CROSS-REFERENCE TO RELATED PATENT APPLICATIONS

[0001] This application claims priority to U.S. Provisional Patent Application Serial No. 62/979,333, entitled “SINGLE-LAYERED ULTRA-SOFT WASHABLE SMART TEXTILES FOR ALL-AROUND PHYSIOLOGICAL MONITORING DURING SLEEP,” filed February 20, 2020, the contents of such application being hereby incorporated by reference in its entirety and for all purposes as if completely and fully set forth herein.

TECHNICAL FIELD

[0002] The present implementations relate generally to biometric sensors, and more particularly to a textile-based sensor for managing cardiopulmonary activity.

BACKGROUND

[0003] Sleep is considered to be the cornerstone for maintaining both physical and mental health. However, nearly one billion people worldwide suffer from various sleep disorders. Conventional systems may not effectively meet needs for noninvasively achieving high sensitivity, multi-parameter monitoring and comfort.

SUMMARY

[0004] It is advantageous to implement a single-layered ultra-soft smart textile supporting monitoring of and corresponding healthcare responses to physiological parameters monitored during sleep, rest, or the like. A single-layered ultra-soft smart textile can advantageously detect, monitor, and respond to dynamic sleeping postures and cardiopulmonary activity. In addition, noninvasive monitoring of respiration and heartbeat activity of a person can be achieved. It is further advantageous to detect an obstructive sleep apnea-hypopnea syndrome (OSAHS) condition, and to intervene in response to detecting the OSAHS condition to improve sleep quality and prevent sudden death during sleep. Thus, a technological solution for a textile-based sensor for managing cardiopulmonary activity is desired.

[0005] Example implementations include a biometric sensor device with a textile sheet, a nonconductive sleeve having a substantially cylindrical shape and a hollow portion in an axial direction thereof, and at least partially affixed to the textile sheet, and a conductive core having a substantially cylindrical shape and disposed at least partially within the hollow portion of the nonconductive sleeve.

[0006] Example implementations further include a device with one or more nonconductive fibers disposed substantially helically around the conductive core in an axial direction thereof, and disposed at least partially within the hollow portion of the nonconductive sleeve.

[0007] Example implementations also include a biometric sensor device with a textile sheet region including a plurality of sensor regions, a plurality of nonconductive sleeves each having a substantially cylindrical shape and a hollow portion in an axial direction thereof, and at least partially affixed to a corresponding one of the sensor regions, and a plurality of conductive cores each having a substantially cylindrical shape and disposed at least partially within a corresponding hollow portion of a corresponding one of the nonconductive sleeves.

[0008] Example implementations further include a device with a plurality of sets of one or more nonconductive fibers each disposed substantially helically around a corresponding one of the conductive cores in an axial direction thereof, and each disposed at least partially within the corresponding hollow portion of the corresponding one of the nonconductive sleeves. [0009] Example implementations also include a method of detecting a physiological response, by deforming a substantially cylindrical sensor unit in a substantially radial direction thereof, inducing a friction contact between a nonconductive sleeve of the sensor unit and one or more nonconductive fibers disposed at least partially within a hollow portion of the nonconductive sleeve in response to the deforming, generating an electrical response at a substantially cylindrical conductive core of the sensor unit in response to the increasing friction contact, generating at least one respiratory signal based on the electrical response, and generating at least one heartbeat signal based on the electrical response.

[0010] Example implementations further include a method including generating a body position based on the position grid, classifying the body position into a sleep position, and in response to a determination that the sleep position corresponds to a predetermined body position and the respiratory signal corresponds a predetermined respiratory state, generating an emergency response.

BRIEF DESCRIPTION OF THE DRAWINGS

[0011] These and other aspects and features of the present implementations will become apparent to those ordinarily skilled in the art upon review of the following description of specific implementations in conjunction with the accompanying figures, wherein: [0012] Fig. 1 illustrates an example system, in accordance with present implementations. [0013] Fig. 2 illustrates an example system in a first example activation state, in accordance with present implementations.

[0014] Fig. 3 illustrates an example system including a plurality of example devices, in accordance with present implementations.

[0015] Fig. 4 illustrates an example device, in accordance with present implementations. [0016] Fig. 5A illustrates an example device in a an example first state, in accordance with present implementations.

[0017] Fig. 5B illustrates an example device in an example second state, in accordance with present implementations.

[0018] Fig. 5C illustrates an example device in an example third state, in accordance with present implementations.

[0019] Fig. 5D illustrates an example device in an example fourth state, in accordance with present implementations.

[0020] Fig. 6 illustrates an example electronic system, in accordance with present implementations.

[0021] Fig. 7 illustrates an example waveform diagram including example waveforms each associated with a corresponding cardiopulmonary state, in accordance with present implementations.

[0022] Fig. 8 illustrates an example waveform diagram including an example respiratory waveform, in accordance with present implementations.

[0023] Fig. 9 illustrates an example waveform diagram including an example heartbeat waveform, in accordance with present implementations.

[0024] Fig. 10 illustrates an example waveform diagram including an example respiratory rate waveform and an example heartbeat rate waveform, in accordance with present implementations.

[0025] Fig. 11 illustrates an example method of managing cardiopulmonary activity, in accordance with present implementations.

[0026] Fig. 12 illustrates an example method of managing cardiopulmonary activity further to the example method of Fig. 11.

[0027] Fig. 13 illustrates an example method of managing cardiopulmonary activity further to the example method of Fig. 12. [0028] Fig. 14 illustrates a further example method of managing cardiopulmonary activity, in accordance with present implementations.

