The subject of the invention is a method and a system for continuous monitoring of safety and basic life functions of patients, particularly in nursing homes for the elderly, as well as nursing and rehabilitation centres.

A method and a device to noninvasively measure a patient's blood pressure is known from patent description US20062176 6. An electric heart rate measurement signal and a waveform pulse measurement signal, which, starting from the heart, spreads inside the blood vessels up to the pulse location, are detected. The time of propagation of the arterial pressure wave between the heart and the pulse measurement site is determined, based on the electrical measurement signal and the pulse measurement signal. The blood pressure is determined by the relationship between the function based on the propagation time; the function relationship includes the first part which determines the elasticity of the blood vessels and the second part which defines the passive behaviour of the electric current on the blood vessels. The device for noninvasive determination of the patient's blood pressure, includes ECG sensors to detect the electrical signal of the heart potential measurement, pulse sensor used to detect the impulse pulse pressure signal, the evaluation system for determining the propagation time (T) of the arterial pressure wave between the heart and the pulse measurement location based an electrical measurement signal and a pulse measurement signal in which the evaluation unit is designed to determine the blood pressure from the propagation time (T) by means of a relationship between functions whose first part determines the active vasoconstriction activity and a second part which determines the passive flexibility of the blood vessels.

A device casing is known from the Polish utility model application W.123727 in the form of a wrist band, used to monitor selected human life parameters. The casing is characterized by a two-element structure. The main part of the casing is made of flexible plastic, housing a socket for a plastic casing for electronic components. The top layer of the casing includes a convex SOS button with the word written in Braille. In the lower part of the casing, which adheres to the wrist, there are an optical sensor and a thermal sensor. A strip with a membrane button and a RGB LED diode is led out of the plastic housing. Also known from patent description US2015-.^

and apparatus for remote monitoring of a patient using a smartwatch. The sensor device is placed in physical contact with the patient. The sensor communicates with the smartwatch via Bluetooth or other wireless communication protocol. Then the smartwatch communicates with a remote server that collects data about the patient. The system can collect data such as the patient's body temperature, amount of exercise performed by the patient and the patient's sleep time. The invention in concern addresses the problem of patient data collection in a patient's home by means of a remote sensor, transferring data to a computer device, transferring data to a server, processing data, generating alerts for a physician if necessary and providing portals through which a patient and doctor may transmit and exchange data and information.

An intelligent sensor for monitoring vital signs is known from the publication of utility model WO2017128840 (A1), which consists of a body of a watch and a watch strap connected to the body. The strap is inflated in such a way that the body of the watch is pressed against the user's wrist. The watch body includes a multifunctional processor chip, a pulse sensor to monitor the user's heart rate, a blood oxygen sensor to monitor the user's blood oxygen saturation and an electrocardiogram sensor to monitor the user's electrocardiogram data.

A patent application P.408557 was also published regarding a multi- sensor medical telematics device which automates the measurement of arterial pressure and pulse irrespective of location and time. It measures the pressure using the oscillation method. Multisensory apparatus for sending medical telematics of blood pressure and heart rate to the indicated mobile phone, through the use of Bluetooth communication module it transmits measurement data of blood pressure and heart rate to a paired mobile phone or mobile device. The multisensory apparatus for medical telematics of arterial blood pressure has an emergency button which, when pressed by the user, sends an alarm message to the indicated telephone number. In the multisensory apparatus for medical telematics a GPS module was used to locate the user of the blood pressure and pulse measurement device when the emergency button was pressed. Multisensory medical telematics device enables remote measurement via a text message command, via GSM (communication module) it transmits pressure measurement data.

Previous solutions known from the state of the art in a fragmentary manner solve the problems of measuring and monitoring of vital activity parameters by measuring various types of parameters and issues of remote transfer of measurement data to a computer device, generating alarms for a doctor, and delivering them to portals through which a patient and doctor can transfer and exchange data and infoimauun. nuwevei , nu comprehensive technical solutions designed for continuous monitoring of the place of stay of the patients and continuous monitoring of the basic life functions of the patients in care facilities, especially in nursing homes for the elderly has been proposed.

