuitry, at block 198. For example, first the user data is filtered to identify a subset of the user data that is relevant to the condition, such as based on the trigger data. The subset of user data and trigger data is used to filter data from the Internet 163, in various embodiments. The filter results in various additional health information identified by searching the Internet 163 based on the filters, such as generic health information related to the condition, social groupings, additional symptoms, additional tests or parameters to perform, devices and/or products related to the condition, blogs, studies, etc.

[00281] In response to the filter identifying various health information, the user and/or the scale 189, in various embodiments, are used to further assess the condition of the user and/or obtain additional information. For example, at block 158, the user further assesses the condition by viewing the various health information on the FUI of the scale 189 and/or the R-GUI. In various embodiments, the display of the data is discerned by the scale, as discussed further herein. The scale is used to further assess the condition of the user by performing additional tests (e.g., body-mass-index, QRS complex over time) and/or asking the user questions, at block 159.

[00282] Alternatively and/or in addition, the enterprise system provides a prompt to the user that indicates general information about the condition and the user is indicating some risk for the condition. The prompt asks if the user would like more information and in response to the user requesting more information, the enterprise system provides the aggregated user data to a physician for review and to confirm the diagnosis, at block 161. The physician is provided access to the user data using the internet and/or external circuitry, such as server CPU that is accessible by the physician. In response to the physician confirming the diagnosis and/or correlation, the scale 189 is modified with the confirmed diagnosis, at block 157.

[00283] In accordance with various embodiments, the user interface (e.g., FUI, GUI, and/or voice input/output circuitry) of the scale is used to provide portions of the user data, diagnosis data (e.g., scale-obtained physiological data), generic health information, and/or other feedback to the user. In some embodiments, the scale 189 includes a display configuration filter (e.g., circuitry and/or computer readable medium) configured to discern the data to display to the user and displays the portion. The display configuration filter discerns which portions of the data to display to the user on the foot-controlled user interface based on various user demographic information (e.g., age, gender, height, diagnosis) and the amount of data. For example, the generic health information identified from the filter 198 may include an amount of data that if all the data is displayed on the foot-controlled user interface, the data is difficult for a person to read and/or uses multiple display screens.

[00284] The display configuration filter discerns portions of the data to display using the scale user interface, such as synopsis of the generic health information (or user data or feedback) and an indication that additional data is displayed on another user device, and other portions to display on the other user device (e.g., the R-GUI). The other user device is selected by the scale (e.g., the filter) based on various communications settings. The communication settings include settings such as user settings (e.g., the user identifying user devices to output data to), scale-based biometrics (e.g., user configures scale, or default settings, to output data to user devices in response to identifying scale-based biometrics), and/or proximity of the user device (e.g., the scale outputs data to the closest user device among a plurality of user devices and/or in response to the user device being within a threshold distance from the scale), among other settings. For example, the scale determines which portions of the user data, clinical indication, generic health information and/or other feedback to output and outputs the remaining portion of data to a particular user device based on user settings/communi cation authorization (e.g., what user devices are authorized by the user to receive particular user data from the scale), and proximity of the user device to the scale. The determination of which portions to output is based on what type of data is being displayed, how much data is available, and the various user demographic information (e.g., an eighteen year old is able to see better than a fifty year old).

[00285] In various embodiments, the enterprise system is used to group users of the scale. A social group, as used herein, includes grouping of a set of scale users based on the aggregated user data. In some embodiments, the social groups are intra scale and/or intra scale.

[00286] Intra scale social groups includes users that use a single scale. For example, the scale is configured to collected data from multiple users. As a specific example, a scale is used by a family training for a marathon. Each member of the family uses the scale to track various physiological parameters, include cardiogram related characteristics, recovery parameters, weight, body-mass-index, and exercise results. With intra scale social groups, the users are using the same scale and, thereby, have a familiarity with one another.

Thereby, the user's identities are disclosed in the social groups, in some embodiments. The family is grouped into an intra scale social grouping and provided with alerts when reports of progress and/or rankings are available for the family. Further, one or more of the users are provided an alert in response to user-configured thresholds, such as a weight threshold.

[00287] Inter scale groups include users that use different scales. For example, the scale communicates user data to an external circuitry, such as a server CPU that pools the user data and identifies correlations between the user data. The social groups are identified automatically by the external circuitry based on the user data. The social groups are based on demographics, user goals, symptoms, physiological parameter values, diagnosis, prescription drug usage, lifestyle habits, medical history, family medical history, and a combination thereof. In specific embodiments, the external circuitry groups user data based on fitness goals (current or historical), demographic information, and scale-obtained data. The external circuitry analyzes the pooled user data from the plurality of scales to identify various correlations between users and dynamically updates the first database over time. Based on the correlated user data sets, the external circuitry identifies various user data sets with correlation and provides users of the correlated data sets access to a social group. The correlation can include demographics, values of user data, user goals, risks, diagnosis, condition, etc.

[00288] In response to the social group, the external circuitry can output a prompt that notifies the respective user of the availability of a social group and generates a way to access the social group, such as generated a new blog, form, and/or page of a social network.

Alternatively and/or in addition, the access to the social group includes accessing (e.g., via the FUI or GUI) reports and/or dashboards about user data.

[00289] The user data provided in the social group, in some embodiments, does not identify the user. For example, with inter scale social groups, the users are not using the same scale and, thereby, may not have familiarity with one another. Thereby, the users' identities are not disclosed in the inter scale social groups, in some embodiments. For example, the scale removes portions of the user data that identifies the user, adds an identifier indicative of the user and the scale to the user data, optionally encrypts at least a portion of the user data, and outputs at least a portion of the user data to external circuitry (e.g., the alias ID as previously described)

[00290] In various embodiments, the data provided to the social groups is not the entire set of user data. For example, there can be a selective relationship between the social group, the number of users in the group, and one or more of the following: level of familiarity between users, level of familiarity of users with physiological data, level of interest in physiological data, and a level of complexity of the data displayed. A level of familiarity between users includes knowledge of identity of the users and/or interactions between the users. A level of familiarity of users with physiological data include technical knowledge of the users regarding physiologic data. A level of interest in physiological data includes interest of the user in more information related to physiologic data. And a level of complexity of the data displayed includes the technical complexity of the subset of user data provided/displayed to the social group. Alternatively and/or in addition, the subset can be normalized, as previously discussed.

[00291] As a specific example, the social group includes an intra scale social group of a family trying to lose weight. The members of the social group are familiar with one another but do not have significant knowledge/background regarding physiological data. However, the users are interested in how weight loss is correlated with physiological data. In various embodiments, the social group is provided access, such as reports, to user data that identifies each user of the group and includes a general correlation of a cardiogram data with weight loss/gains. The users are not provided with specific data, such as BCG and/or PWV that is more complex.

[00292] As another example, the social group includes an inter scale professional social group that includes a physician and a number of users that do not know one another. The members of the social group are not familiar with another and the number of users do not have significant knowledge/background regarding physiological data. However, the physician does. In various embodiments, the social group is provided access, such as reports, to user data that does not identify each user of the group and includes specific data, such as BCG and/or PWV that is more complex. The physician, in such embodiments, may be provided the identification of the user and can explain the more complex data.

[00293] The above described social group and various levels can be used in combination with various features described herein, such as encryption of the data. Further, portions of the data is displayed using a FUI of the scale. The scale discerns which portions to display based on the above-described levels and/or the sensitivity values, as previously described.

[00294] FIG. lm shows an example process for providing social grouping using pooled user data, consistent with various aspects of the present disclosure. The social groupings can be providing using a scale-based user-physiologic social grouping system. The scale-based user-physiologic social grouping system includes a plurality of scales and external circuitry 112. Each scale is configured to monitor signals from a plurality of users, correlate the respective data with the appropriate user using scale-based biometrics and user profiles, and communicate the signals and/or data to the external circuitry.

[00295] In a number of embodiments, user data from the scale and/or multiple scales is used to group users into social groups. The social groups are based on identification of a correlation between user data sets, such as a common scale, demographics, user goals, symptoms, physiological parameter values, diagnosis, prescription drug usage, lifestyle habits, medical history, family medical history, and a combination thereof. For example, the users are grouped into social groups based on a correlation between the user data sets. In some embodiments, intra-scale social groups are formed and the correlation includes the data set are generated by the same scale. For example, a family, a team training for an event, a health group using a gym, etc. may use a single scale.

[00296] For example, the scale is configured to collect data from multiple users. As a specific example, a scale is used by a family training for a marathon. Each member of the family uses the scale to track various physiological parameters, include cardiogram related characteristics, recovery parameters, weight, body-mass-index, and exercise results. With intra-scale social groups, the user are using the same scale and, thereby, have a familiarity with one another. Thereby, the user's identities are disclosed in the social groups, in some embodiments. As a specific example, a family is grouped into an intra-scale social grouping and provided with alerts when reports of progress and/or rankings are available for the family. Further, one or more of the users are provided an alert in response to user- configured thresholds, such as a weight threshold.

[00297] The external circuitry 112, as previously described, identifies various correlations between the user data stored in the user-specific knowledge database 139 and associated with different users. For example, the external circuitry 112 identifies other users that have correlated user data and identified patterns of risks for conditions or diseases based on the correlation.

[00298] Based on the correlations, the external circuitry groups the users into social groups. The user is provided a prompt on a user device 171 -1 , 171 -2, 172-3, 171 -4 and can access the social group using the respective device. Alternatively, the user provides an indication to display the prompt on another user device. In various embodiments, the social group is accessed using the Internet, such as a webpage 169-1 , 169-N that contains a blog, forum, and/or social network page and/or an application that is accessed. Each webpage 169-1, 169-N corresponds to a respective social group and is accessed by users of the groups. The webpages illustrates various reports and dashboards indicating changes in scale-obtained data and various symptoms, treatments, exercise, and/or other information available. The external circuitry 1 12 automatically populates and updates the reports over time using subsequently received scale-based data.

[00299] The external circuitry 1 12, in some embodiments, generates social group data for the social group(s) using scale obtained data of respective users in the group. The users are notified of the availability of a social group and/or social group data via a prompt on a FUI of the scale the next time the user stands on the scale (and the scale recognizes the user using a scale-obtained biometric) and/or on a user interface of another user device. The prompt includes an indication that a social group is available. In various embodiments, the prompt provides a direct link to the generated social group data, such as reports, dashboard, forum, blog and/or webpage. The user accesses the social group by clicking the direct link on the FUI of the scale and/or on the user interface of another user device. Further, the identity of the users remains anonymous and/or the user can select a code-name to use. Alternatively and/or in addition, the scale groups users of the scale into a social group (e.g., intra-scale social group). In such embodiments, the scale, the standalone CPU and/or the external circuitry 1 12 generates the social group data.

[00300] For example, the user is provided a prompt on a user device 171 -1, 171-2, 172-3, 171-4 indicating that a social group is available. In response to the user selecting the prompt, indicating the user is interested in the social group, the user is provided with social group data. The social group data, in various embodiments, is accessed using the Internet and/or the scale and/or another user device.

[00301] In various embodiments, the social group data includes reports and/or dashboards automatically generated and displayed by the external circuitry 112 using the user-specific knowledge database 139. The reports and/or dashboards include rankings of the user based on scale-obtained data, progress (e.g., increases or decreases in physiological parameters, weight, etc.), diagnosis, symptoms, treatments receiving, and other scale- obtained data. For example, a progress report includes increases and/or decreases in physiological parameters and/or weight of the users of the social group over a period of time (e.g., week, month, year) and identifies potential causes of the increase or decrease (e.g., correlations based on scale-obtained data and/or data from other user devices).

[00302] The access to the social group can include selective access to normalized data from the user data sets of the subset of users of the social group. The external circuitry can identify and normalize data form the use data sets based on prioritization data and normalization data, as previous described. Further, the prioritization data can be dependent on or a function of the specific correlation of the social group. The prioritization data and normalization data can be default values and/or can be based on inputs from the users. For example, each respective user can view their user data (as normalized and would be displayed to other users of the social group) prior to joining the social group. The user can verify and/or adjust the normalization.

[00303] In various embodiments, the webpages 169-1 , 169-N are semi-private. A semi- private webpage is accessible by the user of the group and potential user invited by other users of the social group. For example, the users 170-1, 170-2, 170-3, 170-Q of the first social group have access the first webpage 169-1 not the second webpage 169-2. Similarly, the users 172-1 , 172-2, 172-R of the second social group have access to the second webpage 169-N but not the first webpage 169-1.

[00304] The social group data, as used herein, includes various data generated by using at least a portion of the user data of the users belonging to the respective social group.

Example social group data includes reports and/or dashboard, forums, blogs, and webpages of social networks. The reports and/or dashboards include rankings of the user based on scale-obtained data, progress (e.g., increases or decreases in physiological parameters, weight, etc.), diagnosis, symptoms, treatments receiving, and other scale-obtained data. For example, a progress report includes increases and/or decreases in physiological parameters and/or weight of the users of the social group and identifies potential causes of the increase or decrease (e.g., correlations based on scale-obtained data and/or data from other user devices). In various embodiments, the prompt provides a direct link to the generated reports, dashboard, forum, blog and/or webpage. The user accesses the social group by clicking the direct link on the FUI of the scale and/or on the user interface of another user device.

Further, the identity of the users remains anonymous and/or the user can select a code-name to use.

[00305] In various embodiments, the social group is accessed using the Internet, such as a webpage 169-1 , 169-N that contains a blog, forum, and/or social network page and/or an application that is accessed. Each webpage 169-1, 169-N corresponds to a respective social group and is accessed by users of the groups. The webpages illustrates various reports and dashboards indicating changes in scale-obtained data and various symptoms, treatments, exercise, and/or other information available. The external circuitry 1 12 automatically populates and updates the reports over time using subsequently received scale-based data.