[0029] Fig. 15 illustrates a further example method of managing cardiopulmonary activity further to the example method of Fig. 14.

DETAILED DESCRIPTION

[0030] The present implementations will now be described in detail with reference to the drawings, which are provided as illustrative examples of the implementations so as to enable those skilled in the art to practice the implementations and alternatives apparent to those skilled in the art. Notably, the figures and examples below are not meant to limit the scope of the present implementations to a single implementation, but other implementations are possible by way of interchange of some or all of the described or illustrated elements. Moreover, where certain elements of the present implementations can be partially or fully implemented using known components, only those portions of such known components that are necessary for an understanding of the present implementations will be described, and detailed descriptions of other portions of such known components will be omitted so as not to obscure the present implementations. Implementations described as being implemented in software should not be limited thereto, but can include implementations implemented in hardware, or combinations of software and hardware, and vice-versa, as will be apparent to those skilled in the art, unless otherwise specified herein. In the present specification, an implementation showing a singular component should not be considered limiting; rather, the present disclosure is intended to encompass other implementations including a plurality of the same component, and vice-versa, unless explicitly stated otherwise herein. Moreover, applicants do not intend for any term in the specification or claims to be ascribed an uncommon or special meaning unless explicitly set forth as such. Further, the present implementations encompass present and future known equivalents to the known components referred to herein by way of illustration.

[0031] Example implementations include a single-layered and ultra-soft smart textile-based sensor device fabricated from washable functional fibers. The textile-based sensor device can continuously monitor cardiopulmonary states associated with sleep, and provide input to an intervention system relevant to sleep-related diseases. In some implementations, functional fibers are constructed via enwrapping an inner core of twisted conductive yarn with an outer sheath of ultra-thin silicone fiber. Due to high flexibility and ultra-fine diameter corresponding to or exceeding that of textile fibers, the functional fibers can also be easily woven into a fabric textile, to maintain both decent tactile sensations and aesthetical appearance. As one example, a fabric textile can include a household bed sheet.

[0032] In some implementations, a textile-based sensor device shows an example sensitivity of 10.79 mV/Pa over 20,000 press-release cycles, an example wide working frequency bandwidth ranging from 0 Hz to 40 Hz, high mechanical stability, and washing durability under, for example, weekly machine washing. In some implementations, textile-based sensor device integrates real-time dynamic sleeping posture detection and tracking, respiratory signal monitoring, and ballistocardiograph (BCG) signal monitoring. Thus, in some implementations, the single-layered ultra-soft smart textiles provides real-time warning responses and corresponding safety intervention communication to prevent apparent sudden onset of illness during sleep. It is to be understood that an ultra-soft, highly-sensitive, washable, versatile textile-based sensor device in accordance with present implementations can provide a comfortable and non-invasive means of real-time sleep monitoring. It is to be further understood that the textile-based sensor device can be operable in both household and clinical healthcare systems, but is not limited thereto.

[0033] Fig. 1 illustrates an example system, in accordance with present implementations. As illustrated by way of example in Fig. 1, an example system 100 includes a textile-based sensor fabric 110 including a plurality of textile-based sensor regions 400, on which a person 120 can lie, sit, or the like in various positions.

[0034] The textile-based sensor fabric 110 is or includes one or more textile sheets operable to generate an electrical charge in response to physical contact. In some implementations, the textile-based sensor fabric 110 has a length and width corresponding to a fabric sheet, bedding, bedsheet, or the like, on which the person 120 can sit, lie, or the like. In some implementations, the textile-based sensor fabric 110 can detect a body position of the person 120 in accordance with a prone position, a supine position as illustrated by way of example in Fig. 1, or the like. In some implementations, the textile-based sensor fabric 110 includes a plurality of independent textile-based sensor regions 400. As one example, the textile-based sensor fabric 110 can include 61 independent textile-based sensor regions 400, in which 60 textile-based sensor regions 400 each having a size of 10 cm by 13 cm are evenly distributed throughout the whole sleeping area for body movement detection, and 1 textile-based sensor region 400 having a size of 7 cm by 52 cm is located proximate to and substantially under the chest region of the person 120 for physiological signal monitoring located under the chest region. It is to be understood that the textile-based sensor fabric 110 can include any arbitrary number of textile- based sensor regions 400 arranged in any arbitrary configuration associated with or associable with the person 120. In some implementations, the textile-based sensor fabric 110 corresponds in at least one of size and thickness to a textile cotton bedsheet. In some implementations, the textile-based sensor fabric 110 is or includes a textile sheet. As one example, the textile sheet can be but is not limited to a cotton bedsheet. It is to be understood that the person 120 is of arbitrary height, weight, background, gender, or the like, and that the person 120 can also correspond to any living organism or representation of a living organism with cardiopulmonary activity corresponding to or analogous to human cardiopulmonary activity.

[0035] Fig. 2 illustrates an example system in a first example activation state, in accordance with present implementations. As illustrated by way of example in Fig. 2, an example system 200 in a first example activation state includes the textile-based sensor fabric 110, the textile- based sensor regions 400, and a body position activation region 210.

[0036] The body position activation region 210 corresponds to portions of the textile-based sensor fabric 110 in significant pressure contact with the person 120. As one example, the body position activation region 210 corresponds to contact with the person 120 lying on the textile-based sensor fabric 110 in a supine, prone, or like position. In some implementations, a significant pressure contact is a pressure contact exceeding a threshold pressure necessary to generate an electrical charge or change in electrical charge at a corresponding one of the textile-based sensor regions 400. As one example, the body position activation region 210 corresponds to a supine position in which a head of the person 120 is located proximate to the left of the textile-based sensor fabric 110, and the feet are located proximate to the right of the textile-based sensor fabric 110.