The aim of the invention is to develop a comprehensive method and a system enabling improved care for elderly people in nursing homes by monitoring their location to ensure a quick reaction of personnel to an adverse event such as falls, pulse and pressure surges, temperature fluctuations, moving away from the monitored object as well as monitoring and archiving data provided by the monitoring band for medical and statistical purposes. The new solution is to support the functioning of care facilities and improve the safety of patients as well as provide medical data measurements for medical personnel and doctors as well as for the patients' families.

In the method for continuous monitoring of safety and basic vital functions of the patients, the designated monitored object is within radio coverage of the beacon network in such a way that in every part of the monitored rooms the diagnostic band and fall detector placed on the hip belt, which are provided for every patient, communicate with at least three beacons. In this way continuous monitoring through the central beacon and the IT system monitoring centre is carried out, by providing current information to medical personnel equipped with wristbands informing about the position of the patients in the monitored rooms. In case of an alarm signal sent upon a fall by a fall detector and/or a signal sent by a diagnostic band regarding exceeded limit values of the measured blood pressure, pulse, body temperature, or a signal warning about the ambient air humidity change, or about leaving the facility, they initiate an alarm procedure in the form of providing assistance. In turn, the measurement of blood pressure by a known method is initiated and determined at the moment of applying the patient's finger from the hand, on which the diagnostic wristband is not fastened, simultaneously to the proximity sensor, external electrode, and to the external wrist module for optical measurement of the pulse wave from the applied finger located in the diagnostic band.

In the system for continuous monitoring of safety and basic vital functions of the patients in the monitored rooms, fixed beacons are located in stationary mapped locations, where patients equipped with diagnostic bands and a fall detectors as well as medical personnel and/or doctors equipped with personnel bands reside. In each separate room there is a central beacon connected by a communication line to the IT system monitoring centre. The diagnostic bands, fall detectors, personnel bands, and fixed beacons with CAN interfaces are connected via radio modules

other by bidirectional wireless communication. The diagnostic band holds an external electrode with an external sensor of the wrist module for the optical pulse measurement and an external proximity sensor. In the lower plane of the diagnostic band casing there is an internal electrode with an internal optical sensor of the heart rate wrist module, an internal proximity sensor, and a skin temperature measuring module sensor, as well as a charging and communication connector. In turn, the fall detector consists of a processor to which the following components are connected: radio module, inertia measurement module, charging and communication connector, control button, buzzer, vibration motor. The charging and communication connector is connected in series with the battery charging system, the battery, and the converter blocks. The inertia measurement module consists of a digital block for processing signals, calibration, compensation, and change of orientation, to which an accelerometer is connected through an analogue-to-digital converter. A gyroscope, and a fall detection block as well as a step counting block are connected via an analogue-to-digital converter, while the analogue- digital transducers are connected to an oscillator The method and system as per the invention, due to the constant automatic monitoring of the basic life functions of the patients, makes it fundamentally easier to supervise the personnel working directly with a patient. The unexpected technical effect consists of the automatic signalling and monitoring of patient's location and continuous signalling of adverse events occurring among the patients, which enables an immediate response of medical personnel, including doctors and nurses serving in care facilities, especially the ones housing residents of the nursing homes for the elderly. The invention not only allows for ongoing monitoring of the examined functions of the patients, but above all, for mapping of the nursing home building, it makes it possible to determine the floor and sector in which the alert event took place, which allows for quick assistance. The system collects and processes the patient data, which makes it an important component in the process of gathering individual medical records of individual patients. The main users of the system are medical nurses, carers, for whom the system replaces a large part of the daily manual work, consisting of regularly checking the vital functions of the patients. The system is used by doctors for whom the collected data constitute the basis for making a diagnosis, planning treatment, or other activities necessary to improve the health of the patients. Due to the function of collecting a wide spectrum of data and the ability to perform any commissioned analyses or reports - the system is an important tool for medical personnel and doctors. Individualization of threshold (alert) parameters in individual diagnostic bands is conducted as they are adjusted to the health condition of the current patient. In addition to monitoring the basic iife functions of the patients, an important advantage of the invention is the ongoing monitoring and locating the place of siay m i i equei u uasca ui voluntary leaving of nursing homes by the patients and indication of the location of the alarm event.