[00306] The social groups can be intra-scale and/or intra-scale. The social grouping of an intra-scale includes grouping the users of the scale and providing various reports, updates, alerts, and/or forums for the users of the group to interact. The forum, in some

embodiments, includes a private (or public) page of a social network webpage that the users of the group access and communicate. A private page, for instance, is only accessible by the users of the group and/or persons authorized by users of the group.

[00307] In other embodiments, the social groupings are inter-scale. For example, an external circuitry 1 12, such as a server CPU, may receive user data (with user identifying data removed) from a plurality of scales and identifies various users with correlated user data. The users with correlated user data, such as demographic data and/or scale-obtained data, are grouped by the external circuitry 112 without user input.

[00308] An inter-scale social group can be interfaced with an intra-scale social group. For example, two or more intra-scale groups are combined to form a new inter-scale social group and/or an intra-scale social group is added to an existing inter-scale social group or used to create a new inter-scale social group. Both the inter-scale social group and the intra- scale social group may exist at the same time, in various embodiments. The interface does not destroy the social groups. For example, a family uses a scale and forms an intra-scale group. Based on an identified correlation of the intra-scale social group, such as a common user goal (e.g., training for a marathon), the members of the intra-scale social group are added to the inter-scale social group. Alternatively, a specific user is added to another inter- scale social group based on a correlation.

[00309] Further, data that is sensitive to the user and/or identifies the user, in some embodiments, is not provided in the social group data. For example, with inter-scale social groups, the users are not using the same scale and, thereby, may not have a familiarity with one another. Thereby, the user's identities are not disclosed in the inter-scale social groups, in some embodiments. For example, as discussed further herein, the user are identified by an alias ID and/or other non-identifying code.

[00310] The data provided to the social groups is not the entire set of (sensitive) user data. For example, in accordance with various embodiments, there is a selective relationship between the social group, the number of users in the group, and one or more of the following: level of familiarity between users, level of familiarity of users with physiological data, level of interest in physiological data, and a level of complexity of the data displayed.

[00311] In a number of embodiments, the scale is configured to collect data from a plurality of users. In such embodiments, the scale differentiates between the different uses based on scale-based biometrics. The scale-obtained data includes health data that is sensitive to the user, such that unintentional disclosure of scale-obtained data is not desired. Differentiating between the two or more users and automatically communicating (e.g., without further user input) user data responsive to scale-obtained biometrics, in various embodiments, provides a user-friendly and simple way to communicate data from a scale while avoiding and/or mitigating unintentional (and/or without user consent)

communication. For example, the scale, such as during an initialization mode for each of the two or more users, collects user data to identify the scale-based biometrics and stores an indication of the scale-based biometrics in a user profile corresponding with the respective user. During subsequent measurements, the scale recognizes the particular user by comparing collected signals to the indication of the scale-based biometrics in the user profile. The scale, for example, compares the collected signals to each user profile of the two or more users and identifies a match between the collected signals and the indication of the scale-based biometrics. A match, in various embodiments, is within a range of values of the indication stored. Further, in response to verifying the scale-based biometric(s), a particular communication mode is authorized. In accordance with various embodiments, the scale uses a cardiogram of the user (e.g., various combinations of BCG-to-ECG timing, BCG characteristics, ECG characteristics, heart rate) and/or other scale-obtained biometrics (e.g., weight, body-mass-index, foot shape, toe print, other foot characteristics) to differentiate between two or more users.

[00312] The scale communicates the user data, such as the aggregated user data, in various embodiments, by authorizing the communication based on the biometric identified and adding various security measures to the user data in response to the authorized communication. For example, in various embodiments, the user profiles are associated with a hierarchy of different levels of biometrics that enable different data to be communicated and/or to different sources. For example, in response to verifying a first biometric, the scale outputs the user's weight to the user's smartphone or other standalone CPU. In response to verifying a second biometric, the scale outputs additional data to external circuitry and/or that is more sensitive to the user, as discussed further herein. In response to verifying the second biometric, the scale outputs the user data (such as higher-sensitivity user data) from the scale to the smartphone or standalone CPU, from the scale to the smartphone/standalone CPU for sending to a third party, and/or from the scale to the third party.

[00313] As an example, for user data, the above described biometrics are used as directed by the user for indicating and defining protocol to permit such data to be exported from the scale to other external circuitry. In more specific embodiments, the scale operates in different modes of data security including, for example: a default mode in which the user's body mass and/or weight is displayed regardless of any biometric which would associate with the specific user standing on the scale; another mode in which complicated data (or data reviewed infrequently) is only exported from the scale under specific manual commands provided to the scale under specific protocols; and another mode or modes in which the user- specific data that is collected from the scale is processed and accessed based on the type of data. Such data categories include categories of different levels of importance and/or sensitivities such as the above-discussed high and low level data and other data that might be very specific to a symptom and/or degrees of likelihood for diagnoses. Optionally, the CPU in the scale is also configured to provide encryption of various levels of the user's data that is sensitive.

[00314] The social grouping, in specific embodiments, is provided as part of a hierarchy of services. A service, as used herein, includes a function and/or action performed using the platform system and uses and/or is in response to scale-obtained data. A hierarchy of services include different services enabled in response to user selection and activation of subscription levels. The subscription levels have different weighted values that activate the subscription level. Further, each subscription level is associated with one or more services. For example, the scale-obtained data from the particular scale drives a physiological related prompt for a service.

[00315] The weighted values of the subscription levels, in some embodiments, are based on the value of the service or corresponding data to the user, the user-sensitivity and/or regulation of the corresponding data, the value of the corresponding data to the service provider/provider of the scales, value of the corresponding data to the requester. The value of the service and/or corresponding data can be determined based on a level of security of the data, a level of technical detail of the data, and/or a likelihood of diagnosing the user based on the data. The requester of the data provided by the service, in various

embodiments, includes a third party, such as a researcher, physician, government entity, and/or other entity. The different subscription levels have different weighted values that, in some embodiments, increase with the levels of subscription.

[00316] In a number of specific embodiments, social groupings are providing as services in a plurality of different subscription levels. For example, in a first subscription level, a user is provided access to a social group based on exercise interest and/or goals or other consumer related interest. At a second subscription level, a user is provided access to physiological social group, which is based on scale-obtained data and/or diagnosis of the scale-obtained data by a physician. At a third subscription level, a user is provided access to the (more) professional social group. For example, a physician participates in the professional social group with other users and/or actively tracks progress of the user.

Alternatively and/or in addition, the physician uses the professional social group to perform a study and/or experiment. As a specific service example, a gym may offer gym

subscriptions whose cost decreases as fitness of the user increases, which is determined using scale-obtained data. The cost maybe offset by insurance companies (e.g., health insurance) which offer contributions to a gym subscription if the user goes a threshold number of times in a month and/or based on other health factors.

[00317] The external circuitry 112 can output an indication of an available social group to the scales of the users with the correlated user data and each scale displays, using the FUI, an alert of an available social group. The user accesses the social group data using the FUI and/or a standalone CPU that is in communication with the scale. For example, in response to an alert, the user selects an interest in the social grouping using the FUI. The scale outputs the indication and a link to a webpage or application associated with the social group (or information on how to access the social grouping) to the standalone CPU (e.g., user smartphone, tablet). The webpage can include a page of a social network, an application or portal for the user to log-in to, a forum, etc. In various embodiments, data is tracked for users of the social group and reports are provided, such as rankings of the users in the group, progress of the users, new observations, and/or information learned. Alternatively and/or in addition, the users of the group are provided a forum to discuss various health issues, successes, failures, exercise, eating, etc.

[00318] In accordance with various embodiments, the user interface (e.g., GUI, FUI, and/or voice input/output circuitry) of the scale is used to provide portions of the user data, diagnosis data (e.g., scale-obtained physiological data), generic health information, and/or other feedback to the user. In some embodiments, the scale includes a display configuration filter (e.g., circuitry and/or computer readable medium) configured to discern the data to display to the user and displays the portion, as previously discussed.

[00319] The scale can be used by multiple different users. A subset or each of the different users can have various user devices (e.g., peripheral devices such as cellphones, smartwatches, laptop or desktop computers). The multiple users may synchronize their respective user devices to the common scale (or to multiple scales). One or more of the users can be provided with access to the social group, as previously described herein. The user is provided with the access to the social group via the user interface (e.g., a display on the FUI of the scale) and/or an external GUI of a user device. The scale can default display to the user interface of the scale (e.g., FUI) and/or the external GUI based on use of the scale. For example, the scale can be in a consumer mode, a professional mode, and/or a combination consumer/professional mode (among other modes). Data provided to the user and/or the professional can default to be displayed on the FUI of the scale, the GUI of the user device, and/or a GUI of other external circuitry depending on the use of the scale. [00320] FIG. In shows an example apparatus for updating a patient profile, consistent with various aspects of the present disclosure. The apparatus includes scale having a platform and a user display, as previously described in connection with FIG. la.

[00321] In a number of embodiments, the processing circuitry 104 and/or the scale includes an output circuit. The output circuit receives the user data and, in response, sends the user data, including the data indicative of the user's identity and the generated cardio- related physiologic data, from the scale for reception at external circuitry 1 12 that is not integrated within the scale. In various embodiments, the output circuit displays on the user display the user's weight and the data indicative of the user's identity and/or the generated cardio-related physiologic data corresponding the collected signals.

[00322] The external circuitry 112 receives the user data, and in response, validates the user data as concerning the user associated with a specific patient profile using the data indicative of the user's identity. The validation, in some embodiments, includes comparing user data to the patient profile. In various embodiments, the data indicative of the user's identity is the user ID and/or is associated with the user ID (e.g., is mapped to and/or otherwise correlated to). In a number of embodiments, the external circuitry 1 12 includes and/or is in communication with a patient profile database 1 13. The patient profile database 113 stores a plurality of patient profiles, each corresponding to a specific user. Each patient profile includes medical data, demographic data, historical user data, and user identification data, among other information. For example, the patient profiles can be medical records. The data in the patient profiles is searched by the external circuitry 112 and matched to the data indicative of the user's identity within the user data.

[00323] In specific embodiments, the validation includes comparing a physiologic parameter and/or other biometric data determined using the user data to data within the patient profile. For example, the biometric data is captured by the data-procurement circuitry 108 and can include the length of the foot, the width of the foot, a shape of the foot, a toe print, facial recognition, etc. The physiologic parameter can include a BCG measurement determined using the user data. In various embodiments, the scale determines the physiological parameter and outputs the physiological parameter as user data.

Alternatively, the external circuitry 1 12 determines the physiological parameter.

[00324] The validation can include comparing voice sounds captured from the user and/or pictures of the user captured using the scale to data within the patient profile. For example, the scale can include a speaker component and the processing circuitry 104 and the speaker component can capture voice sounds from the user. In other embodiments, the scale includes a camera circuitry and the processing circuitry 104 and the camera circuitry capture pictures of the user, such as facial images to perform facial recognition techniques on. The output circuitry outputs the voice sounds and/or pictures to the external circuitry 112. The external circuitry 112 can compare the voice sounds and/or pictures to the patient profile database 113 to identity a corresponding patient profile and to verify the user data corresponds to the user associated with the patient profile.

[00325] In further specific embodiments, the validation includes comparing verification data, which is included in the user data, to data within the patient profile. Verification data can include a password (e.g., toe tapped password or voice spoken password), a physical address, a user ID, a security number, a picture selected on the user display, a barcode, an RFID scan, a communication from another circuitry, and a combination thereof. For example, a user device, such as a smart phone and/or smart watch may send a user ID to the scale (e.g., password, finger print, or identification). Alternatively, the user inputs the verification data. For example, the data-procurement circuitry 108 can include input/output circuitry configured to capture the verification from the user. The input/output by the user can include vocal, data entry on the scale and/or an input/out circuitry, and/or data entered by the user to another user device (and the other user device sends the data to the scale). That is, in some embodiments, other user circuitry, including a communication circuit, provides the data indicative of the user's identity to the scale.

[00326] The verification, in various embodiments, is performed by the external circuitry 112 or by the scale and the external circuitry 112. For example, the processing circuitry 104 of the scale can confirm identification of the user using the collected signals indicative of the user's identity and communicates the data indicative of the user's identity to the external circuitry 112. The data can include a user ID and/or other metadata stored on the memory circuitry of the scale, in some embodiments. The external circuitry 112 validates the cardio- related physiologic data as concerning the user associated with the specific patient profile by identifying the specific patient profile and correlating the cardio-related physiologic data with the specific patient profile. Alternatively, the processing circuitry 104 generates the data indicative of the user's identity (but may not confirm identification). The external circuitry 112 validates the cardio-related physiologic data as concerning the user by confirming identification of the user using the data indicative of the user's identity in response to identifying the patient profile (e.g., matching the user identification data to the patient profile) and correlates the cardio-related physiologic data with the patient profile. [00327] The external circuitry 112, in response to the validation, automatically updates the patient profile. An automatic update, as used herein, includes storing data associated with the user within the patient profile without manual data entry by a human. The update includes a user weight and a cardiogram measurement collected by the scale and/or determined using user data collected by the scale. Although embodiments are not so limited and the update can include various physiological parameters. In various embodiments, the user data includes physiologic parameters and/or data indicative of the physiologic parameters. For example, the processing circuitry 104 can determine the physiological parameters or the external circuitry 112 can.

[00328] In a number of related embodiments, the external circuitry 112 determines additional physiological parameters and/or clinical indications of the user. The clinical indication is determined using the cardio-related physiologic data and is stored in the specific patient profile for review by a physician. The clinical indication can be determined by correlating the user data with historically collected user data and/or sample census data, and therefrom, deriving the clinical indication.