[0037] In some implementations, the textile-based sensor fabric 110 is arranged in a grid by rows i 202 and columns j 204. In some implementations, by sequentially scanning through a plurality of the textile-based sensor regions 400, a computing system operatively coupled to the textile-based sensor fabric 110 creates a binary image of the entire smart textile that represents a pressure distribution of the person 120 on the textile-based sensor fabric 110. In some implementations, the computing system also receives dynamic input from the textile- based sensor fabric 110 to recognize and record body movement. As one example, person 120 can initially lie on the textile-based sensor fabric 110 in a supine position before turning to a left lateral position. Concurrently, a computing system including a display interface can present and record sleep position changes. In this example the computing system can present and record sleep position changes including the number of times the person 120 turns over, gets up, or the like, during a predetermined sleep period. It is to be understood that a sleep period can be a predetermined period of time, can begin or end based on a predetermined pressure or cardiopulmonary state, or the like.

[0038] Fig. 3 illustrates an example system including a plurality of example devices, in accordance with present implementations. As illustrated by way of example in Fig. 3, an example system 300 includes the textile-based sensor fabric 110, the textile-based sensor regions 400, a plurality of sensor leads 310, a sensor bus 320, and a cardiopulmonary textile- based sensor region 330.

[0039] The sensor leads 310 include one or more conductive wires operable to transmit one or more electrical responses to the sensor bus. In some implementations, the sensor leads 310 include at least one metallic cylindrical core at least partially surrounded by nonconductive material. In some implementations, the nonconductive material includes polymer, fiber, or the like. In some implementations, the nonconductive material is nonresponsive to triboelectric charge. In some implementations, the sensor leads 310 operatively couple the sensor bus 320 to a corresponding one of the textile-based sensor regions 400 or the cardiopulmonary textile- based sensor region 330.

[0040] The sensor bus 320 is operable to communicatively couple the textile-based sensor fabric 110 to an electronic signal processing system. In some implementations, signals generated from each of the textile-based sensor regions 400 or the cardiopulmonary textile- based sensor region 330 are electrically connected and individually addressable to an electronic signal processing system. In some implementations, the sensor bus thus aggregates analog output from each of the textile-based sensor regions 400 or the cardiopulmonary textile-based sensor region 330 to express a sleeping posture and subtle physiological signals of a person 120 in contact with the textile-based sensor fabric 110. In some implementations, the sensor bus 320 is operable to communicate one or more instructions, signals, conditions, states, or the like from one or more of the textile-based sensor fabric 110 and an electronic signal processing system. In some implementations, the sensor bus 320 includes one or more analog communication channels, lines, traces, or the like.

[0041] The cardiopulmonary textile-based sensor region 330 corresponds in structure and operation to the textile-based sensor regions 400, and is operable to detect one or more cardiopulmonary responses from the person 120. In some implementations, the cardiopulmonary textile-based sensor region 330 is oriented proximate to a cardiopulmonary system of the person 120, in order to be deformable by pressure contact caused by respiration and heartbeat activity of the person 120. In some implementations, the cardiopulmonary textile-based sensor region 330 is disposed over a corresponding one of the textile-based sensor regions 400, where the cardiopulmonary textile-based sensor region 330 is dedicated to detecting cardiopulmonary activity, and the corresponding one of the textile-based sensor regions 400 is dedicated to detecting body pressure contact from the person 120. Thus, in some implementations, two sensor regions are co-located at the cardiopulmonary textile-based sensor region 330. It is to be understood that the cardiopulmonary textile-based sensor region 330 can include an arbitrary number of textile-based sensor regions 400, and is not limited to being disposed at one of the textile-based sensor regions 400.

[0042] Fig. 4 illustrates an example device, in accordance with present implementations. As illustrated by way of example in Fig. 4, an example textile-based sensor device 400 includes a corresponding one of the sensor leads 310 and a sensor unit 500.

[0043] The sensor unit 500 is integrably disposed in, on, or with the textile-based sensor region 400. In some implementations, the sensor unit 500 is integrated with, woven into, affixed to, or the like, a woven washable fiber or textile sheet in a substantially cylindrical shape formed into a serpentine structure across a planar surface of the textile-based sensor device 400. In some implementations, the sensor unit 500 has a diameter of approximately 1 mm. The textile- based sensor device 400 has an advantageous mechanical durability, including consistent operation without degradation after repetitive pressure application of 20,000 cycles. In some implementations, the textile-based sensor device 400 can continue operation substantially at a frequency of 1 Hz and a pressure of 2 kPa with substantially no performance degradation, after the repetitive pressure application.

[0044] Figs. 5A-D illustrate an example sensor unit 500A-D in cross-section view and under varying levels of pressure application causing varying levels of deformation 502A-D of the sensor unit 500A-D. In some implementations, the sensor unit 500 is washable due to a functional fiber with a sheath-core structure. This structure includes a hollow nonconductive sleeve 530A-D at least partially encapsulating a conductive fiber as the inner core. In some implementations, the nonconductive sleeve 530A-D has a substantially cylindrical shape with an inner diameter of approximately 0.5 mm and an outer diameter of approximately 1 mm. In some implementations, the nonconductive sleeve 530A-D is or includes silicone or the like. In some implementations, the conductive fiber includes a substantially cylindrical conductive core 510A-D including one or more nonconductive fibers 520A-D disposed at least partially surrounding the conductive core 510A-D substantially helically and in contact therewith. In some implementations, the nonconductive fibers 520A-D are or include polyester. It is to be understood that sensor unit 500A-D can be made of economically low-cost materials and constructed by scalable fabrication technologies, further reducing cost. It is to be further understood that the flexibility and size of the sensor unit 500A-D allow it to be woven into textiles in various arrangements, woven patterns, and the like, to preserve its functionality while allowing aesthetic customizability. The sensor unit 500A-D can also advantageously withstand twisting, folding, and harsh deformation in a manner corresponding to nondestructive twisting, folding and deformations applicable to textile fabrics. In some implementations, sensing performance of the sensor unit 500A-D is stable under perspiration and high humidity conditions, due to the insulation of the conductive fiber from the ambient environment by the nonconductive sleeve 530A-D.