An example of the subject of the invention has been illustrated in a drawing, in which Fig.1 - shows a general communication scheme of the system located in the monitored object, Fig.2 - shows the patient's diagnostic band in a perspective in an external top view. Fig.3 - shows the patient's diagnostic band in a perspective view from the inner side adjacent to the wrist, Fig.4 - shows a block diagram of the patient's wristband, Fig.5 - shows a block diagram of a medical personnel wristband, Fig.6 - shows a block diagram of the fall detector, Fig.7 - shows the location of the diagnostic band and fall detector on the patient, Fig.8 - block diagram of a fixed beacon, Fig.9 - block diagram of a central beacon, Fig.10 - block diagram of an inertia measurement module , Fig.11 - shows the algorithm of setting the zero values for individual variables of the inertia measurement module , Fig.12 - shows the daily activity graphs registered with the inertia measurement module placed on the patient's belt, Fig.13 - shows the charts of falls and daily activity recorded with the inertia measurement module , placed on the patient's belt, Fig.14 - shows the algorithm for measuring the patient's pulse rate and blood pressure, Fig.15 - shows a graph with the principle of measuring the pulse wave propagation time, Fig.16 - shows a graph with the detection of the peak of the wave with the QRS complex, Fig.17 - shows a graph with the pulses from the pacemaker with a significant amplitude in the ECG record, Fig.18 - shows a graph with the application of pulse detection from the pacemaker and deleting them from the course, Fig.19 - shows an example of the course of the QRS complex detection function.

Example 1

The system for continuous monitoring of safety and basic vital functions of the patients as per the invention consists of fixed beacons RS located in the monitored rooms PMM of the nursing home DO (Fig.1 ), where the patients PD reside, who are provided with diagnostic bands OD worn on the wrist and with the fall detector DU placed on the hip belt (Fig.7) as well as medical personnel PM and doctors L equipped with personnel bands OP. In the isolated room, preferably in the medical duty office DL, there is a central beacon RC, connected by wired communication LP with the IT system monitoring centre ICMS. Diagnostic bands OD, fall detectors DU, personnel bands OP and fixed beacons RS enable the mutual bidirectional wireless communication LP via the radio modules MR installed in them, transferring measurement data via the central beacon to the IT system monitoring centre ICMS. Fixed beacons RS, made in the form of modules mounted in fixed locations established at the stage of mapping project of a monitored nursing home are connected to the 230 VAC mains power suppiy. i ne nxea Deacons RS are communicating wirelessly or via wired network, allowing for mutual transmission of data from the network terminals to the central beacon RC. Radio modules MR allow for the determination of the distance between the diagnostic band OD and the fall detector DU and the personnel band OP from the fixed beacons RS.

The fixed beacon RS (Fig.8) consists of the processor PRS connected to: radio module MRRS and two interfaces CAN1 and CAN2, enabling the distribution of the network in a mixed topology. Radio lines are placed in fixed places with known locations. The monitored area is within radio coverage in such a way that in each location the monitoring device, i.e. the diagnostic band OD, fall detector DU, and personnel band OP communicate with at least three radio beacons, which allows for triangulation of their location in the monitored rooms PMM. The fixed beacon RS is powered by a battery AKRS connected to the battery charging system ULRS connected to the converter block DC/DCRS, supplied with 24 V voltage.

The central beacon RC (Fig.9) consists of a processor PRC connected to: radio module MRRC and a USB interface allowing for the distribution of the network in a mixed topology. The central beacon unit RC is equipped with a 230 V power supply system and a converter block DC/DCRC.