[00329] The clinical indication and/or the physiological parameter may indicate an emergency situation. For example, the clinical indication and/or the physiological parameter is compared to a threshold value and in response to the clinical indication and/or the physiological parameter being outside the threshold value, a signal providing an alert is generated by the external circuitry 112 and/or the processing circuitry 104 and sent to another circuitry. For example, the clinical indication and/or the physiological parameter may indicate the user is having heart failure, a seizure, difficulty breathing, and fluid buildup, among other indications. In some instances, the signal is sent from the external circuitry 112 to circuitry associated with a nurse station and/or the physician such that another person is informed of the emergency situation.

[00330] Although the present examples embodiments provided above are in reference to external circuitry performing the determination, embodiments in accordance with the present disclosure are not so limited. For example, the processing circuitry 104 of the scale can determine the physiologic parameter while the user is standing on the platform. Further, the scale can be used to perform a variety of process in addition or alternatively to checking in a patient. As described further herein, the scale can be located at user's home and/or in a commercial setting and can offer review of the scale obtain data by a physician or other health professional as a service. In other embodiments, assessment circuitry can perform the described features directed to determining physiological parameters, clinical indications, and updating patient profiles. The assessment circuitry can be integrated with the scale and/or integrated with the external circuitry 112.

[00331] In various related embodiments, the scale is used to perform a question and answer session. For example, the scale can display questions using the user display, provides computer generated voice questions using a speaker component, and/or outputs signals to another device (e.g., such as a tablet at the physician's office, an application on a smart phone of the user, or a smart watch, etc.) that include the questions. The questions are used to identify symptoms and/or reasons why the user is visiting the physician. The answers input by the user are output to the external circuitry 112 and used to update the specific patient profile. The update, for instance, includes populating the data in the specific user patient profile. In various embodiments, the external circuitry uses the input data to determine the clinical indication and/or to further refine the clinical indication stored. As previously described, voice input/output circuitry can be used to perform the question and answer session.

[00332] FIG. lo shows an example process for updating a patient profile, consistent with various aspects of the present disclosure. The apparatus illustrated by FIG. lo can include the apparatus, including one or more scales 128 and external circuitry as previously described. Each scale includes an output circuit to send the user data to external circuitry 112. The external circuitry 112 receives the user data and automatically update a specific patient profile associated with the user. Although the present embodiment describes and illustrates external circuitry performing the processing, embodiments are not so limited and assessment circuitry can perform the described features.

[00333] The apparatus can be used to automatically update patient profiles of a plurality of users. The scales 128, for example, correspond to the plurality of users. For example, each scale, at block 114 waits for a user to stand on the platform. Staff and/or other personal, such as a nurse in the room or a reception can instruct the user to stand on the scale when in the room or when the user enters the room. In various embodiments, in response to the user standing on and/or approaching the scale, the apparatus obtains identification data to identify the user. In other embodiments, the scale is located in the dwelling of the user or in a commercial setting. The user may stand on the scale without instructions from other personal.

[00334] In response to the user standing on the respective scale, the respective scale collects signals indicative of an identity of the user and cardio-physiological measurements. The processing circuitry, at block 117, processes the signals and, in response, derives user data. For example, the processing circuitry of each scale, using the signals, derives and outputs user data corresponding to a particular user to the output circuit.

[00335] In various embodiments, the scale and/or external circuitry 1 12 estimates a height or other relevant distance of the user. For example, the scale includes and/or is in communication with a physical arm. The physical arm is connected to the scale and used to measure a height of the user. The measurement can be digital and/or another person can assist and can verbally input the measurement to the scale. Similarly, the estimated height or distance can occur by the user and/or another person measuring and inputting the measurement to the scale. In some embodiments, the user inputs (verbally, digitally, with another device) an estimate of their height to the scale. In various embodiments, the estimation includes using look up tables and at least one of a sensor on the user's finger and a head sensor on the user's head.

[00336] In accordance with various embodiments, a relevant distance is determined by the scale instructing the user to place their hand at a particular location, such as their waist. For example, the instruction can include a verbal instruction using a speaker component, a written instruction using the user display of the scale or a user display of another user device, and/or a picture on the user display of the scale or of another user device. The scale includes a light source and, responsive to the instruction, outputs a light source from the scale toward the location of the user's hand. Further, the scale determines the relevant distance based on a return from the light source reflecting back from the patient's hand.

[00337] The scale can be used to performs a question and answer session. For example, the data-procurement circuitry and the processing resource (in addition to the user display, a speaker component, and/or a camera circuitry) provide a number of questions in a question and answer session to identify symptoms and/or reasons that the user is visiting the physician, which may optionally include the use of voice input/output circuitry.

[00338] The output circuit receives the user data and outputs various user data. For example, at least a portion of the data is output to the user display of the scale, and, at block

173, each scale displays data to the user. The displayed data includes a body weight measured using the scale, among other data. Further, the output circuit outputs the user data to the external circuitry 1 12.

[00339] In response to receiving the user data from the plurality of scales 128, at block

174, the external circuitry 112 validates respective user data as corresponding to respective user associated with patient profiles, updates the patient profiles using the respective user data, and, optionally, determines clinical indications. In various embodiments, the external circuitry includes computer-readable instructions executed to perform the various function (e.g., the validation logic 192 to validate the user data, update logic 193 to update patient profiles, and clinical indication logic 194 to determine clinical indications using the user data and/or question and answer data).

[00340] The external circuitry 112 can receive the user-data that corresponds to the plurality users from the plurality of scales 128. In response to receiving the user data, the external circuitry 112, at block 174, validates the user data as corresponding to the users associated with the respective patient profiles. The validation can occur by comparing the user data to data in the patient profile database 1 13. Further, at block 176, the external circuitry 112 determines clinical indications using the user data and/or historical user data. For example, the external circuitry 112 includes and/or is in communication with a clinical indication database 177. The clinical indication database 177 includes various sample census data of other users having various clinical indications and/or physiological parameter values and/or symptoms that are indicative of the clinical indication. The external circuitry 112 compares the user data to the clinical indication database 177 to determine correlated clinical indication(s). At block 178, the external circuitry automatically updates the respective patient profiles in the patient profile database 113 that correspond to the users and the user data received.

[00341] In various embodiments, the external circuitry 1 12 outputs the clinical indication and/or other health information back to the scale and/or another user device to display to the user. Further, the external circuitry optionally controls access to the patient profiles. The control of access can include allowing access to the physiological parameter (e.g., a clinical indication) and the user-data to at least one physician corresponding to at least one of the plurality of users and for interpretation. Further, the control includes not allowing access to the physiological parameter(s) to the plurality of users (e.g., without a prescription). In various embodiments, the users are allowed access to the user data in the profile and the scale can display portions of the user data and/or other non-regulated data. In various embodiments, a specific user among the plurality of users is allowed access to the physiological parameter corresponding to the specific user in response to interpretation by a physician corresponding to the specific user and a prescription from the physician to access the physiological parameter. Further, in some embodiments, a demographic model and/or other report is provided to one or more users in response to the physiological parameter and/or categories of interest input by the user. [00342] In a number of embodiments, the external circuitry 1 12 outputs various data. For example, the external circuitry 112 includes an output circuitry to output a signal to other circuitry. The signal, in some embodiments, is output to circuitry associated with the physician, nurses, and/or other staff that is indicative of completion of a check-in process and/or that the user is ready to be seen by the physician. The signal is output in response to the update of the specific user profile. In various embodiments, the signal includes an indication of a clinical indication or data containing the clinical indication, physiological parameters and/or other data. The physician may review the data in the signal and/or log-in to the specific patient profile and review the data prior to seeing the user and/or at the beginning of the appointment. Alternatively and/or in addition, the physiological parameters and/or various other health information is sent to circuitry associated with the user (e.g., the scale for display and/or other user circuitry, such as a cellphone).

[00343] An alert can be sent in response to the clinical indication and/or a physiological parameter being outside a threshold value. For example, in response to a clinical indication that indicates the user is experience heart failure, a signal containing an alert is sent to circuitry of the physician, hospital, nurse station, etc.

[00344] In some embodiments, the external circuitry controls access to the patient profile and/or the data. The control of access includes allowing access to the physiological parameter and/or clinical indications and the user data to a physician corresponding to the user for information. Further, the control includes not allowing access to the physiological parameters and/or clinical indications to the user. In various embodiments, the user is allowed to access the user data in the profile and the scale can display portions of the user data and/or other non-regulated data. Additionally, the external circuitry 1 12 may not allow access to the profile and/or any data corresponding to the profile to non-qualified personal, such as other users. In various embodiments, the user is allowed access the physiological parameter in response to interpretation by the physician and a prescription from the physician to access the physiological parameter. Further, in some embodiments, a demographic model and/or other report is provided to the user in response to the

physiological parameter. For example, the user may not be allowed to view the

physiological parameter but is provided generic information corresponding to other users with similar physiological parameter value.

[00345] The access can be controlled using a verification process. For example, in response to verifying identification of the physician and/or the user, access to particular data can be provided. The verification can be based on a user sign in and password, a password, biometric data, etc., and/or identification of the user using the scale (in which, the relevant data is sent to the scale or another user device in response to the identification).

[00346] In various embodiments, the physiological parameter is provided as an additional service. For example, the user can obtain the information and/or have their physician interpret the information for a service fee. For example, the user can use the scale and data stored thereon as part of an online doctor visit. The service fee can include a one-time fee for a single interpretation, a monthly or yearly service fee, and/or can be a portion of a health care insurance fee (e.g., the user can purchase a health care plan that includes the service). In such embodiments, the physician corresponding to the user can access the physiological parameter and/or other user data in response to verification that the user has enabled the service and verification of the identity of the physician.

[00347] The automatic update of the patient profile and further analysis by the external circuitry 1 12, for example, can result in a reduction of human and computer resources to enter data as compared to manually entering data into the patient profile. The automatic update, thereby, can reduce time spent on entering data into the patient profile and reduce frustration with changing regulation. For example, circuitry of the scale and/or the external circuitry 1 12 can be updated with new questions to ask and/or information to obtain in response to changes in regulations. Further, the update to the circuitry of the scale and/or the external circuitry 1 12 can include a mapping of old data (which may have been coded differently) to new data to correlate the user data obtain over time. Asking questions to the user can prompt the user to remember issues and, in some instances, can be in response to measured data. For example, the user data may indicate the user has a heart condition and the scale, in response, asks questions regarding symptoms or lifestyle habits that are correlated with the heart condition. And, by provided the further analysis to the physician before or during the appointment, the physician can verify potential health issues and discuss the same with the user during the same appointment. Such information can include life-style suggestions, explanation for how to use the prescribed medicine and/or why it is prescribed, and/or other advice, such as symptoms that the user should watch for. In some

embodiments, in response to the clinical indication or data that is outside a threshold, the scale is used to provide an alert indicating a potential medical emergency.

[00348] The remaining figures illustrate various ways to collect the physiologic data from the user, electrode configurations, and alternative modes of the processing circuitry 104. For general and specific information regarding the collection of physiologic data, electrode configurations, and alternative modes, reference is made to U. S. Patent Application 14/338,266 filed on October 7, 2015, which is hereby fully incorporated by references for its teachings.

[00349] FIG. lp shows current paths 100 through the body of a user 105 standing on a scale 110 for the IPG trigger pulse and Foot IPG, consistent with various aspects of the present disclosure. Impedance measurements 115 are measured when the user 105 is standing and wearing coverings over the feet (e.g., socks or shoes), within the practical limitations of capacitive-based impedance sensing, with energy limits considered safe for human use. The measurements 115 can be made with non-clothing material placed between the user's bare feet and contact electrodes, such as thin films or sheets of plastic, glass, paper or wax paper, whereby the electrodes operate within energy limits considered safe for human use. The IPG measurements can be sensed in the presence of callouses on the user's feet that normally diminish the quality of the signal.

[00350] As shown in FIG. lp, the user 105 is standing on a scale 110, where the tissues of the user's body will be modeled as a series of impedance elements, and where the time- varying impedance elements change in response to cardiovascular and non-cardiovascular movements of the user. ECG and IPG measurements sensed through the feet can be challenging to take due to small impedance signals with (1) low SNR, and because they are (2) frequently masked or distorted by other electrical activity in the body such as the muscle firings in the legs to maintain balance. The human body is unsteady while standing still, and constant changes in weight distribution occur to maintain balance. As such, cardiovascular signals that are measured with weighing scale-based sensors typically yield signals with poor SNR, such as the Foot IPG and standing BCG Thus, such scale-based signals require a stable and high quality synchronous timing reference, to segment individual heartbeat- related signals for signal averaging to yield an averaged signal with higher SNR versus respective individual measurements.

[00351] The ECG can be used as the reference (or trigger) signal to segment a series of heartbeat-related signals measured by secondary sensors (optical, electrical, magnetic, pressure, microwave, piezo, etc.) for averaging a series of heartbeat-related signals together, to improve the SNR of the secondary measurement. The ECG has an intrinsically high SNR when measured with body-worn gel electrodes, or via dry electrodes on handgrip sensors. In contrast, the ECG has a low SNR when measured using foot electrodes while standing on said scale platforms; unless the user is standing perfectly still to eliminate electrical noise from the leg muscles firing due to body motion. As such, ECG measurements at the feet while standing are considered to be an unreliable trigger signal (low SNR). Therefore, it is often difficult to obtain a reliable cardiovascular trigger reference timing when using ECG sensors incorporated in base scale platform devices. Both Inan, et al. (IEEE Transactions on Information Technology in Biomedicine, 14:5, 1188-1196, 2010) and Shin, et al.

(Physiological Measurement, 30, 679-693, 2009) have shown that the ECG component of the electrical signal measured between the two feet while standing was rapidly overpowered by the electromyogram (EMG) signal resulting from the leg muscle activity involved in maintaining balance.