[0045] The washable functional fiber can convert pressure changes into electrical signals through one or more of triboelectrification and electrostatic induction. Before the nonconductive sleeve 530A-D makes contact with the nonconductive fibers 520A-D, electron transfer is prevented via local trapping effects within either material. When the two materials come into contact induced by the biomechanical signals from human body, the electron clouds of two materials overlap, the initial single well potential becomes a double well potential, and the electrons transfer, for example, from silicone to polyester. Therefore, positive and negative charges are produced on the silicone rubber and polyester surfaces, respectively. When the pressure is released, the two materials are separated from each other due to the elasticity of the silicone rubber. As a result, an electrical potential is built up between the two materials, driving electrons from the electrode to the ground.

[0046] Fig. 5A illustrates an example device in an example first state, in accordance with present implementations. As illustrated by way of example in Fig. 5A, an example device 500A includes a conductive core 510A having a first core charge state, a plurality of nonconductive fibers 520A having a first fiber charge state, and a nonconductive sleeve 530A having a first sleeve charge state. In some implementations, the example device 500A includes a first radial displacement state 502A, a first triboelectric voltage state 504A, and a first triboelectric current state 506A.

[0047] The conductive core 510A having a first core charge state is disposed in contact with the nonconductive fibers 520A and without substantial friction contact with the nonconductive sleeve 530A. In some implementations, the first core charge state corresponds to a first positive charge state of the conductive core 510A. The nonconductive fibers 520 A having a first fiber charge state are disposed in contact with the nonconductive fibers 520A and without substantial friction contact with the nonconductive sleeve 530A. In some implementations, the first fiber charge state corresponds to a first negative charge state of the nonconductive fibers 520A. The nonconductive sleeve 530A having a first sleeve charge state is in a substantially undeformed state in the absence of application of substantial pressure by a person 120.

[0048] The first radial displacement state 502A corresponds to a substantially undeformed state of the nonconductive sleeve 530A, and corresponds to a largest diameter of the nonconductive sleeve 530A in a radial direction corresponding to the application of pressure to the sensor unit 500A. In response to the first radial displacement state 502A, the first triboelectric voltage state 504A corresponds to a reference voltage difference between the conductive core 510A and the nonconductive sleeve 530A. Similarly, the first triboelectric current state 506A corresponds to a relative minimum or absent current flow between the conductive core 510A and the nonconductive sleeve 530A.

[0049] Fig. 5B illustrates an example device in an example second state, in accordance with present implementations. As illustrated by way of example in Fig. 5B, an example device 500B includes a conductive core 510B having a second core charge state, a plurality of nonconductive fibers 520B having the first fiber charge state, and a nonconductive sleeve 530B having a second sleeve charge state. In some implementations, the example device 500B includes a second radial displacement state 502B, a second triboelectric voltage state 504B, and a second triboelectric current state 506B.

[0050] The conductive core 510B having a second core charge state is disposed in contact with the nonconductive fibers 520B and with increasing friction contact with the nonconductive sleeve 530B. In some implementations, the second core charge state corresponds to a second positive charge state of the conductive core 510B less than the first positive charge state. The nonconductive fibers 520B having a second fiber charge state are disposed in contact with the nonconductive fibers 520B and with increasing friction contact with the nonconductive sleeve 530B. In some implementations, the second fiber charge state corresponds to a first negative charge state of the nonconductive fibers 520B. The nonconductive sleeve 530B having a second sleeve charge state is in an increasingly deformed state in the presence of increasing application of pressure by a person 120.

[0051] The second radial displacement state 502B corresponds to an increasingly deformed state of the nonconductive sleeve 530B, and corresponds to a decreasing diameter of the nonconductive sleeve 530B in a radial direction corresponding to the application of pressure to the sensor unit 500B. In response to the second radial displacement state 502B, the second triboelectric voltage state 504B corresponds to a negative voltage difference from the conductive core 510B to the nonconductive sleeve 530B. Similarly, the second triboelectric current state 506B corresponds to a negative current flow from the conductive core 51 OB to the nonconductive sleeve 53 OB.

[0052] Fig. 5C illustrates an example device in an example third state, in accordance with present implementations. As illustrated by way of example in Fig. 5C, an example device 500C includes a conductive core 5 IOC having a third core charge state, a plurality of nonconductive fibers 520C having the first fiber charge state, and a nonconductive sleeve 530C having a third sleeve charge state. In some implementations, the example device 500C includes a third radial displacement state 502C, a third triboelectric voltage state 504C, and a third triboelectric current state 506C.