Diagnostic band OD of the patients PD, which allows the following operations continuously or at time intervals given by the system: heart rate measurement, ambient temperature measurement - skin surface temperature measurement and ambient temperature measurement, estimation of arterial blood pressure and relative air humidity measurement. Diagnostic band OD (Fig.2 and Fig.3) is made in a form similar to a wrist watch, wherein in the upper outer plane of the casing OZ there is a display W and next to it, in an oval recession, an external electrode EZ is located with an external sensor of the wrist module for optical pulse wave measurement from finger ZMFT and the external proximity sensor ZCZ. On the side of the casing there is a control button PS for the control of the functions of the diagnostic band OD. In the lower plane of the casing OW of the diagnostic band OD, there is an internal electrode EW with an inner optical sensor of the wrist pulse measurement MT, an internal proximity sensor WCZ, as well as a skin temperature sensor MTS. A charging and communication connector USB is located next to it.

Diagnostic band OD of patients PD (Fig.4) consists of a processor P connected to: radio module MR, display W, inertia measurement module MB, ambient temperature measurement module MTO, moisture measurement module MW, charging and communication connector USB, internal capacitive proximity sensor WCZ, skin temperature measuring module MTS wrist optical pulse measurement module MT, con i

vibration motor SW, external electrode EZ, and internal electrode EW by wrist optical pulse measurement module MEKG, external optical sensor ZCO for pulse wave measurement, and external proximity sensor ZCZ. The charging and communication connector USB is connected in series with the battery charging system UL, the battery AK, and four converter blocks DC/DC. The radio module MR of the diagnostic band OD working in the frequency range from 3.244 GHz to 6.999 GHz, 500 MHz or 900 MHz bandwidth, and 1 10 kbps or 850 kbps or 6.8 Mbps bandwidth enables bidirectional communication from the fixed beacons RS and the determination of the position of the patient PD equipped with the diagnostic band PD in monitored rooms PMM.

An ambient temperature measurement module MTO with a measuring range of -30°C to 100X, accuracy ± 0.3°C, response time (τ 63%) 5 s measures the temperature around a patient PD with a diagnostic band OD and together with skin temperature measurement module MTS allows for the determination of changes in the temperature of the a patient PD.

The moisture measurement module MW with the measuring range from 0 to 100% RH and response time (τ 63%) 8 s measures the relative humidity in around the patient PD equipped with the diagnostic band OD. Setting the appropriate humidity thresholds allows to achieve an additional alert notifying the medical personnel PM whether the patient PD is staying outside the monitored facility or is, for example, in the bathroom.

The wrist optical pulse measurement module MT RED/IR LED type allows for continuous measurement of the pulse of the patient PD via the analysis of the blood flow through the blood vessels. This module, after putting on the diagnostic band OD by the patient PD.

The internal capacitive proximity sensor WCZ, located on the internal electrode EW, allows for signalling of the removal and putting on the diagnostic band OD by the patient PD.

An electrocardiographic diagnostic module MEKG with an input range of ± 300 mV, CMRR 1 15 dB, measurement noise 0.82 VRMS, sampling from 125 to 5 2 Hz, ADC 18 bits, with detection of R-R intervals has been applied.

The internal electrode EW is a measuring electrode connected to a one-lead electrocardiographic diagnostic module MEKG, which contacts the skin on the wrist of the hand on which the diagnostic band OD is worn. The buzzer B, vibration motor SW, and display W constitute the interface with the patient PD. Determining the pulse rate and calculating bloou pl easure is uaseu un measuring the time of pulse wave propagation TT from the heart to a selected location on the body, determining the pulse wave propagation rate PWV and calculating blood pressure BP on this basis using the formula (2).

Pulse wave propagation time TT is calculated as the time difference between the characteristic points on the ECG record and the pulse wave curve. The characteristic point in the ECG record is the peak of the wave R in the complex QRS, i.e. the fragment of the electrocardiographic record, which denotes the largest ECG waveform, while in the pulse curve it is the location with the fastest curve change or the zero crossing point. The principle of measuring the pulse wave propagation time TT is shown in Fig.15. In determining the position of complexes QRS in the ECG record an algorithm based on the so-called detection function has been applied, which provides optimal detection performance, immunity to interference, and the ability to work in online mode. Detecting the peak of the wave R with the complex QRS is shown in Fig.16. The ECG curve, especially in cases of disease, is characterized by significant variability, therefore for the analysis of the heart rhythm and determining the HR heart rate, only the so-called normal or dominant contractions are selected. An additional problem is caused by contractions stimulated by the implanted cardiac pacemaker, when stimulus pulses of considerable amplitude appear in the ECG record, as shown in Fig.17. The device as per the invention uses pulse detection from the pacemaker and deletes them from the curve as is shown in Fig.18. The device uses detection of typical contractions of ventricular origin and rejects them from further analysis.