[00352] The accuracy of cardiovascular information obtained from weighing scales is also influenced by measurement time. The number of beats obtained from heartbeats for signal averaging is a function of measurement time and heart rate. Typically, a resting heart rates range from 60 to 100 beats per minute. Therefore, short signal acquisition periods may yield a low number of beats to average, which may cause measurement uncertainty, also known as the standard error in the mean (SEM). SEM is the standard deviation of the sample mean estimate of a population mean. Where, SE is the standard error in the samples N, which is related to the standard error or the population S. The following is an example SE for uncorrelated noise:

[00353] For example, a five second signal acquisition period may yield a maximum of five to eight beats for ensemble averaging, while a 10 second signal acquisition could yield 10-16 beats. However, the number of beats available for averaging and SNR determination is usually reduced for the following factors; (1) truncation of the first and last ensemble beat in the recording by the algorithm, (2) triggering beats falsely missed by triggering algorithm, (3) cardiorespiratory variability, (4) excessive body motion corrupting the trigger and Foot IPG signal, and (5) loss of foot contact with the measurement electrodes.

[00354] Sources of noise can require multiple solutions for SNR improvements for the signal being averaged. Longer measurement times increase the number of beats lost to truncation, false missed triggering, and excessive motion. Longer measurement times also reduce variability from cardiorespiratory effects. If shorter measurement times (e.g., less than 30 seconds) are desired for scale-based sensor platforms, sensing improvements need to tolerate body motion and loss of foot contact with the measurement electrodes.

[00355] The human cardiovascular system includes a heart with four chambers, separated by valves that return blood to the heart from the venous system into the right side of the heart, through the pulmonary circulation to oxygenate the blood, which then returns to the left side of the heart, where the oxygenated blood is pressurized by the left ventricles and is pumped into the arterial circulation, where blood is distributed to the organs and tissues to supply oxygen. The cardiovascular or circulatory system is designed to ensure oxygen availability and is often the limiting factor for cell survival. The heart normally pumps five to six liters of blood every minute during rest and maximum cardiac output during exercise increases up to seven-fold, by modulating heart rate and stroke volume. The factors that affect heart rate include autonomic innervation, fitness level, age and hormones. Factors affecting stroke volume include heart size, fitness level, contractility or pre-ejection period, ejection duration, preload or end-diastolic volume, afterload or systemic resistance. The cardiovascular system is constantly adapting to maintain a homeostasis (set point) that minimizes the work done by the heart to maintain cardiac output. Blood pressure is continually adjusting to minimize work demands during rest. Cardiovascular disease encompasses a variety of abnormalities in (or that affect) the cardiovascular system that degrade the efficiency of the system, which include but are not limited to chronically elevated blood pressure, elevated cholesterol levels, edema, endothelial dysfunction, arrhythmias, arterial stiffening, atherosclerosis, vascular wall thickening, stenosis, coronary artery disease, heart attack, stroke, renal dysfunction, enlarged heart, heart failure, diabetes, obesity and pulmonary disorders.

[00356] Each cardiac cycle results in a pulse of blood being delivered into the arterial tree. The heart completes cycles of atrial systole, delivering blood to the ventricles, followed by ventricular systole delivering blood into the lungs and the systemic arterial circulation, where the diastole cycle begins. In early diastole the ventricles relax and fill with blood, then in mid-diastole the atria and ventricles are relaxed and the ventricles continue to fill with blood. In late diastole, the sinoatrial node (the heart's pacemaker) depolarizes then contracting the atria, the ventricles are filled with more blood and the depolarization then reaches the atrioventricular node and enters the ventricular side beginning the systole phase. The ventricles contract and the blood is pumped from the ventricles to arteries.

[00357] The ECG is the measurement of the heart's electrical activity and is described in five phases. The P-wave represents atrial depolarization, the PR interval is the time between the P-wave and the start of the QRS complex. The QRS wave complex represents ventricular depolarization. The QRS complex is the strongest wave in the ECG and is frequently used as a timing reference for the cardiovascular cycle. Atrial repolarization is masked by the QRS complex. The ST interval represents the period of zero potential between ventricular depolarization and repolarization. The cycle concludes with the T-wave representing ventricular repolarization.

[00358] The blood ejected into the arteries creates vascular movements due to the blood's momentum. The blood mass ejected by the heart first travels headward in the ascending aorta and travels around the aortic arch then travels down the descending aorta. The diameter of the aorta increases during the systole phase due to the high compliance (low stiffness) of the aortic wall. Blood traveling in the descending aorta bifurcates in the iliac branch which transitions into a stiffer arterial region due to the muscular artery composition of the leg arteries. The blood pulsation continues down the leg and foot. Along the way, the arteries branch into arteries of smaller diameter until reaching the capillary beds where the pulsatile blood flow turns into steady blood flow, delivering oxygen to the tissues. The blood returns to the venous system terminating in the vena cava, where blood returns to the right atrium of the heart for the subsequent cardiac cycle.

[00359] Surprisingly, high quality simultaneous recordings of the Leg IPG and Foot IPG are attainable in a practical manner (e.g., a user operating the device correctly simply by standing on the impedance body scale foot electrodes), and can be used to obtain reliable trigger fiducial timings from the Leg IPG signal. This acquisition can be far less sensitive to motion-induced noise from the Leg EMG that often compromises Leg ECG measurements. Furthermore, it has been discovered that interleaving the two Kelvin electrode pairs for a single foot, result in a design that is insensitive to foot placement within the boundaries of the overall electrode area. As such, the user is not constrained to comply with accurate foot placement on conventional single foot Kelvin arrangements, which are highly prone to introducing motion artifacts into the IPG signal, or result in a loss of contact if the foot is slightly misaligned. Interleaved designs begin when one or more electrode surfaces cross over a single imaginary boundary line separating an excitation and sensing electrode pair. The interleaving is configured to maintain uniform foot surface contact area on the excitation and sensing electrode pair, regardless of the positioning of the foot over the combined area of the electrode pair.

[00360] Various aspects of the present disclosure include a weighing scale platform (e.g., scale 110) of an area sufficient for an adult of average size to stand comfortably still and minimize postural swaying. The nominal scale length (same orientation as foot length) is 12 inches and the width is 12 inches. The width can be increased to be consistent with the feet at shoulder width or slightly broader (e.g., 14 to 18 inches, respectively). [00361] FIG. lq is a flow chart depicting an example manner in which a user-specific physiologic meter or scale may be programmed in accordance with the present disclosure. This flow chart uses a computer processor circuit (or central processing unit (CPU)) along with a memory circuit shown herein as user profile memory 146a. The CPU operates in a low-power consumption mode, which may be in off mode or a low-power sleep mode, and at least one other higher power consumption mode of operation. The CPU can be integrated with presence and/or motion sense circuits, such as a passive infrared (PIR) circuit and/or pyroelectric PIR circuit. In a typical application, the PIR circuit provides a constant flow of data indicative of amounts of radiation sensed in a field of view directed by the PIR circuit. For instance, the PIR circuit can be installed behind an upper surface which is transparent to infrared light (and/or other visible light) of the platform and installed at an angle so that the motion of the user approaching the platform apparatus is sensed. Radiation from the user, upon reaching a certain detectable level, wakes up the CPU which then transitions from the low-power mode, as depicted in block 140, to a regular mode of operation. Alternatively, the low-power mode of operation is transitioned from a response to another remote/wireless input used as a presence to awaken the CPU. In other embodiments, user motion can be detected by an accelerometer integrated in the scale or the motion is sensed with a single integrated microphone or microphone array, to detect the sounds of a user approaching.

[00362] The flow proceeds to block 142 where the user or other intrusion is sensed as data received at the platform apparatus. At block 144, the circuitry assesses whether the received data qualifies as requiring a wake up. If not, flow turns to block 140. If however, wake up is required, flow proceeds from block 144 to block 146 where the CPU assesses whether a possible previous user has approached the platform apparatus. This assessment is performed by the CPU accessing the user profile memory 146A and comparing data stored therein for one or more such previous users with criteria corresponding to the received data that caused the wake up. Such criteria includes, for example, the time of the day, the pace at which the user approached the platform apparatus as sensed by the motion detection circuitry, the height of the user as indicated by the motion sensing circuitry and/or a camera installed and integrated with the CPU, and/or more sophisticated bio-metric data provided by the user and/or automatically by the circuitry in the platform apparatus.

[00363] As discussed herein, such sophisticated circuitry can include one or more of the following user-specific attributes: foot length, type of foot arch, weight of user, and/or manner and speed at which the user steps onto the platform apparatus, or sounds made by the user's motion or by user speech (e.g., voice). In some embodiments, facial or body-feature recognition may also be used in connection with the camera and comparisons of images therefrom to images in the user profile memory.

[00364] From block 146, flow proceeds to block 148 where the CPU obtains and/or updates user corresponding data in the user profile memory. As a learning program is developed in the user profile memory, each access and use of the platform apparatus is used to expand on the data and profile for each such user. From block 148, flow proceeds to block 150 where a decision is made regarding whether the set of electrodes at the upper surface of the platform are ready for the user, such as may be based on the data obtained from the user profile memory. For example, delays may ensue from the user moving his or her feet about the upper surface of the platform apparatus, as may occur while certain data is being retrieved by the CPU (whether internally or from an external source such as a program or configuration data updates from the Internet cloud) or when the user has stepped over the user display. If the electrodes are not ready for the user, flow proceeds from block 150 to block 152 to accommodate this delay.

[00365] Once the CPU determines that the electrodes are ready for use while the user is standing on the platform surface, flow proceeds to block 160. Stabilization of the user on the platform surface may be ascertained by injecting current through the electrodes via the interleaved arrangement thereof. Where such current is returned via other electrodes for a particular foot and/or foot size, and is consistent for a relatively brief period of time, for example, a few seconds, the CPU can assume that the user is standing still and ready to use the electrodes and related circuitry. At block 160, a decision is made that both the user and the platform apparatus are ready for measuring impedance and certain segments of the user's body, including at least one foot.

[00366] The remaining flow of FIG. lq includes the application and sensing of current through the electrodes for finding the optimal electrodes (162) and for performing impedance measurements (block 164). These measurements are continued until completed at block 166 and all such useful measurements are recorded and are logged in the user profile memory of the user, at block 168. At block 172, the CPU generates output data to provide feedback and, as can be indicated as a request via the user profile for this user, as an overall report on the progress for the user and relative to previous measurements made for this user has stored in the user profile memory. Such feedback may be shown on the user display, through a speaker with co-located apertures in the platform for audible reception by the user, and/or by vibration circuitry which, upon vibration under control of the CPU, the user can sense through one or both feet while standing on the scale. From this output at block 172, flow returns to the low power mode as indicated at block 174 with the return to the beginning of the flow at the block 140.

[00367] FIG. 2a shows an example of the insensitivity to foot placement 200 on scale electrode pairs 205/210 with multiple excitation paths 220 and sensing current paths 215, consistent with various aspects of the present disclosure. An aspect of the platform is that it has a thickness and strength to support a human adult of at least 200 pounds without fracturing, and another aspect of the device platform is comprised of at least six electrodes, where the first electrode pair 205 is solid and the second electrode pair 210 are interleaved. Another aspect is the first and second interleaved electrode pairs 205/210 are separated by a distance of at least 40 +/- 5 millimeters, where the nominal separation of less than 40 millimeters has been shown to degrade the single Foot IPG signal. Another key aspect is the electrode patterns are made from materials with low resistivity such as stainless steel, aluminum, hardened gold, ITO, index matched ITO (IMITO), carbon printed electrodes, conductive tapes, silver-impregnated carbon printed electrodes, conductive adhesives, and similar materials with resistivity lower than 300 ohms/sq. The resistivity can be below 150 ohms/sq. The electrodes are connected to the electronic circuitry in the scale by routing the electrodes around the edges of the scale to the surface below, or through at least one hole in the scale (e.g., a via hole).

[00368] Suitable electrode arrangements for dual Foot IPG measurements can be realized in other embodiments. In certain embodiments, the interleaved electrodes are patterned on the reverse side of a thin piece (e.g., less than 2mm) of high-ion-exchange (HIE) glass, which is attached to a scale substrate and used in capacitive sensing mode. In certain embodiments, the interleaved electrodes are patterned onto a thin piece of paper or plastic which can be rolled up or folded for easy storage. In certain embodiments, the interleaved electrodes are integrated onto the surface of a tablet computer for portable IPG

measurements. In certain embodiments, the interleaved electrodes are patterned onto a kapton substrate that is used as a flex circuit.

[00369] In certain embodiments, the scale area has a length of 10 inches with a width of eight inches for a miniature scale platform. Alternatively, the scale may be larger (up to 36 inches wide) for use in bariatric class scales.

[00370] In the present disclosure, the leg and foot impedance measurements can be simultaneously carried out using a multi-frequency approach, in which the leg and foot impedances are excited by currents modulated at two or more different frequencies, and the resulting voltages are selectively measured using a synchronous demodulator as shown in FIG. 3a. This homodyning approach can be used to separate signals (in this case, the voltage drop due to the imposed current) with very high accuracy and selectivity.

[00371] This measurement configuration is based on a four-point configuration in order to minimize the impact of the contact resistance between the electrode and the foot, a practice well-known in the art of impedance measurement. In this configuration the current is injected from a set of two electrodes (the "injection" and "return" electrodes), and the voltage drop resulting from the passage of this current through the resistance is sensed by two separate electrodes (the "sense" electrodes), usually located in the path of the current. Since the sense electrodes are not carrying any current (by virtue of their connection to a high-impedance differential amplifier), the contact impedance does not significantly alter the sensed voltage.

[00372] In order to sense two distinct segments of the body (the legs and the foot), two separate current paths are defined by electrode positioning. Two injection electrodes can be used, each connected to a current source modulated at a different frequency. The injection electrode for leg impedance is located under the plantar region of the left foot, while the injection electrode for the Foot IPG is located under the heel of the right foot. Both current sources share the same return electrode located under the plantar region of the right foot. This is an illustrative example and other configurations may be used. The sensing electrodes can be localized so as to sense the corresponding segments. Leg IPG sensing electrodes are located under the heels of each foot, while the two foot sensing electrodes are located under the heel and plantar areas of the right foot. The inter-digitated nature of the right foot electrodes ensures a four-point contact for proper impedance measurement, irrespectively of the foot position.