[0053] The conductive core 5 IOC having a third core charge state is disposed in contact with the nonconductive fibers 520C and with maximum friction contact with the nonconductive sleeve 530C. In some implementations, the third core charge state corresponds to a first reference charge state of the conductive core 5 IOC. It is to be understood that that the first reference charge state is not limited to a zero voltage, and can correspond to any reference voltage at or corresponding to a voltage bound associated with the conductive core 5 IOC in the state 500C. The nonconductive fibers 520C having a third fiber charge state are disposed in contact with the nonconductive fibers 520C and with maximum substantial friction contact with the nonconductive sleeve 530C. In some implementations, the third fiber charge state corresponds to a first negative charge state of the nonconductive fibers 520C. The nonconductive sleeve 530C having a third sleeve charge state is in a maximally deformed state in the presence of application of maximum pressure by a person 120.

[0054] The third radial displacement state 502C corresponds to a maximally deformed state of the nonconductive sleeve 530C, and corresponds to a smallest diameter of the nonconductive sleeve 530C in a radial direction corresponding to the application of pressure to the sensor unit 500C. In response to the third radial displacement state 502C, the third triboelectric voltage state 504C corresponds to a positive voltage difference between the conductive core 5 IOC and the nonconductive sleeve 530C. Similarly, the third triboelectric current state 506C corresponds to a relative minimum or absent current flow between the conductive core 5 IOC and the nonconductive sleeve 530C. In some implementations, pressure sensitivity is greatest from 0 kPa to 2 kPa, at approximately 10.79 mV/Pa for example. In some implementations, higher pressure above 2 kPa, sensitivity is approximately 0.62 mV/Pa. In some implementations, increase of the external pressure beyond 2 kPa saturates the effective contact area and slows increase of the third triboelectric voltage state 504C.

[0055] Fig. 5D illustrates an example device in an example fourth state, in accordance with present implementations. As illustrated by way of example in Fig. 5D, an example device 500D includes a conductive core 510D having a fourth core charge state, a plurality of nonconductive fibers 520D having the first fiber charge state, and a nonconductive sleeve 530D having a fourth sleeve charge state. In some implementations, the example device 500D includes a fourth radial displacement state 502D, a fourth triboelectric voltage state 504D, and a fourth triboelectric current state 506D.

[0056] The conductive core 510D having a fourth core charge state is disposed in contact with the nonconductive fibers 520D and with decreasing friction contact with the nonconductive sleeve 530D. In some implementations, the fourth core charge state corresponds to a second positive charge state of the conductive core 510D less than the first positive charge state. The nonconductive fibers 520D having a fourth fiber charge state are disposed in contact with the nonconductive fibers 520D and with decreasing friction contact with the nonconductive sleeve 530D. In some implementations, the fourth fiber charge state corresponds to a first negative charge state of the nonconductive fibers 520D. The nonconductive sleeve 530D having a fourth sleeve charge state is in an decreasingly deformed state in the presence of decreasing application of pressure by a person 120. As one example, the decreasing application of pressure can be caused by the person 120 shifting body positions, sitting up, or the like.

[0057] The fourth radial displacement state 502D corresponds to an decreasingly deformed state of the nonconductive sleeve 530D, and corresponds to an increasing diameter of the nonconductive sleeve 530D in a radial direction corresponding to the application of pressure to the sensor unit 500D. In response to the fourth radial displacement state 502D, the fourth triboelectric voltage state 504D corresponds to a positive voltage difference from the conductive core 510D to the nonconductive sleeve 530D. Similarly, the fourth triboelectric current state 506D corresponds to a positive current flow from the conductive core 510D to the nonconductive sleeve 530D.

[0058] Fig. 6 illustrates an example electronic system, in accordance with present implementations. As illustrated by way of example in Fig. 6, an example electronic system 600 includes the textile-based sensor fabric 110, the sensor bus 320, a system processor 610, a sensor signal amplifier 620, a bandpass filter 630, a low-pass filter 640, an analog-to-digital converter 650, and a communication interface 660.

[0059] The system processor 610 is operable to execute one or more instructions associated with input from the sensor signal amplifier 620. In some implementations, the system processor 610 is an electronic processor, an integrated circuit, or the like including one or more of digital logic, analog logic, digital sensors, analog sensors, communication buses, volatile memory, nonvolatile memory, and the like. In some implementations, the system processor 610 includes but is not limited to, at least one microcontroller unit (MCU), microprocessor unit (MPU), central processing unit (CPU), graphics processing unit (GPU), physics processing unit (PPU), embedded controller (EC), or the like. In some implementations, the system processor 610 includes a memory operable to store or storing one or more instructions for operating components of the system processor 610 and operating components operably coupled to the system processor 610. In some implementations, the one or more instructions include at least one of firmware, software, hardware, operating systems, embedded operating systems, and the like. It is to be understood that the system processor 610 or the system 600 generally can include at least one communication bus controller to effect communication between the system processor 610 and the other elements of the system 610.

[0060] The sensor signal amplifier 620 operable to increase magnitude of the triboelectric voltage or other electrical response received from one or more of the sensor fibers. In some implementations, the sensor signal amplifier 620 is operatively coupled to the sensor bus 320 by a multiplexer or the like operable to sequentially cycle through one or more of the sensor regions 400 operatively coupled therewith. In some implementations, output voltage remains substantially constant while current gradually increases, yielding a clean signal throughout the working frequency range. In some implementations, the working frequency range is approximately 0 to 20Hz. The frequency response is advantageous to sleep monitoring, because the heartbeat signal during sleeping can commonly be in the frequency range of 0 to 20 Hz. Thus, in some implementations, the device reliably captures a heartbeat signal within a particular frequency range. In some implementations, the sensor signal amplifier 620 includes one or more logical or electronic devices including but not limited to integrated circuits, logic gates, flip flops, gate arrays, programmable gate arrays, and the like. It is to be understood that any electrical, electronic, or like devices, or components associated with the sensor signal amplifier 620 can also be associated with, integrated with, integrable with, replaced by, supplemented by, complemented by, or the like, the system processor 610 or any component thereof.