The algorithm for detection of complexes QRS (Fig.14) consists of several successive operations performed on the signal to determine the course of the so-called detection function that has a clear, easy-to-find maximum at the location of the complex QRS occurrence.

The next steps in determining the detection function are:

- fine-tuned filtration (band-pass),

- non-linear operation (module or ^Λ 2),

- low-pass filtration (smoothing),

- searching for a maximum above a certain threshold,

- determination of R-R intervals.

An example curve of the detection function of the complex QRS is shown in Fig.19, where a sampling frequency of 500 Hz was adopted.

Due to the variability of individual ECG curves, the initial threshold is determined separately for each patient and possibly modified later. This is done in the initial part of the record, up to a few seconds long. The first three steps of the algorithm are carried out and the maxin. „„.

The initial threshold value is a fraction (usually 50-70%) of the value (or averaged value) of found maxima. In case of longer records, the threshold value can be modified with the current value of the detected maximum.

The problem of detecting impulses from the pacemaker in the device was solved during the attempt to simultaneously detect complexes QRS and pulses from the pacemaker while comparing the amplitudes of responses from the two algorithms. Depending on the ratio of these amplitudes, a decision is made to detect or not to detect pulses from the pacemaker. In case of choosing detection, fragments with pacemaker pulses are removed from the course, and the detection of complexes QRS is repeated. Pacemaker pulse detection is based on a similar algorithm, although the filter parameters and thresholds are different (matched to pacemaker pulses).

The subsequent steps of this algorithm are:

- fine-tuned filtration (band-pass),

- non-linear operation (module or ^Λ 2),

- low-pass filtration (smoothing),

- searching for a maximum above a certain threshold,

- replacement of the fragment with a pulse from the pacemaker with a linear course with an adequate slope,

- repeating the detection of complexes QRS using the modified signal

The pulse detector in the form of an external wrist optical pulse wave measurement with a finger module ZMFT works on the basis of detection of a location where the change of the curve is the fastest. An alternative approach is to look for the zero crossing point of a falling (or rising) pulse signal fragment. Due to the fact that the heartbeat signal is sampled at several times lower frequency, to obtain a smooth instead of a stepped course, tailored band pass filtering is used to remove the slow-changing component and approximation (smoothing) of the curve is applied. The device uses the determination of the zero crossing point for the falling fragment of the filtered pulse signal. The times corresponding to passages of the pulse signal through the zero are recorded.

When determining the pulse wave propagation time TT in the first stage of the algorithm, it is important to determine the pairs of RR (i) and PP (i), such that for all RR (i) < PP (i), i.e. that the ECG course precedes the pulse course. Subsequently TT (i) = PP (i) - RR (i) are calculated and averaged.

TT = average [TT (i)]

In turn, when determining the rate of PWV pulse wave propagation PWV = k ^* H / TT (1) where:

k=0.5 for hand pulse measurement,

H - increase in [cm]

TT - pulse wave propagation time (Transit Time) in [ms]

The current blood pressure value is determined by the formula (2)

ΒΡ _Ρπ = P1 ^* PWV ^* exp(P3 ^* PVW) + P2 ^* (PWV) ^P4 + (BPPTTcai - BPcai) (2) where:

P1 =700

P2=766000

P3=-1

P4=9

BPPTT - calculated pressure value in [mmHg]

BPPTTcai - calculated reference pressure value in [mmHg]

BPcal - measured value of reference pressure in [mmHg]

PWV- calculated value of pulse wave velocity (Pulse Waive Velocity) in [cm / s]

To take into account the individual characteristics of the studied patient, a calibration is performed by measuring the pressure with a classical method, while the changes of the pulse wave propagation velocity are used to calculate (estimate) the changes of pressure.