[00373] FIGs. 2b shows an example of electrode configurations, consistent with various aspects of the disclosure. As shown by the electrode connections, in some embodiments, ground is coupled to the heel of one foot of the user (e.g., the right foot) and the foot current injection (e.g., excitation paths 220) is coupled to the toes of the respective one foot (e.g., toes of the right foot). The leg current injection is coupled to the toes of the other foot (e.g., toes of the left foot).

[00374] FIG. 2c shows an example of electrode configurations, consistent with various aspects of the disclosure. As shown by the electrode connections, in some embodiments, ground is coupled to the heel of one foot of the user (e.g., the right foot) and the foot current injection (e.g., excitation paths 220) is coupled to the toes of the one foot (e.g., toes of the right foot). The leg current injection is coupled to the heels of the other foot of the user (e.g., heels of the left foot).

[00375] FIGs. 3a-3b show example block diagrams depicting the circuitry for sensing and measuring the cardiovascular time-varying IPG raw signals and steps to obtain a filtered IPG waveform, consistent with various aspects of the present disclosure. The example block diagrams shown in FIGs. 3a-3b are separated in to a leg impedance sub-circuit 300 and a foot impedance sub-circuit 305.

[00376] Excitation is provided by way of an excitation waveform circuit 310. The excitation waveform circuit 310 provides a stable amplitude excitation signal by way of various wave shapes of various, frequencies, such as more specifically, a sine wave signal (as is shown in FIG. 3a) or, more specifically, a square wave signal (as shown in FIG. 3b). This excitation waveform (of sine, square, or other wave shape) is fed to a voltage-controlled current source circuit 315 which scales the signal to the desired current amplitude. The generated current is passed through a decoupling capacitor (for safety) to the excitation electrode, and returned to ground through the return electrode (grounded-load configuration). Amplitudes of 1 and 4 mA peak-to-peak are typically used for Leg and Foot IPGs, respectively.

[00377] The voltage drop across the segment of interest (legs or foot) is sensed using an instrumentation differential amplifier (e.g., Analog Devices AD8421) 320. The sense electrodes on the scale are AC-coupled to the inputs of the differential amplifier 320

(configured for unity gain), and any residual DC offset is removed with a DC restoration circuit (as exemplified in Burr-Brown App Note Application Bulletin, SBOA003, 1991, or Burr-Brown/Texas Instruments INA118 datasheet). Alternatively, a fully differential input amplification stage can be used which eliminates the need for DC restoration.

[00378] The signal is then demodulated with a phase-sensitive synchronous demodulator circuit 325. The demodulation is achieved in this example by multiplying the signal by 1 or - 1 synchronously with in-phase the current excitation. Such alternating gain is provided by an operational amplifier (op amp) and an analog switch (SPST), such as an ADG442 from Analog Devices). More specifically, the signal is connected to both positive and negative inputs through 10 kOhm resistors. The output is connected to the negative input with a 10 kOhm resistor as well, and the switch is connected between the ground and the positive input of the op amp. When open, the gain of the stage is unity. When closed (positive input grounded), the stage acts as an inverting amplifier with a gain of -1. Further, fully differential demodulators can alternatively be used which employ pairs of double-pole single-throw (DPST) analog switches whose configuration can provide the benefits of balanced signals and cancellation of charge injection artifacts. Alternatively, other demodulators such as analog multipliers or mixers can be used. The in-phase synchronous detection allows the demodulator to be sensitive to only the real, resistive component of the leg or foot impedance, thereby rejecting any imaginary, capacitive components which may arise from parasitic elements associated with the foot to electrode contacts.

[00379] Once demodulated, the signal is band-pass filtered (0.4 80 Hz) with a band-pass filter circuit 330 before being amplified with a gain of 100 with a non-inverting amplifier circuit 335 (e.g., using an LT1058 operational amplifier from Linear Technology Inc.). The amplified signal is further amplified by 10 and low-pass filtered (cut-off at 20 Hz) using a low-pass filter circuit 340 such as 2-pole Sallen-Key filter stage with gain. The signal is then ready for digitization and further processing. In certain embodiments, the signal from the demodulator circuit 325 can be passed through an additional low-pass filter circuit 345 to determine body or foot impedance.

[00380] In certain embodiments, the generation of the excitation voltage signal, of appropriate frequency and amplitude, is carried out by a microcontroller, such as an MSP430 (Texas Instruments, Inc.) or a PIC18Fxx series (Microchip Technology, Inc.). The voltage waveform can be generated using the on-chip timers and digital input/outputs or pulse width modulation (PWM) peripherals, and scaled down to the appropriate voltage through fixed resistive dividers, active attenuators/amplifiers using on-chip or off-chip operational amplifiers, as well as programmable gain amplifiers or programmable resistors. In certain embodiments, the generation of the excitation frequency signal can be accomplished by an independent quartz crystal oscillator whose output is frequency divided down by a series of toggle flip-flops (such as an ECS-100AC from ECS International, Inc., and a CD4024 from Texas Instruments, Inc.). In certain embodiments, the generation of the wave shape and frequency can be accomplished by a direct digital synthesis (DDS) integrated circuit (such as an AD9838 from Analog Devices, Inc.). In certain embodiments, the generation of the wave shape (either sine or square) and frequency can be accomplished by a voltage-controlled oscillator (VCO) which is controlled by a digital microcontroller, or which is part of a phase- locked loop (PLL) frequency control circuit. Alternatively, the waveforms and frequencies can be directly generated by on- or off-chip digital-to-analog converters (DACs).

[00381] In certain embodiments, the shape of the excitation is not square, but sinusoidal. Such configuration can reduce the requirements on bandwidth and slew rate for the current source and instrumentation amplifier. Harmonics, potentially leading to higher electromagnetic interference (EMI), can also be reduced. Such excitation may also reduce electronics noise on the circuit itself. Lastly, the lack of harmonics from sine wave excitation may provide a more flexible selection of frequencies in a multi-frequency impedance system, as excitation waveforms have fewer opportunities to interfere between each other. Due to the concentration of energy in the fundamental frequency, sine wave excitation could also be more power-efficient. In certain embodiments, the shape of the excitation is not square, but trapezoidal. Alternatively, raised cosine pulses (RCPs) could be used as the excitation wave shape, providing an intermediate between sine and square waves. RCPs could provide higher excitation energy content for a given amplitude, but with greatly reduced higher harmonics.

[00382] To further reduce potential electromagnetic interference (EMI), other strategies may be used, such as by dithering the square wave signal (i.e., introducing jitter in the edges following a fixed or random pattern) which leads to so called spread spectrum signals, in which the energy is not localized at one specific frequency (or a set of harmonics), but rather distributed around a frequency (or a set of harmonics). An example of a spread-spectrum circuit suitable for Dual-IPG measurement is shown in FIG. 3b. Because of the synchronous demodulation scheme, phase-to-phase variability introduced by spread-spectrum techniques will not affect the impedance measurement. Such a spread-spectrum signal can be generated by, but not limited to, specialized circuits (e.g., Maxim MAX31C 80, SiTime SiT9001), or generic microcontrollers (see Application Report SLAA291, Texas Instruments, Inc.).

These spread-spectrum techniques can be combined with clock dividers to generate lower frequencies as well.

[00383] As may be clear to one skilled in the art, these methods of simultaneous measurement of impedance in the leg and foot can be used for standard Body Impedance Analysis (BIA), aiming at extracting the relative content of total water, free-water, fat mass and other body composition measures. Impedance measurements for BIA are typically done at frequencies ranging from kilohertz up to several megahertz. The multi-frequency measurement methods described above can readily be used for such BIA, provided that low- pass filtering (345, FIGs. 3a and 3b) instead of band-pass filtering (330, FIGs. 3a and 3b) is performed following the demodulation. In certain embodiments, a separate demodulator channel may be driven by the quadrature phase of the excitation signal to allow the imaginary component of the body impedance to be extracted in addition to the real component. A more accurate BIA can be achieved by measuring both the real and imaginary components of the impedance. This multi -frequency technique can be combined with traditional sequential measurements used for BIA, in which the impedance is measured at several frequencies sequentially. These measurements are repeated in several body segments for segmental BIAs, using a switch matrix to drive the current into the desired body segments.

[00384] While FIG. 2 shows a circuit and electrode configuration suitable to measure two different segments (legs and one foot), this approach is not readily extendable to more segments due to the shared current return electrode (ground). To overcome this limitation, and provide simultaneous measurements in both feet, the system can be augmented with analog switches to provide time-multiplexing of the impedance measurements in the different segments. This multiplexing can be a one-time sequencing (each segment is measured once), or interleaved at a high-enough frequency that the signal can be

simultaneously measured on each segment. The minimum multiplexing rate for proper reconstruction is twice the bandwidth of the measured signal, based on signal processing theory (the Nyquist rate), which equals to about 100 Hz for the impedance signal considered here. The rate must also allow for the signal path to settle in between switching, which usually limits the maximum multiplexing rate. Referring to FIG. 14a, one cycle might start the measurement of the leg impedance and left foot impedances (similarly to previously described, sharing a common return electrode), but then follow with a measurement of the right foot after reconfiguring the switches. For specific information regarding typical switch configurations, reference to U.S. Patent Application 14/338,266 filed on October 7, 2015, which is fully incorporated for its specific and general teaching of switch configurations.

[00385] Since right and left feet are measured sequentially, one should note that a unique current source (at the same frequency) may be used to measure both, providing that the current source is not connected to the two feet simultaneously through the switches, in which case the current would be divided between two paths. One should also note that a fully- sequential measurement, using a single current source (at a single frequency) successively connected to the three different injection electrodes, could be used as well, with the proper switch configuration sequence (no splitting of the current path).

[00386] In certain embodiments, the measurement of various body segments (e.g., the legs, right foot and left foot) is achieved simultaneously due to as many floating current sources as segments to be measured, running at separate frequencies so they can individually be demodulated. Such configuration is exemplified in FIG. 14b for three segments (legs, right and left feet). Such configuration provides true simultaneous measurements without the added complexity of time-multiplexing/ demultiplexing, and associated switching circuitry. An example of such a floating current source is found in Plickett, et al,

Physiological Measurement, 32 (2011). Another approach to floating current sources is the use of transformer-coupled current sources (as depicted in FIG. 14c). Using transformers to inject current into the electrodes enables the use of simpler, grounded-load current sources on the primary, while the electrodes are connected to the secondary. The transformer turns ratio can typically be 1 : 1, and since frequencies of interest for impedance measurement are typically in the 10-1000 kHz (occasionally 1 kHz for BIA), relatively small pulse transformers can be used. In order to limit the common mode voltage of the body, one of the electrodes in contact with the foot can be grounded.

[00387] While certain embodiments presented in the above specification have used current sources for excitation, the excitation can also be performed by a voltage source, where the resulting injection current is monitored by a current sense circuit so that impedance can still be derived by the ratio of the sensed voltage (on the sense electrodes) over the sensed current (injected in the excitation electrodes). It should be noted that broadband spectroscopy methods could also be used for measuring impedances at several frequencies. Combined with time-multiplexing and current switching described above, multi-segment broadband spectroscopy can be achieved.

[00388] Various aspects of the present disclosure are directed toward robust timing extraction of the blood pressure pulse in the foot which is achieved by means of a two-step processing. In a first step, the usually high-SNR Leg IPG is used to derive a reference (trigger) timing for each heart pulse. In a second step, a specific timing in the lower-SNR Foot IPG is extracted by detecting its associated feature within a restricted window of time around the timing of the Leg IPG.

[00389] Consistent with yet further embodiments of the present disclosure, FIG. 3c depicts an example block diagram of circuitry, including, for example, the operation of the CPU as in FIG. la with the related more specific circuit blocks/modules in FIGs. 3A-3B. As shown in the center of FIG. 3c, the computer circuit 370 is shown with other previously- mentioned circuitry in a generalized manner without showing some of the detailed circuitry (e.g., amplification and current injection/sensing (372)). The computer circuit 370 can be used as a control circuit with an internal memory circuit (or as integrated with the memory circuit for the user profile memory 146A of FIG. la) for causing, processing and/or receiving sensed input signals as at block 372. These sensed signals can be responsive to injection current and/or these signals can be sensed by less complex grid-based sense circuitry surrounding the platform as is convention in capacitive touch-screen surfaces which, in certain embodiments, the platform includes.

[00390] The memory circuit can be used not only for the user profile memory, but also as to provide configuration and/or program code and/or other data such as user-specific data from another authorized source such as from a user monitoring his/her logged data and/or profile from a remote desk-top. The remote device or desk-top can communicate with and access such data via a wireless communication circuit 376. For example, the wireless communication circuit 376 provides an interface between an app on the user's cellular telephone/tablet and the apparatus, wherefrom the phone is the output/input interface for the platform (scale) apparatus including, for example, an output display, speaker and/or microphone, and vibration circuitry.

[00391] A camera 378 and image encoder circuit 380 (with compression and related features) can also be incorporated as an option. As discussed above, the weighing scale components, as in block 382, are also optionally included in the housing which encloses and/or surrounds the platform.

[00392] For long-lasting battery life in the platform apparatus (batteries not shown), at least the CPU 370, the wireless communication circuit 376, and other current draining circuits are inactive unless and until activated in response to the intrusion/sense circuitry 388. As shown, one specific implementation employs a Conexant chip (e.g., CX93510) to assist in the low-power operation. This type of circuitry is designed for motion sensors configured with a camera for visual verification and image and video monitoring applications (e.g., by supporting JPEG and MJPEG image compression and processing of images). When combined with an external CMOS sensor, the chip retrieves and stores compressed JPEG and audio data in an on-chip memory circuit (e.g., 256 KB/128 KB frame buffer) to alleviate the necessity of external memory.