[0061] The bandpass filter 630 is operable to reduce or remove analog signal interference, environmental noise, or the like, from an amplified electrical response received from the sensor signal amplifier 520 to isolate heartbeat activity. In some implementations, the bandpass filter 630 isolates a frequency range associated with heartbeat activity and corresponding to a ballistocardiograph (BCG). In some implementations, the bandpass filter 630 isolates the BCG signal by filtering within a frequency range between approximately lHz and 22 Hz. In some implementations, the bandpass filter 630 includes one or more logical or electronic devices including but not limited to integrated circuits, logic gates, flip flops, gate arrays, programmable gate arrays, and the like. It is to be understood that any electrical, electronic, or like devices, or components associated with the bandpass filter 630 can also be associated with, integrated with, integrable with, replaced by, supplemented by, complemented by, or the like, the system processor 610 or any component thereof.

[0062] The low-pass filter 640 is operable to reduce or remove analog signal interference, environmental noise, or the like, from an amplified electrical response received from the sensor signal amplifier 520 to isolate respiratory activity. In some implementations, the low-pass filter 640 isolates respiratory activity by filtering within a frequency range approximately below 0.4 Hz. In some implementations, the low-pass filter 640 includes one or more logical or electronic devices including but not limited to integrated circuits, logic gates, flip flops, gate arrays, programmable gate arrays, and the like. It is to be understood that any electrical, electronic, or like devices, or components associated with the low-pass filter 640 can also be associated with, integrated with, integrable with, replaced by, supplemented by, complemented by, or the like, the system processor 610 or any component thereof.

[0063] The analog-to-digital converter 650 is operable to convert an analog triboelectric response voltage or the like to a digital body position response. In some implementations, the analog-to-digital converter 650 includes one or more logical or electronic devices including but not limited to integrated circuits, logic gates, flip flops, gate arrays, programmable gate arrays, and the like. It is to be understood that any electrical, electronic, or like devices, or components associated with the analog-to-digital converter 650 can also be associated with, integrated with, integrable with, replaced by, supplemented by, complemented by, or the like, the system processor 610 or any component thereof. [0064] The communication interface 660 is operable to communicatively couple the system processor 610 to an external device. In some implementations, the system processor 610 receives the digital signals and transmits them to an external device via, for example, an on board Bluetooth transmitter. As one example, images of real-time sleeping posture and various physiological signals can be displayed on the external device based on digital signals transmitted by the communication interface 660. In some implementations, an external device includes but is not limited to a smartphone, mobile device, wearable mobile device, tablet computer, desktop computer, laptop computer, cloud server, local server, and the like. In some implementations, the communication interface 660 is operable to communicate one or more instructions, signals, conditions, states, or the like between one or more of the system processor 610 and the external device. In some implementations, the communication interface 660 includes one or more digital, analog, or like communication channels, lines, traces, or the like. As one example, the communication interface 660 is or includes at least one serial or parallel communication line among multiple communication lines of a communication interface. In some implementations, the communication interface 660 is or includes one or more wireless communication devices, systems, protocols, interfaces, or the like. In some implementations, the communication interface 660 includes one or more logical or electronic devices including but not limited to integrated circuits, logic gates, flip flops, gate arrays, programmable gate arrays, and the like. In some implementations, the communication interface 660 includes ones or more telecommunication devices including but not limited to antennas, transceivers, packetizers, wired interface ports, and the like. It is to be understood that any electrical, electronic, or like devices, or components associated with the communication interface 660 can also be associated with, integrated with, integrable with, replaced by, supplemented by, complemented by, or the like, the system processor 610 or any component thereof.

[0065] Fig. 7 illustrates an example waveform diagram including example waveforms each associated with a corresponding cardiopulmonary state, in accordance with present implementations. As illustrated by way of example in Fig. 7, an example waveform diagram 700 includes an example normal cardiopulmonary waveform 710, an example deep respiration cardiopulmonary waveform 720, and an example reduced respiration cardiopulmonary waveform 730. It is to be understood that each of the cardiopulmonary waveforms 710, 720 and 730 are superimposed upon each other for illustrative purposes, and that a single cardiopulmonary waveform associated with a person 120 can transition between one or more of the cardiopulmonary waveforms 710, 720 and 730 over time in response to changes in cardiopulmonary state by the person 120.

[0066] The normal respiration cardiopulmonary waveform 710 corresponds to a breathing pattern absent of substantial voluntary or involuntary modification by a person 120. As one example, a typical respiratory rate at rest is 12-18 breaths per minute, corresponding to a respiration frequency in the range of 0.2-0.33 Hz. In some implementations, the normal respiration cardiopulmonary waveform 710 has an amplitude range approximately between - 0.3 V and 0.4 V.

[0067] The deep respiration cardiopulmonary waveform 720 corresponds to a breathing pattern including substantial voluntary increase in breathing activity by a person 120. As one example, deep breathing can correspond to increased displacement of a nonconductive sleeve 530A-D proximate to the chest cavity of the person 120, resulting in an increased amplitude of the deep respiration cardiopulmonary waveform 720 as compared to the normal respiration cardiopulmonary waveform 710. In some implementations, the deep respiration cardiopulmonary waveform 720 has an amplitude range approximately between -0.8 V and 0.8 V.