Diagnostic band OD transmits the measurement data wirelessly in a continuous manner and/or at time intervals set by the system. The measurement data is sent to the IT system monitoring centre ICMS via the fixed beacon RS network. Electronic systems are powered by the internal battery AK. The time of operation between battery charging AK is at least 24 hours, although it depends on the frequency of measurements and the frequency of data being transferred to the system. The battery charging system UL provides a message appearing in the IT system monitoring centre ICMS concerning the low battery voltage level, the internal capacitive proximity sensor WCZ provides a a message about the removal of the diagnostic band OD, the inertia measurement module MB estimates physical activity, and each diagnostic band OD has a unique identification number allowing for identification of each patient PD. The fall detector DU worn on the hip belt o† the patient PD (Ng.e), which is used to detect the fall event of the patient PD and automatically send an alarm signal to the medical personnel PM as well as to measure movement activities, e.g. to count steps.

The fall detector DU (Fig.6) consists of a processor P _u which is connected to: radio module MR _U , inertia measurement module MB _U , charging and communication connector USB _U , control button PSu, buzzer B _u and a vibration motor SWu. The charging and communication connector USBu is connected in series with the battery charging system UL _U , the battery AK _U , and four converter blocks DC/DC _U . The battery charging system ULu provides a message appearing in the IT system monitoring centre ICMS concerning the low battery voltage level, in addition each fall detector DU has a unique identification number allowing for the identification of each patient PD. The Inertia measurement module MB _U (Fig.10) consists of a digital block for processing signals, calibration, compensation, and change of orientation BPSK, to which an accelerometer ACC (XYZ) is connected via an analogue- to-digital converter ADCA, while a gyroscope ZYR (XYZ) is connected via an analogue-to-digital converter ADC _Z . The analogue-to-digital converters ADCa and ADCz are connected to the quartz oscillator OSC generating measurement cycles. Fall detection is indicated by sound and a message appearing in the IT system monitoring centre ICMS. With the use of the control button PSu, the patient PD can disable a false alarm. In the inertia measurement module MB _U , a gyroscope ZYR (XYZ) for measuring of angular acceleration was used, which was also one of the sources of data for the fall detection algorithm. The gyroscope ZYR (XYZ) was placed in the casing of a small MEMS (MicroElectroMechanical System) electromechanical sensor. It is built of microscopic tiles that vibrate with altitude change, and due to the sensors placed in it, it is possible to determine its relative position. The gyroscope ZYR (XYZ) used is able to measure angular acceleration in 3 axes in the ranges from ±245 - ±2000 deg/sec (dps - degree per second). For the lowest range, this gives a resolution of 8.75 mdps/digit, and for the highest, 70.00 mdps/digit. In case of the inertia measurement module MB _U , the sampling frequency is 10 Hz.

The used accelerometer ACC (XYZ) measures the linear or angular acceleration. Linear acceleration was used as one of the input parameters for the fall detection algorithm. The main element of the accelerometer is inert mass, suspended on elastic beams, constituting a part of the capacitor. When changing the position of the beam, the capacity changes thus causing a change in the output voltage which also serves as the input information for further processing.

The used accelerometer ACC (XYZ) measures linear acceleration in 3 axes in ranges from ±2g - ±16g. For the lowest range, this gives a working resolution 0.061 mg/LSB, and for the highest a reso

typical current consumption is 300μΑ for a sampling frequency of 50Hz and 1 μΑ for standby. In case of the inertia measurement module MB _U , the sampling frequency is 10 Hz.

The correct operation of the fall detector DU was preceded by a series of tests to optimally calibrate the axes of the accelerometer and gyroscope - determining the appropriate directions for individual axes so that the device base located on the patient's belt pointed to the '∑ axis with an acceleration of 1 g, the axis indicated a positive acceleration at left turn, and the 'X' axis indicated a positive acceleration when the patient leaned back, which optimizes the increase of resistance to false fall detection and greater effectiveness during the detection of fall.