[00393] In a specific embodiment, a method of using the platform with the plurality of electrodes are concurrently contacting a limb of the user, includes operating such to automatically obtain measurement signals from the plurality of electrodes. As noted above, these measurement signals might initially be through less complex (e.g., capacitive grid- type) sense circuitry. Before or while obtaining a plurality of measurement signals, the signal-sense circuitry 388 is used to sense wireless-signals indicative of the user approaching the platform and, in response, cause the CPU circuitry 370 to transition from a reduced power-consumption mode of operation and at least one higher power-consumption mode of operation. After the circuitry is operating in the higher power-consumption mode of operation, the CPU accesses the user-corresponding data stored in the memory circuit and causes a plurality of impedance-measurement signals to be obtained by using the plurality of electrodes while they are contacting the user via the platform; therefrom, the CPU generates signals corresponding to cardiovascular timings of the user.

[00394] The signal-sense circuit can be employed as a passive infrared detector and with the CPU programmed (as a separate module) to evaluate whether radiation from the passive infrared detector is indicative of a human. For example, sensed levels of radiation that corresponds to a live being, such as a dog, that is less than a three-foot height, and/or has not moved for more than a couple seconds, can be assessed as being a non-human.

[00395] As the user is recognized as being human, the CPU is activated and attempts the discernment process of which user might be approaching. This is performed by the CPU accessing the user-corresponding data stored in the memory circuit (the user profile memory). If the user is recognized based on parameters such as discussed above (e.g., time of morning, speed of approach, etc.), the CPU can select one of a plurality of different types of user-discernible visual/audible/tactile information for presenting the discerned user with visual/audible/tactile information that is retrieved from the memory. For example, user- selected visual/audible data can be outputted for the user. Also, responsive to the motion detection indication, the camera can be activated to capture at least one image of the user while the user is approaching the platform (and/or while the user is on the platform to log confirmation of the same user with the measured impedance information). As shown in block 374 of FIG. 3c, where a speaker is also integrated with the CPU, the user can simply command the platform apparatus to start the process and activation proceeds. As previously discussed, the scale can include voice input/output circuitry to receive the user commands via voice commands.

[00396] In another method, the circuitry of FIG. 3c is used with the electrodes being interleaved and engaging the user, as a combination weighing scale (via block 382) and a physiologic user-specific impedance-measurement device. By using the impedance- measurement signals and obtaining at least two impedance-measurement signals between one foot of the user and another location of the user, the interleaved electrodes assist the CPU in providing measurement results that indicate one or more of the following user- specific attributes as being indicative or common to the user: foot impedance, foot length, and type of arch, and wherein one or more of the user-specific attributes are accessed in the memory circuit and identified as being specific to the user. This information can be retrieved by the user, medical and/or security personnel, according to a data-access authorization protocol as might be established upon initial configuration for the user.

[00397] FIG. 3d shows an exemplary block diagram depicting the circuitry for interpreting signals received from electrodes (e.g., 372 of FIG. 3c), and/or CPU 370 of FIG. 3c. The input electrodes 375 transmit electrical signals through the patient's body

(depending on the desired biometric and physiological test to be conducted) and output electrodes 380 receive the modified signal as affected by a user's electrical impedance 385. Once received by the output electrodes 380, the modified signal is processed by processor circuitry 370 based on the selected test. Signal processing by the processor circuitry 370 is discussed with regards to FIGs. 3a-b. In certain embodiments of the present disclosure, the circuitry within 370 is provided by Texas Instruments part # AFE4300.

[00398] FIG. 4 shows an example block diagram depicting signal processing steps to obtain fiducial references from the individual Leg IPG "beats," which are subsequently used to obtain fiducials in the Foot IPG, consistent with various aspects of the present disclosure. As shown in block 400, the Leg IP and the Foot IPG are simultaneously measured. At 405, the Leg IPG is low-pass filtered at 20 Hz with an 8-pole Butterworth filter, and inverted so that pulses have an upward peak. The location of the pulses is determined by taking the derivative of this signal, integrating over a 100 ms moving window, zeroing the negative values, removing the large artifacts by zeroing values beyond 15x the median of the signal, zeroing the values below a threshold defined by the mean of the signal, and then searching for local maxima. Local maxima closer than a defined refractory period of 300 ms to the preceding ones are dismissed. The result is a time series of pulse reference timings.

[00399] At 410, the foot IPG is low-pass filtered at 25 Hz with an 8-pole Butterworth filter and inverted (so that pulses have an upward peak). Segments starting from the timings extracted (415) from the Leg IPG (reference timings) and extending to 80% of the previous pulse interval, but no longer than one second, are defined in the Foot IPG. This defines the time windows where the Foot IPG is expected to occur, avoiding misdetection outside of these windows. In each segment, the derivative of the signal is computed, and the point of maximum positive derivative (maximum acceleration) is extracted. The foot of the IPG signal is then computed using an intersecting tangent method, where the fiducial (420) is defined by the intersection between a first tangent to the IPG at the point of maximum positive derivative and a second tangent to the minimum of the IPG on the left of the maximum positive derivative within the segment. [00400] The time series resulting from this two-step extraction is used with another signal to facilitate further processing. These timings are used as reference timings to improve the SNR of BCG signals to extract intervals between a timing of the BCG (typically the I- wave) and the Foot IPG for the purpose of computing the PWV, as previously disclosed in U.S. 2013/0310700 (Wiard). In certain embodiments, the timings of the Leg IPG are used as reference timings to improve the SNR of BCG signals, and the foot IPG timings are used to extract intervals between timing fiducials of the improved BCG (typically the I-wave) and the Foot IPG for the purpose of computing the PTT and the (PWV).

[00401] In certain embodiments, the processing steps include an individual pulse SNR computation after individual timings are extracted, either in Leg IPG or Foot IPG.

Following the computation of the SNRs, pulses with a SNR below a threshold value are eliminated from the time series, to prevent propagating noise. The individual SNRs may be computed in a variety of methods known to one skilled in the art. For instance, an estimated pulse can be computed by ensemble averaging segments of signal around the pulse reference timing. The noise associated with each pulse is defined as the difference between the pulse and the estimated pulse. The SNR is the ratio of the root-mean-square (RMS) value of the estimated pulse over the RMS value of the noise for that pulse.

[00402] In certain embodiments, the time interval between the Leg IPG pulses, and the Foot IPG pulses, also detected by the above-mentioned methods, is extracted. The Leg IPG measuring a pulse occurring earlier in the legs compared to the pulse from the Foot IPG, the interval between these two is related to the propagation speed in the lower body, i.e., the peripheral vasculature. This provides complementary information to the interval extracted between the BCG and the Foot IPG for instance, and is used to decouple central versus peripheral vascular properties. It is also complementary to information derived from timings between the BCG and the Leg ICG.

[00403] FIG. 5 shows an example flowchart depicting signal processing to segment individual Foot IPG "beats" to produce an averaged IPG waveform of improved SNR, which is subsequently used to determine the fiducial of the averaged Foot IPG, consistent with various aspects of the present disclosure. Similar to the method shown in FIG. 4, the Leg IP and the Foot IPG are simultaneously measured (500), the Leg IPG is low-pass filtered (505), the foot IPG is low-pass filtered (510), and segments starting from the timings extracted (515) from the Leg IPG (reference timings). The segments of the Foot IPG extracted based on the Leg IPG timings are ensemble-averaged (520) to produce a higher SNR Foot IPG pulse. From this ensemble-averaged signal, the start of the pulse is extracted using the same intersecting tangent approach as described earlier. This approach enables the extraction of accurate timings in the Foot IPG even if the impedance signal is dominated by noise, as shown in FIG. 7b. These timings are used together with timings extracted from the BCG for the purpose of computing the PTT and (PWV). Timings derived from ensemble-averaged waveforms and individual waveforms can also be both extracted, for the purpose of comparison, averaging and error-detection.

[00404] Specific timings extracted from the IPG pulses (from either leg or foot) are related (but not limited) to the peak of the pulse, the minimum preceding the peak, or the maximum second derivative (maximum rate of acceleration) preceding the point of maximum derivative. An IPG pulse and the extraction of a fiducial (525) in the IPG can be performed by other signal processing methods, including (but not limited to) template matching, cross-correlation, wavelet-decomposition, or short window Fourier transform.

[00405] FIG. 6a shows examples of the Leg IPG signal with fiducials (plot 600); the segmented Leg IPG into beats (plot 605); and the ensemble-averaged Leg IPG beat with fiducials and calculated SNR (plot 610), for an exemplary high-quality recording, consistent with various aspects of the present disclosure. FIG. 6b shows examples of the Foot IPG signal with fiducials derived from the Leg IPG fiducials (plot 600); the segmented Foot IPG into beats (plot 605); and the ensemble-averaged Foot IPG beat with fiducials and calculated SNR (plot 610), for an exemplary high-quality recording.

[00406] FIG.7a shows examples of the Leg IPG signal with fiducials (plot 700); the segmented Leg IPG into beats (plot 705); and the ensemble averaged Leg IPG beat with fiducials and calculated SNR (plot 710), for an exemplary low-quality recording, consistent with various aspects of the present disclosure.

[00407] FIG.7b shows examples of the Foot IPG signal with fiducials derived from the Leg IPG fiducials (plot 700); the segmented Foot IPG into beats (plot 705); and the ensemble-averaged Foot IPG beat with fiducials and calculated SNR (plot 710), for an exemplary low-quality recording, consistent with aspects of the present disclosure.

[00408] FIG. 8 shows an example correlation plot 800 for the reliability in obtaining the low SNR Foot IPG pulse for a 30-second recording, using the first impedance signal as the trigger pulse, from a study including 61 test subjects with various heart rates, consistent with various aspects of the present disclosure.

[00409] In certain embodiments, a dual-Foot IPG is measured, allowing the detection of blood pressure pulses in both feet. Such information can be used for diagnostic of peripheral arterial diseases (PAD) by comparing the relative PATs in both feet to look for asymmetries. It can also increase the robustness of the measurement by allowing one foot to have poor contact with electrodes (or no contact at all). SNR measurements can be used to assess the quality of the signal in each foot, and to select the best one for downstream analysis.

Timings extracted from each foot can be compared and set to flag potentially inaccurate PWV measurements due to arterial peripheral disease, in the event these timings are different by more than a threshold. Alternatively, timings from both feet are pooled to increase the overall SNR if their difference is below the threshold.

[00410] In certain embodiments, the disclosure is used to measure a PWV, where the IPG is augmented by the addition of BCG sensing into the weighing scale to determine characteristic fiducials between the BCG and Leg IPG trigger, or the BCG and Foot IPG. The BCG sensors are comprised typically of the same strain gage set used to determine the body weight of the user. The load cells are typically wired into a bridge configuration to create a sensitive resistance change with small displacements due to the ejection of the blood into the aorta, where the circulatory or cardiovascular force produce movements within the body on the nominal order of 1-3 Newtons. BCG forces can be greater than or less than the nominal range in cases such as high or low cardiac output.

[00411] FIGs. 9a-b show example configurations to obtain the PTT, using the first IPG as the triggering pulse for the Foot IPG and BCG, consistent with various aspects of the present disclosure. The I-wave of the BCG 900 normally depicts the headward force due to cardiac ejection of blood into the ascending aorta which is used as a timing fiducial indicative of the pressure pulse initiation of the user's proximal aorta relative to the user's heart. The J-wave is indicative of timings in the systole phase and also incorporates information related to the strength of cardiac ejection and the ejection duration. The K- Wave provides systolic and vascular information of the user's aorta. The characteristic timings of these and other BCG waves are used as fiducials that can be related to fiducials of the IPG signals of the present disclosure.

[00412] FIG. 10 shows nomenclature and relationships of various cardiovascular timings, consistent with various aspects of the present disclosure.

[00413] FIG. 11 shows an example graph 1100 of PTT correlations for two detection methods (white dots) Foot IPG only, and (black dots) Dual-IPG method, consistent with various aspects of the present disclosure.

[00414] FIG. 12 shows an example graph 1200 of PWV obtained from the present disclosure compared to the ages of 61 human test subjects, consistent with various aspects of the present disclosure. [00415] FIG. 13 shows an example of a scale 1300 with integrated foot electrodes 1305 to inject and sense current from one foot to another foot, and within one foot.

[00416] FIG. 14a-c shows various examples of a scale 1400 with interleaved foot electrodes 1405 to inject/ sense current from one foot to another foot, and measure Foot IPG signals in both feet.

[00417] FIGs. 15a-d shows an example breakdown of a scale 1500 with interleaved foot electrodes 1505 to inject and sense current from one foot to another foot, and within one foot.

[00418] FIG. 16 shows an example block diagram of circuit-based building blocks, consistent with various aspects of the present disclosure. The various circuit-based building blocks shown in FIG. 16 can be implemented in connection with the various aspects discussed herein. In the example shown, the block diagram includes foot electrodes 1600 that can collect the IPG signals. Further, the block diagram includes strain gauges 1605, and an LED/photosensor 1610. The foot electrodes 1600 is configured with a leg impedance measurement circuit 1615, a foot impedance measurement circuit 1620, and an optional second foot impedance measurement circuit 1625. The leg impedance measurement circuit 1615, the foot impedance measurement circuit 1620, and the optional second foot impedance measurement circuit 1625 report the measurements collected to a processor circuitry 1645. The processor circuitry 1645 collects data from a weight measurement circuit 1630 and an optional balance measurement circuit 1635 that are configured with the strain gauges 1605. Further, an optional photoplethysmogram (PPG) measurement circuit 1640, which collects data from the LED/photosensor 1610, provides data to the processor circuitry 1645.