[0068] The reduced respiration cardiopulmonary waveform 730 corresponds to a breathing pattern with substantial voluntary or involuntary modification by a person 120. In some implementations, the reduced respiration cardiopulmonary waveform 730 corresponds to a signal indicting an OSAHS condition. As one example, falling of soft tissue in an airway of a person 120 blocks air from passing through the trachea and induces OSAHS, resulting in decreased breathing corresponding to the reduced respiration cardiopulmonary waveform 730. In some implementations, reduced respiration cardiopulmonary waveform 730 has a peak-to- peak frequency greater than that of the normal respiration cardiopulmonary waveform 710 and the deep respiration cardiopulmonary waveform 720. In some implementations, the reduced respiration cardiopulmonary waveform 730 has an amplitude range approximately between 0 V and 0.15 V.

[0069] Fig. 8 illustrates an example waveform diagram including an example respiratory waveform, in accordance with present implementations. As illustrated by way of example in Fig. 8, an example waveform diagram 800 includes an example respiration waveform 810 having a first peak 812 at time tl 802, and a second peak 814 at time t2 804. In some implementations, the respiration waveform 810 has an amplitude range approximately between 0 V and 0.8 V. [0070] Fig. 9 illustrates an example waveform diagram including an example heartbeat waveform, in accordance with present implementations. As illustrated by way of example in Fig. 9, an example waveform diagram 900 includes an example heartbeat waveform 910 having a plurality of peaks corresponding to a cardiac waveform, and is based on a bandpass-filtered waveform of one or more of the normal respiration cardiopulmonary waveform 710, the deep respiration cardiopulmonary waveform 720, and the reduced respiration cardiopulmonary waveform 730. In some implementations, the heartbeat waveform 910 corresponds to BCG in the 1-20 Hz frequency range and associated with synchronous movements of the heartbeat caused by left ventricular pump activity. As one example, the heartbeat waveform 910 features several prominent peaks and can be separated into three major components: pre-systolic (G), systolic (H, I, J, K) and diastolic (L) components.

[0071] Fig. 10 illustrates an example waveform diagram including an example respiratory rate waveform and an example heartbeat rate waveform, in accordance with present implementations. As illustrated by way of example in Fig. 10, an example waveform diagram 1000 includes a respiratory rate waveform 1010 and a heartbeat rate waveform 1020.

[0072] The respiratory rate waveform 1010 corresponds to a respiration rate of a person 120 and is based on a low-pass filtered waveform of one or more of the normal respiration cardiopulmonary waveform 710, the deep respiration cardiopulmonary waveform 720, and the reduced respiration cardiopulmonary waveform 730. In some implementations, the respiratory rate is calculated by Equation 1 : bpm (1)

[0073] In Equation 1, a respiratory rate (RR) is calculated based on a current time T ^ax associated with a current (m) respiratory peak, and a preceding time associated with a respiratory peak preceding the current respiratory peak (m-1). Correspondingly, a maximum respiratory voltage is expressed as R^ ^ax and the preceding maximum respiratory voltage is R _m -i ^m the interval T _m ^ax )· In some implementations, the maximum respiratory voltage corresponds to the first peak 812, the time tl 802 corresponds to the current time, the preceding maximum respiratory voltage corresponds to the second peak 814, and the time t2 804. corresponds to the preceding time.

[0074] The heartbeat rate waveform 1020 corresponds to a heartbeat rate of a person 120 and is based on a bandpass- filtered waveform of one or more of the normal respiration cardiopulmonary waveform 710, the deep respiration cardiopulmonary waveform 720, and the reduced respiration cardiopulmonary waveform 730. In some implementations, the heartbeat rate is calculated by Equation 1 correspondingly to the respiratory rate, and by selecting current and preceding peaks in accordance with the J peak or other corresponding peak or peaks of the BCG.

[0075] Fig. 11 illustrates an example method of managing cardiopulmonary activity, in accordance with present implementations. In some implementations, the example system 100 performs method 1100 according to present implementations. In some implementations, the method 1100 begins at step 1110.

[0076] At step 1110, the example system deforms at least one sensor unit in a radial direction thereof. In some implementations, step 1110 includes at least one of steps 1112 and 1114. At step 1112, the example system compresses the sensor unit in the radial direction thereof. At step 1114, the example system deforms the sensor unit in response to pressure contact at the sensor unit by a body or portion thereof. The method 1100 then continues to step 1120.

[0077] At step 1120, the example system increases friction contact within the sensor unit. In some implementations, step 1120 includes step 1122. At step 1122, the example system contacts at least one conductive fiber of the sensor unit to a nonconductive sleeve of the sensor unit. The method 1100 then continues to step 1130.

[0078] At step 1130, the example system generates at least one triboelectric response at the sensor unit. The trace of the normal breathing process is accompanied by the heartbeat: the large amplitude signal is the respiratory signal, and the small amplitude signal is the heartbeat signal. It was justified that our smart textile can accurately capture these two important physiological signals simultaneously. The method 1100 then continues to step 1140. At step 1102, the example system continues to step 1130.

[0079] At step 1140, the example system aggregates one or more triboelectric responses with respect to a body position grid. In some implementations, step 1140 includes step 1142. At step 1142, the example system aggregates the triboelectric responses by sequential sampling of a plurality of sensor units. The method 1100 then continues to step 1150.

[0080] At step 1150, the example system obtain at least one cardiopulmonary signal from the triboelectric response. In some implementations, step 1150 includes step 1152. At step 1152, the example system obtains a combined a cardiopulmonary signal including a respiratory signal and a cardiac signal. The method 1100 then continues to step 1202.