Fig.11 . shows the initialization of the algorithm in the aspect of setting zero values for individual variables, for the correct operation of the algorithm

1.1 . Collecting data for the accelerometer and gyroscope - sampling data at the appropriate frequency and scaling

1.1.1 .

a Filtration of data from the accelerometer and gyroscope - filtration of data with a high-pass filter, a Butterworth filter of the 3rd order, and a cut-off frequency equal to 1.5 Hz b Calculation of the acceleration vector - calculation of acceleration vectors for filtered data from the accelerometer and gyroscope according to the function accelVector= ^" ^ ² + y ² + z ²

1.1 .2.

a Data filtration using inertia! filter - filtration of data from the linear acceleration on the 'X' axis with the first degree inertial filter with a time constant equal to 0.8 seconds

1.2. Record of filtered data - record of data from the accelerometer and gyroscope filtered by the high-pass filter and data for the X axis filtered by the inertial filter

1.3. Checking the availability of adequate amount of data - checking whether the data from the last 3 minutes has already been collected in the device's memory

1 :4. Threshold of the lying position exceeded? - checking if the threshold for data on the X axis of linear acceleration has been exceeded. This threshold can be modified in a very simple manner, so as the device matches the needs of a selected age group of patients

1.5. Find the maximal difference - seeking the maximal difference for data from the accelerometer and gyroscope

1.6. Calculate the probability - calculates the probability of the largest differences found for accelerometer and gyroscope data from the last 3 minutes 1.7. Multiply the probabilities by the weignis - mumpues ine calculated probabilities. By weight, the sum of which is 1

1.8. Sum up probabilities from the accelerometer and gyroscope - sums the calculated probabilities, scaled by individual weights

1.9. Delete the oldest data set - deletes the oldest set of data stored in the memory

1.10. The threshold of falling has been exceeded? - checks whether the threshold for falling from the calculated probability has been exceeded

1 .1 1. Fall detected - the fall has been detected, information is sent to the user.

In order to determine the threshold values ensuring the proper operation of the fall detector DU, a series of tests was carried out for various motor activities of patients PD, including falls. The sample data is presented in diagrams showing registry of various motor activities, including falls. On the right-hand side of the graphs there is a legend describing the displayed data pertaining to: resAcc - fall probability for data recorded by the accelerometer (linear acceleration) before multiplication by the appropriate weight for this parameter

resGyro - fall probability for data recorded by the gyroscope (angular acceleration) before being multiplied by the weight for this parameter

resFall - probability with which the patient fell (to facilitate the analysis, it is displayed only when the LayTHLD fall detection threshold is exceeded)

LayTHLD - probability threshold using which the device detects the fall (if resFall is greater than or equal to the threshold, the fall is registered and the user is informed about it)

accZ - Linear acceleration measured in the '∑' axis, filtered through a 1st degree inertial filter. If the values go below 0.6g, the algorithm starts analysing the remaining data (acceleration vectors from the accelerometer and gyroscope); in other cases the data are not analysed.

Where Fig.12 shows the diagrams of daily activity recorded with the inertia measurement module MB located on the patient's PO belt, Fig.13 - shows the falls and daily activity graphs recorded with the inertia measurement module MB located on the patient's PO belt.

As a result of a number of tests and experiments, it was decided that the inertia measurement module MB installed in the diagnostic band OD of the patient and the inertia measurement module MB _P installed in the band of medical personnel OP, located on the wrist, will register the movement activity, while the fall detector DU located on the paueni s ru Deit wnicn win detect and signal the patient's fall.

The experiments have shown that the inertia measurement module MB is able to detect falls while being worn on the wrist, however, excessive physical activity when placing inertia measurement module MB on the wrist indicates the need to put it on the belt, which allows to limit false fall detections to a minimum and ensure greater fall detection efficiency.