[00419] The processor circuitry 1645 is powered via a power circuit 1650. Further, the processor circuitry 1645 collects user input data from a user interface 1655 (e.g., iPad®, smart phone and/or other remote user handy/CPU with a touch screen and/or buttons). The data collected/measured by the processor circuitry 1645 is shown to the user via a display 1660. Additionally, the data collected/measured by the processor circuitry 1645 can be stored in a memory circuit 1680. Further, the processor circuitry 1645 can optionally control a haptic feedback circuit 1665, a speaker or buzzer 1670, a wired/wireless interface 1675, and an auxiliary sensor 1685 for one-way or two-way communication between the scale and the user.

[00420] FIG. 17 shows an example flow diagram, consistent with various aspects of the present disclosure. At block 1700, a PWV length is entered. At block 1705, a user's weight, balance, leg, and foot impedance are measured. At 1710, the integrity of signals is checked (e.g., SNR). If the signal integrity check is not met, the user's weight, balance, leg, and foot impedance are measured again (block 1705), if the signals integrity check is met, the leg impedance pulse timings are extracted (as is shown at block 1715). At block 1720, foot impedance and pulse timings are extracted, and at block 1725, BCG timings are extracted. At block 1730, a timings quality check is performed. If the timings quality check is not validated, the user's weight, balance, leg and foot impedance are again measured (block 1705). If the timings quality check is validated, the PWV is calculated (as is shown at block 1735). At block 1740, the PWV is displayed to the user.

[00421] FIG. 18 shows an example scale 1800 communicatively coupled to a wireless device, consistent with various aspects of the present disclosure. A display 1805 can display the various aspects measured by the scale 1800. The scale can also wirelessly broadcast the measurements to a wireless device 1810. The wireless device 1810 can also be implemented as an iPad®, smart phone or other CPU to provide input data for configuring and operating the scale.

[00422] As an alternative or complementary user interface used in other embodiments, the scale includes a FUI which is enabled/implementable by one or more foot-based biometrics (for example, with the user being correlated to previously-entered user weight, and/or foot size/shape). In certain embodiments, the user foot-based biometric is also implemented by the user manually entering data (e.g., a password) on the upper surface or display area of the scale. In implementations in which the scale is configured with a haptic, capacitive or flexible pressure-sensing upper surface, the (upper surface/tapping) touching from or by the user is sensed in the region of the surface and processed according to conventional X - Y grid Signal processing in the logic circuitry/CPU that is within the scale. By using one or more of the accelerometers located within the scale at its corners, such user data entry is sensed by each such accelerometer so long as the user's toe, heel or foot pressure associated with each tap provides sufficient force. In a specific example, when the user stands on the platform of the scale, and the scale detects touching of the toe, the scale can reject the toe touch (or tap) as a foot signal (e.g., similar to wrist rejection for capacitive tablets with stylus). Although the present discussion refers to a FUI, embodiments are not so limited. Various embodiments can include one or more internal or external GUIs that are in communication with the scale and used to obtain a biometric. The internal or external GUIs can be in place of the FUI and/or in combination with a FUI. For example, a user device having a GUI, such as tablet, is in communication with the scale via a wired or wireless connection. The user device obtains a biometric, such a finger print, and communicates the biometric to the scale.

[00423] In various embodiments, the above discussed user interface is used with other features described herein for the purpose of controlling access to prescription (RX) health information and providing additional non-RX health information such as: collecting the categories of interest input by the user, the biometric and/or passwords entered by the user, displaying the additional health information, and displaying an indication that RX health information can be accessed as a service or that additional health information is available. For example, the user enters the categories of interest to the scale using their foot and the user-interface. The user data (e.g., RX health information or other user data) might include less data that is less sensitive to the user (e.g., the user's weight) and data that is more sensitive to the user (e.g., the user's scale obtains cardiograms and other data generated by or provided to the scale and associated with the user's symptoms and/or diagnoses). For data that may be more user-sensitive, the above described biometrics are used as directed by the user for indicating and defining protocol to permit such data to be exported from the scale to other remote devices and/or for such data to be displayed on the user-interface.

[00424] In some specific embodiments, the scale operates in different modes of data security and communication. The different modes of data security and communication are enabled in response to biometrics identified by the user and using the user interface. In some embodiments, the scale is used by multiple users and/or the scale operates in different modes of data security and communication in response to identifying the user using biometrics. The different modes of data security and communication include, for example: a first mode (e.g., default mode) in which the user's body mass and/or weight is displayed regardless of any biometric which would associate with the specific user standing on the scale and no data is communicated to external circuitry; a second mode in which complicated/more-sensitive data (or data reviewed infrequently) is only exported from the scale under specific manual commands provided to the scale under specific protocols and in response to a biometric; and third mode or modes in which the user-specific data that is collected from the scale is processed and accessed based on the type of data and in response to a biometric. Such data categories include categories of different levels of importance and/or sensitivities such as the above-discussed high and low level data and other data that might be very specific to a symptom and/or degrees of likelihood for diagnoses. Optionally, the CPU in the scale is also configured to provide encryption of various levels of the sensitivity of the user data. [00425] In some embodiments, the different modes of data security and communication are enabled in response to recognizing the user standing on the scale using a biometric and operating in a particular mode of data security and communication based on user preferences and/or services activated. For example, the different modes of operation include the default mode (as discussed above) in which certain data (e.g., categories of interest, categories of user data, or historical user data) is not communicated from the scale to extemal circuitry, a first communication mode in which data is communicated to extemal circuitry as identified in a user profile, a second or more communication modes in which data is communicated to a different extemal circuitry for further processing. The different communication modes are enabled based on biometrics identified from the user and user settings in a user profile corresponding with each user.

[00426] In a specific embodiment, a first user of the scale may not be identified and/or have a user profile set up. In response to the first user standing on the scale, the scale operates in a default mode. During the default mode, the scale displays the user's body weight on the FUI and does not output user data. A second user of the scale has a user profile set up that indicates the user would like data communicated to a computing device of the user. When the second user stands on the scale, the scale recognizes the second user based on a biometric and operates in a first communication mode. During the first communication mode, the scale outputs at least a portion of the user data to an identified extemal circuitry. For example, the first communication mode allows the user to upload data from the scale to extemal circuitry identified by the user (e.g., the computing device of the user) that includes non-regulated health information. In the first communication mode, the scale performs the processing of the raw sensor data and/or the extemal circuitry can. For example, the scale sends the raw sensor data and/or non-regulated health information to a computing device of the user. The computing device may not provide access to the raw sensor data to the user and/or can send the raw sensor data to another external circuitry for further processing in response to a user input. For example, the computing device can ask the user if the user would like additional health information and/or regulated health information as a service. In response to receiving an indication the user would like the additional health information and/or regulated health information, the computing device outputs the raw sensor data and/or non-regulated health information to another external circuitry for processing, providing to a physician for review, and controlling access, as discussed above. [00427] In one or more additional communication modes, the scale outputs raw sensor data to an external circuitry for further processing. For example, during a second communication mode and a third communication, the scale sends the raw sensor data and other data to external circuitry for processing. Using the above-provided example, a third user of the scale has a user profile set up that indicates the third user would like additional health information, such as non-regulated health information based on categories of interest. When the third user stands on the scale, the scale recognizes the third user based on one or more biometrics and operates in a second communication mode. During the second communication mode, the scale outputs the raw sensor data to the external circuitry. The external circuitry processes the raw sensor data, determines at least one physiologic parameter of the user, and derives the additional health information. The external circuitry allows access to the user to additional health information but does not allow the user to access regulated health information, including the physiologic parameter. For example, the regulated health information may not be accessed by the third user until the third user has paid a service fee and/or until a prescription by a physician is obtained. In some embodiments, the external circuitry outputs the additional health information and/or an indication that additional health information can be accessed to the scale to display to the third user on the user interface.

[00428] A fourth user of the scale has a user profile set up that indicates the fourth user has enabled a service to access regulated health information. When the fourth user stands on the scale, the scale recognizes the user based on one or more biometrics and operates in a fourth communication mode. In the fourth communication mode, the scale outputs raw sensor data to the external circuitry, and the external circuitry processes the raw sensor data and controls access to the data. For example, the external circuitry may not allow access to the regulated health information until a physician reviews the information. In some embodiments, the external circuitry outputs data to the scale, in response to physician review. For example, the output data can include the regulated health information and/or an indication that regulated health information is ready for review. The external circuitry may be accessed by the user, using the scale and/or another user device. In some embodiments, using the FUI of the scale, the scale displays the regulated health information to the user. In various embodiments, if the scale is unable to identify a particular (high security) biometric that enables the fourth communication mode, the scale may operate in a different communication mode and may still recognize the user. For example, the scale may operate in a default communication mode in which the user data collected by the scale is stored in a user profile corresponding to the fourth user and on the scale. In some related embodiments, the user data is output to the external circuitry at a different time.

[00429] Although the present embodiments illustrates a number of security and communication modes, embodiments in accordance with the present disclosure can include additional or fewer modes. Furthermore, embodiments are not limited to different modes based on different users. For example, a single user may enable different communication modes in response to particular biometrics of the user identified and/or based on user settings in a user profile.

[00430] In various embodiments, the scale defines a user data table that defines types of user data and sensitivity values of each type of user data. In specific embodiments, the FUI or other user interface displays the user data table. In other specific embodiments a user interface of a smartphone, tablet, and/or other computing device displays the user data table. For example, a wired or wireless tablet is used, in some embodiments, to display the user data table. The sensitivity values of each type of user data, in some embodiments, define in which communication mode(s) the data type is communicated and/or which biometric is used to enable communication of the data type. In some embodiments, a default or pre-set user data table is displayed and the user revises the user data table using the foot-controlled user interface. The revisions are in response to user inputs using the user's foot and/or contacting or moving relative to the FUI. Although the embodiments are not so limited, the above (and below) described control and display is provided using a wireless or wired tablet or other computing device as a user interface. The output to the wireless or wired tablet, as well as additional external circuitry, is enabled using biometrics. For example, the user is encouraged, in particular embodiments, to configure the scale with various biometrics. The biometric include scale-based biometrics and biometrics from the tablet or other user computing device, such as a finger print. The biometric, in some embodiments, used to enable output of data to the tablet and/or other external circuitry includes a higher integrity biometric (e.g., higher likelihood of identifying the user accurately) than a biometric used to identify the user and stored data on the scale. [00431] An example user data table is illustrated below:

The above-displayed table is for illustrative purposes and embodiments in accordance with the present disclosure can include additional user-data types than illustrated, such as cardiogram characteristics, clinical indications, physiologic parameters, user goals, demographic information, etc. In various embodiments, the user data table includes additional rows than illustrated. The rows, in specific embodiments, include different data input sources and/or sub-data types (as discussed below). Data input sources include source of the data, such as physician provided, input from the Internet, user provided, from the external circuitry. The different data from the data input sources, in some embodiments, is used alone or in combination.

[00432] In various embodiments, the user adjusts the table displayed above to revise the sensitivity values of each data type. Further, although the above-illustrated table includes a single sensitivity value for each data type, in various embodiments, one or more of the data types are separated into sub-data types and each sub-data type has a sensitivity value. As an example, the user-specific advertisement is separated into: prescription advertisement, external device advertisements, exercise advertisements, and diet plan advertisement.

Alternatively and/or in addition, the sub-data types for user-specific advertisement include generic advertisements based on a demographic of the user and advertisements in response to scale collected data (e.g., advertisement for a device in response to physiologic parameters), as discussed further herein.

[00433] For example, weight data includes the user's weight and historical weight as collected by the scale. In some embodiments, weight data includes historical trends of the user's weight and correlates to dietary information and/or exercise information, among other user data. Body mass index data, includes the user's body mass index as determined using the user's weight collected by the scale and height. In some embodiments, similar to weight, body mass index data includes history trends of the user's body mass index and correlates to various other user data.

[00434] User-specific advertisement data includes various prescriptions, exercise plans, dietary plans, and/or other user devices and/or sensors for purchase, among other advertisements. The user-specific advertisements, in various embodiments, are correlated to input user data and/or scale-obtained data. For example, the advertisements include generic advertisements that are relevant to the user based on a demographic of the user. Further, the advertisements include advertisements that are responsive to scale collected data (e.g., physiologic parameter includes a symptom or problem and advertisement is correlated to the symptom or problem). A number of specific examples include advertisements for beta blockers to slow heart rate, advertisements for a user wearable device (e.g., Fitbit®) to monitor heart rate, and advertisements for a marathon exercise program (such as in response to an indication the user is training for a marathon), etc.

[00435] Physician provided diagnosis/report data includes data provided by a physician and, in various embodiments, is in responsive to the physician reviewing the scale- obtained data. For example, the physician provided diagnosis/report data includes diagnosis of a disorder/condition by a physician, prescription medication prescribed by a physician, and/or reports of progress by a physician, among other data. In various embodiments, the physician provided diagnosis/reports are provided to the scale from external circuitry, which includes and/or accesses a medical profile of the user.

[00436] Scaled stored suggestion data includes data that provides suggestions or advice for symptoms, diagnosis, and/or user goals. For example, the suggestions include advice for training that is user specific (e.g., exercise program based on user age, weight, and cardiogram data or exercise program for training for an event or reducing time to complete an event, such as a marathon), suggestions for reducing symptoms including dietary, exercise, and sleep advice, and/or suggestions to see a physician, among other suggestions. Further, the suggestions or advice include reminders regarding prescriptions. For example, based on physician provided diagnosis/report data and/or user inputs, the scale identifies the user is taking a prescription medication. The identification includes the amount and timing of when the user takes the medication, in some embodiments. The scale reminds the user and/or asks for verification of consumption of the prescription medication using the foot- controlled user interface.

[00437] As further specific examples, recent discoveries may align and associate different attributes of scale-based user data collected by the scale to different tools, advertisements, and physician provided diagnosis. For example, it has recently been discovered that atrial fibrillation is more directly correlated with obesity. The scale collects various user data and monitors weight and various components/symptoms of atrial fibrillation. In a specific embodiment, the scale recommends/suggests to the user to: closely monitor weight, recommends a diet, goals for losing weight, correlates weight gain and losses for movement in cardiogram data relative to arrhythmia. The movement in cardiogram data relative to arrhythmia, in specific embodiments, is related to atrial fibrillation. For example, atrial fibrillation is associated with indiscernible or fibrillating p- waves and beat to beat fluctuations. Thereby, the scale correlates weight gain/loss with changes in amplitude (e.g., discernibility) of a p-wave of a cardiogram (preceding a QRS complex) and changes in beat to beat fluctuations.

[00438] FIGs. 19a-c show example impedance as measured through different parts of the foot based on the foot position, consistent with various aspects of the present disclosure. Example impedance measurement configurations may be implemented using a dynamic electrode configuration for measurement of foot impedance and related timings. Dynamic electrode configuration may be implemented using independently-configurable electrodes to optimize the impedance measurement. As shown in FIG. 19a, interleaved electrodes 1900 are connected to an impedance processor circuit 1905 to determine foot length, foot position, and/or foot impedance. As is shown in FIG. 19b, an impedance measurement is determined regardless of foot position 1910 based on measurement of the placement of the foot across the electrodes 1900. This is based in part in the electrodes 1900 that are engaged

(blackened) and in contact with the foot (based on the foot position 1910), which is shown in FIG. 19c.

[00439] More specifically regarding FIG 19a, configuration includes connection/de- connection of the individual electrodes 1900 to the impedance processor circuit 1905, their configuration as current-carrying electrodes (injection or return), sense electrodes (positive or negative), or both. The configuration is preset based on user information, or updated at each measurement (dynamic reconfiguration) to optimize a given parameter (impedance SNR, measurement location). The system algorithmically determines which electrodes under the foot to use in order to obtain the highest SNR in the pulse impedance signal. Such optimization algorithm may include iteratively switching configurations and measuring the impedance, and selecting the best suited configuration. Alternatively, the system first, through a sequential impedance measurement between each individual electrode 1900 and another electrode in contact with the body (such as an electrode in electrode pair 205 on the other foot), determine which electrodes are in contact with the foot. By determining the two most apart electrodes, the foot size is determined. Heel location can be determined in this manner, as can other characteristics such as foot arch type. These parameters are used to determine programmatically (in an automated manner by CPU/logic circuitry) which electrodes are selected for current injection and return (and sensing if a Kelvin connection issued) to obtain the best foot IPG.

[00440] In various embodiments involving the dynamically reconfigurable electrode array 1900/1905, an electrode array set is selected to measure the same portion/segment of the foot, irrespective of the foot location on the array. FIG. 19b illustrates the case of several foot positions on a static array (a fixed set of electrodes are used for measurement at the heel and plantar/toe areas, with a fixed gap of an inactive electrode or insulating material between them). Depending on the position of the foot, the active electrodes are contacting the foot at different locations, thereby sensing a different volume/segment of the foot. If the IPG is used by itself (e.g., for heart measurement), such discrepancies may be non-consequential. If timings derived from the IPG are referred to other timings (e.g., R-wave from the ECG, or specific timing in the BCG), such as for the calculation of a PTT or PWV, the small shifts in IPG timings due to the sensing of slightly different volumes in the foot (e.g., if the foot is not always placed at the same position on the electrodes) can introduce an error in the calculation of the interval. With respect to FIG. 19b, the timing of the peak of the IPG from the foot placement on the right (sensing the toe/plantar region) is later than from the foot placement on the left, which senses more of the heel volume (the pulse reaches first the heel, then the plantar region). Factors influencing the magnitude of these discrepancies include foot shape (flat or not) and foot length.

[00441] Various embodiments address challenges relating to foot placement. FIG. 19c shows an example embodiment involving dynamic reconfiguration of the electrodes to reduce such foot placement-induced variations. As an example, by sensing the location of the heel first (as described above), it is possible to activate a subset of electrodes under the heel, and another subset of electrodes separated by a fixed distance (1900). The other electrodes (e.g., unused electrodes) are left disconnected. The sensed volume will therefore be the same, producing consistent timings. The electrode configuration leading to the most consistent results may be informed by the foot impedance, foot length, the type of arch (all of which can be measured by the electrode array as shown above), but also by the user ID (foot information can be stored for each user, then looked up based on automatic user recognition or manual selection (e.g., in a look-up-table stored for each user in a memory circuit accessible by the CPU circuit in the scale).

[00442] In certain embodiments, the apparatus measures impedance using a plurality of electrodes contacting one foot and with at least one other electrode (typically many) at a location distal from the foot. The plurality of electrodes (contacting the one foot) is arranged on the platform and in a partem configured to inject current signals and sense signals in response thereto, for the same segment of the foot so that the timing of the pulse-based measurements does not vary because the user placed the one foot at a slightly different position on the platform or scale. In FIG. 19a, the foot-to-electrode locations for the heel are different locations than that shown in FIGs. 19b and 19c. As this different foot placement can occur from day to day for the user, the timing and related impedance measurements are for the same (internal) segment of the foot. By having the processor circuit inject current and sense responsive signals to first locate the foot on the electrodes (e.g., sensing where positions of the foot's heel plantar regions and/or toes), the pattern of foot-to-electrode locations permits the foot to move laterally, horizontally and both laterally and horizontally via the different electrode locations, while collecting impedance measurements relative to the same segment of the foot.

[00443] The BCG/IPG system can be used to determine the PTT of the user, by identification of the average I-Wave or derivative timing near the I-Wave from a plurality of BCG heartbeat signals obtained simultaneously with the Dual-IPG measurements of the present disclosure to determine the relative PTT along an arterial segment between the ascending aortic arch and distal pulse timing of the user's lower extremity. In certain embodiments, the BCG/IPG system is used to determine the PWV of the user, by identification of the characteristic length representing the length of the user's arteries, and by identification of the average I-Wave or derivative timing near the I-Wave from a plurality of BCG heartbeat signals obtained simultaneously with the Dual-IPG measurements of the present disclosure to determine the relative PTT along an arterial segment between the ascending aortic arch and distal pulse timing of the user's lower extremity. The system of the present disclosure and alternate embodiments may be suitable for determining the arterial stiffness (or arterial compliance) and/or cardiovascular risk of the user regardless of the position of the user's feet within the bounds of the interleaved electrodes. In certain embodiments, the weighing scale system incorporated the use of strain gage load cells and six or eight electrodes to measure a plurality of signals including: body weight, BCG, body mass index, fat percentage, muscle mass percentage, and body water percentage, heart rate, heart rate variability, PTT, and PWV measured simultaneously or synchronously when the user stands on the scale to provide a comprehensive analysis of the health and wellness of the user.

[00444] In other certain embodiments, the PTT and PWV are computed using timings from the Leg IPG or Foot IPG for arrival times, and using timings from a sensor located on the upper body (as opposed to the scale measuring the BCG) to detect the start of the pulse. Such sensor may include an impedance sensor for impedance cardiography, a hand-to-hand impedance sensor, a photoplethysmogram on the chest, neck, head, arms or hands, or an accelerometer on the chest (seismocardiograph) or head.

[00445] Communication of the biometric information is another aspect of the present disclosure. The biometric results from the user are stored in the memory on the scale and displayed to the user via a display on the scale, audible communication from the scale, and/or the data is communicated to a peripheral device such as a computer, smart phone, tablet computing device. The communication occurs to the peripheral device with a wired connection, or can be sent to the peripheral device through wireless communication protocols such as Bluetooth or WiFi. Computations such as signal analyses described therein may be carried out locally on the scale, in a smartphone or computer, or in a remote processor (cloud computing).

[00446] Other aspects of the present disclosure are directed toward apparatuses or methods that include the use of at least two electrodes that contacts feet of a user. Further, circuitry is provided to determine a pulse arrival time at the foot based on the recording of two or more impedance signals from the set of electrodes. Additionally, a second set of circuitry is provided to extract a first pulse arrival time from a first impedance signal and use the first pulse arrival time as a timing reference to extract and process a second pulse arrival time in a second impedance signal.

[00447] Various embodiments are implemented in accordance with the following U.S. Provisional Applications. U.S. Provisional Application (Ser. No. 62/264,807), entitled "Diagnostic-Capable Scale for Auto-Updating Patient Profiles Using Scale Collected User Data", filed December 8, 2015, which is herein incorporated by reference generally for its teaching of physiological scales, measurements, and communications and specifically with regards to automatically updating patient profiles using scale-obtained data features and aspects as described in connection with FIGs. la-Id in the underlying provisional. U.S. Provisional Application (Ser. No. 62/260,174), entitled "Remote Physiologic Parameter Determination Methods and Platform Apparatuses", filed November 25, 2015, which is herein incorporated by reference generally for its teaching of physiological scales, measurements, and communications and specifically with regards to remotely processing physiological data and providing generic health information based on categories of interest features and aspects as described in connection with FIGs. la- Id of the underlying provisional. U.S. Provisional Application (Ser. No. 62/263,380), entitled "Remote

Physiologic Parameter Determination Methods and Platform Apparatuses", filed December 4, 2015, which is herein incorporated by reference generally for its teaching of physiological scales, measurements, and communications and specifically with regards to controlling access to scale-obtained data that is regulated features and aspects as described in connection with FIGs. la-Id in the underlying provisional. U.S. Provisional Application (Ser. No. 62/265,833), entitled "Scale-Based User-Physiological Heuristic Systems", filed December 10, 2015, which is herein incorporated by reference generally for its teaching of

physiological scales, measurements, and communications and specifically with regards to securely communicating and storing scale data, identifying risks that a user has a condition, and providing generic information correlating to the condition to the user features and aspects as described in connection with FIGs. la-lb of the underlying provisional. U.S. Provisional Application (Ser. No. 62/265,627), entitled "Secure Data Communication and Storage Using Scale-Based User-Physiological Heuristic Systems", filed December 10, 2015, which is herein incorporated by reference generally for its teaching of physiological scales, measurements, and communications and specifically with regards to securely communicating and storing scale data using alias IDs and security measures, separately storing the correlation of the alias IDs to scale/user from user data, and securely providing the data to other sources while protecting the users' identities features and aspects as described in connection with FIGs. la-lc of the underlying provisional. U.S. Provisional Application (Ser. No. 62/266,440), entitled "Scale-Based User-Physiological Social Grouping System", filed December 11, 2015, which is herein incorporated by reference generally for its teaching of physiological scales, measurements, and communications and specifically with regards to identifying correlations between data sets of different users and grouping users into social groups based on the correlations features and aspects as described in connection with FIGs. la-lc of the underlying provisional. U.S. Provisional Application (Ser. No. 62/266,496), entitled "User-Specific Scale-Based Enterprise System", filed December 11, 2015, which is herein incorporated by reference generally for its teaching of physiological scales, measurements, and communications and specifically with regards to using trigger data on the scale to trigger a filter of data on the enterprise system and identify correlated data with a user condition related to the trigger data features and aspects as described in connection with FIGs. la- Id of the underlying provisional.

U.S. Provisional Application (Ser. No. 62/266,523), entitled "Social Grouping Using a User- Specific Scale-Based Enterprise System", filed December 11, 2015, which is herein incorporated by reference generally for its teaching of physiological scales, measurements, and communications and specifically with regards to using grouping users into inter and intra scale social groups based on aggregated user data sets, and providing normalized user data to other users in the social group aspects as described in connection with FIGs. la-lc of the underlying provisional. For instance, embodiments herein and/or in the provisional applications may be combined in varying degrees (including wholly). Reference may also be made to the experimental teachings and underlying references provided in the underlying provisional application. Embodiments discussed in the provisional applicants are not intended, in any way, to be limiting to the overall technical disclosure, or to any part of the claimed invention unless specifically noted.

[00448] Reference may also be made to published patent documents U.S. Patent Publication 2010/0094147 and U.S. Patent Publication 2013/0310700, which are, together with the references cited therein, herein fully incorporated by reference for the purposes of sensors and sensing technology. The aspects discussed therein may be implemented in connection with one or more of embodiments and implementations of the present disclosure (as well as with those shown in the figures). In view of the description herein, those skilled in the art will recognize that many changes may be made thereto without departing from the spirit and scope of the present disclosure.

[00449] As illustrated herein, various circuit-based building blocks and/or modules may be implemented to carry out one or more of the operations/activities described herein shown in the block-diagram-type figures. In such contexts, these building blocks and/or modules represent circuits that carry out these or related operations/ activities. For example, in certain embodiments discussed above (such as the pulse circuitry modularized as shown in FIGs. 3a-b), one or more blocks/modules are discrete logic circuits or programmable logic circuits for implementing these operations/activities, as in the circuit blocks/modules shown. In certain embodiments, the programmable circuit is one or more computer circuits programmed to execute a set (or sets) of instructions (and/or configuration data). The instructions (and/or configuration data) can be in the form of firmware or software stored in and accessible from a memory circuit. As an example, first and second modules/blocks include a combination of a CPU hardware-based circuit and a set of instructions in the form of firmware, where the first module/ block includes a first CPU hardware circuit with one set of instructions and the second module/block includes a second CPU hardware circuit with another set of instructions.

[00450] Based upon the above discussion and illustrations, those skilled in the art will readily recognize that the above described aspects and features, and without limitation to the number thereof, can be combined in specific designs so that the scale is configured and arranged to perform these aspects and features in combination in a manner consistent with the description thereof. Further, based upon the above discussion and illustrations, those skilled in the art will readily recognize that various modifications and changes may be made to the present disclosure without strictly following the exemplary embodiments and applications illustrated and described herein. For example, the input terminals as shown and discussed may be replaced with terminals of different arrangements, and different types and numbers of input configurations (e.g., involving different types of input circuits and related connectivity). Such modifications do not depart from the true spirit and scope of the present disclosure, including that set forth in the following claims.