Another device of the system as per the invention is the medical personnel band OP (Fig.5), which is used to receive alarms by the medical personnel PM and/or doctors L and to facilitate localisation of patients PD in monitored rooms PMM for immediate assistance. The band of the medical personnel OP enables the patient PD to be informed about the alarm and for them to confirm its occurrence. The medical personnel band OP is made in a form similar to that of the diagnostic band OD and has the form of a wrist watch with a display W _P located in the upper external plane of the casing. On the side of the casing there is the control button PS _P responsible for the functions of the medical personnel band OP. In the lower plane of the casing of the medical personnel band OP, there is the internal electrode EW _P of the band, with the internal proximity sensor WCZ _P . A charging and communication connector USB _P is located next to it. The arrangement of the medical personnel band OP (Fig.5) consists of a processor P _P , connected to: radio module MR _P , display W _P , inertia measurement module MB _P , charging and communication connector USB _P , internal capacitive proximity sensor WCZ , control button PS , buzzer Bp and vibration motor SW _P . The charging and communication connector USB _P is connected in series with the battery charging system UL _P , the battery AK _P , and four converter blocks DC/DC _P . The medical personnel band OP system provides information to the IT system monitoring centre ICMS about low battery AK _P voltage level and the fact that the patient's PD band is removed, as detected by the internal capacitive proximity sensor WCZ _P .

In addition, the physical activity of the medical personnel OP is estimated via the signals from inertia measurement module MB _P , and each band has a unique identification number enabling the identification of medical personnel PM.

The system as per the invention, assisted and controlled by the IT system, enables practical and optional use of individual devices in the form of a diagnostic band OD, fall detector DU and personnel band OP for providing coordinated monitoring of patients PD in the monitored rooms PMM of the nursing home DO. The main task of the IT system monitoring centre ICMS is receiving the measurement data from the diagnostic bands OD, associating the data with System Users, and subsequently introducing the data into a virtual System User file index. The medical personnel win nave access 10 the index and will be able to manage diagnostic bands OD, view system statistics, and generate reports on the system operation. Medical personnel will have access to a common IT system, which significantly speeds up and organises the exchange of information. The data collected in the system regarding the users and their activities recorded by the bands is made available to the medical personnel through the IT system. The system also enables the management of collected data in terms of personal data protection.

The system for continuous monitoring of safety and basic vital functions of the patients as per the invention enables:

The presentation of the measurement data for selected diagnostic bands OD,

The archiving of measurement data for all diagnostic bands OD,

The review of historical data in specified time periods of 7 days,

Setting up threshold values for individual measured parameters, individually for each diagnostic band OD,

Tracking changes in threshold values for individual diagnostic bands OD,

Sending alarms after exceeding the threshold values to the nearest personnel band OP,

Presentation of currently exceeded threshold values and presentation of notifications confirmed by medical personnel PM and/or a doctor L along archiving thereof,

Presentation of current location data of selected diagnostic bands OD and selected personnel bands OP along archiving thereof,

Ability to set measurement intervals and communication intervals for diagnostic bands OD and selected personnel bands OP,

Ability to link the identification code of the diagnostic bands OD and the identification codes of the fall detector DU with individual patients PD,

Viewing historical location data of diagnostic bands OD and personnel bands OP,

The possibility to select active alarms for a given diagnostic band OD. Example 2

In the method as per the invention, the designated object is within the radio coverage of the beacon RD network in such a way that the diagnostic band OD and the fall detector DU located on the hip belt, provided for each patient PD, communicates with at least three beacons RD in every part of the monitored rooms PMM. This way the continuous monitoring of the whereabouts of patients PD in monitored rooms PMM is carried out via the central beacon RC and the IT system monitoring centre ICMS by providing current information to medical personnel PM equipped with bands OP. In the event of an alarm signal triggered by the fall of a patient PD being sent by the fall detector DU and/or the signal sent by the diagnostic band OD concerning exceeding the threshold values of measured blood pressure parameters, pulse, the patient's PD body temperature, or ambient humidity change signal, or concerning the circumstance of leaving the facility by the patient PD, the action to provide assistance is commenced.

The electrocardiographic diagnostic module MEKG with R-R interval detection allows for the determination of the first bipolar Einthoven limb lead and the determination of R-R and time of occurrence of complex QRS. The first bipolar Einthoven limb lead is determined via the external electrode EZ, which is touched by the finger of the patient's PD hand without the diagnostic band OD attached, and via the internal electrode EW, which is in direct and constant contact with the wrist of the hand on which the diagnostic band OD is worn.