[0081] Fig. 12 illustrates an example method of managing cardiopulmonary activity further to the example method of Fig. 11. In some implementations, the example system 100 performs method 1200 according to present implementations. In some implementations, the method 1200 begins at step 1202. The method 1200 then continues to step 1210.

[0082] At step 1210, the example system converts at least one cardiopulmonary signal to a digital signal. The acquired cardiopulmonary signal is or includes a superposition of respiratory and heartbeat signals. These two vital signs play a significant role of accurately assessing physiological state and medical diagnoses of a person 120. In some implementations, digital signal processing including low-pass and bandpass filtering separates raw physiological signals of the cardiopulmonary signal. The method 1200 then continues to step 1220.

[0083] At step 1220, the example system generates at least one respiratory signal based on the digital signal. In some implementations, step 1220 includes at least one of steps 1222, 1224 and 1226. At step 1222, the example system applies a low pass filter to the digital signal. At step 1224, the example system isolates one or more respiratory signal peaks. At step 1126, the example system generates a respiratory rate signal based on one or more of the respiratory signal peaks. The method 1200 then continues to step 1230.

[0084] At step 1230, the example system generates at least one heartbeat signal based on the digital signal. In some implementations, step 1230 includes at least one of steps 1232, 1234 and 1236. At step 1232, the example system applies a bandpass filter to the digital signal. At step 1234, the example system isolates one or more heartbeat signal peaks. At step 1236, the example system generates a heartbeat rate signal based on one or more of the heartbeat signal peaks. The method 1200 then continues to step 1302.

[0085] Fig. 13 illustrates an example method of managing cardiopulmonary activity further to the example method of Fig. 12. In some implementations, the example system 100 performs method 1300 according to present implementations. In some implementations, the method 1300 begins at step 1302. The method 1300 then continues to step 1310.

[0086] At step 1310, the example system identifies a body position based on a body position grid response. In some implementations, the example system identifies the body position in accordance with detection of body pressure at one or more of the sensor devices 400 in accordance with a predetermined body position pattern. In some implementations, body positions including prone, supine, sitting, recumbent, and the like can be associated with corresponding body position patterns including a grid pattern comparable, matchable, or the like, with body position activation region 210. The method 1300 then continues to step 1320. [0087] At step 1320, the example system classifies respiratory signals according to one or more waveform characteristics. In some implementations, the example system classifies the respiratory signal by one or more of amplitude, frequency, and the like, to classify the respiratory signal as one of the normal respiration cardiopulmonary waveform 710, the deep respiration cardiopulmonary waveform 720, and the reduced respiration cardiopulmonary waveform 730. The method 1300 then continues to step 1330.

[0088] At step 1330, the example system determines whether a respiratory signal corresponds to a target respiratory signal classification. In accordance with a determination that the respiratory signal corresponds to the target respiratory signal classification, the method 1300 continues to step 1340. Alternatively, in accordance with a determination that the respiratory signal does not correspond to the target respiratory signal classification, the method 1300 continues to step 1102.

[0089] At step 1340, the example system classifies the body position to a sleep position. The method 1300 then continues to step 1350.

[0090] At step 1350, the example system determines whether the sleep position corresponds to a target sleep position classification. In some implementations, the example system determines whether the sleep position corresponds to a target sleep position classification after a predetermined delay period subsequent to an initial detection of reduced respiration. In some implementations, the delay period corresponds to a period during which reduced breathing becomes a health hazard. As one example, to avoid sudden death caused by a prolonged apnea during sleep, a delay period could correspond to 10 seconds. It is to be understood that this delay period can be customized according to any arbitrary length in accordance with individual or cohort medical needs, conditions, or the like. In accordance with a determination that the sleep position corresponds to the target sleep position classification, the method 1300 continues to step 1360. Alternatively, in accordance with a determination that the sleep position does not correspond to the target sleep position classification, the method 1300 continues to step 1102. [0091] At step 1360, the example system generates an emergency response. In some implementations, step 1360 includes at least one of steps 1362 and 1364. At step 1362, the example system generates an emergency physical stimulus response. As one example, the example system can activate a bedside bulb or an audible alarm to quickly awaken the person 120 and help them return to normal breathing. At step 1364, the example system generates an emergency communication response. As one example, the example system can automatically alert a doctor, medical system, emergency response system, or the like, to ensure that the person 120 receives timely treatment. In some implementations, the method 1300 ends at step 1360. [0092] Fig. 14 illustrates a further example method of managing cardiopulmonary activity, in accordance with present implementations. In some implementations, the example system 100 performs method 1400 according to present implementations. In some implementations, the method 1400 begins at step 1110. It is to be understood that steps 1110, 1120, 1130, 1140 and 1150 of Fig. 14 can correspond at least partially to steps 1110, 1120, 1130, 1140 and 1150 of Fig. 11. It is to be further understood that steps 1210, 1220 and 1230 of Fig. 14 can correspond at least partially to steps 1210, 1220 and 1230 of Fig. 15.

[0093] At step 1110, the example system deforms at least one sensor unit in a radial direction thereof. The method 1400 then continues to step 1120. At step 1120, the example system increases friction contact within the sensor unit. The method 1400 then continues to step 1130. At step 1130, the example system generates at least one triboelectric response at the sensor unit. The method 1400 then continues to step 1140. At step 1102, the example system continues to step 1130. At step 1140, the example system aggregates one or more triboelectric responses with respect to a body position grid. The method 1400 then continues to step 1150. At step 1150, the example system obtain at least one cardiopulmonary signal from the triboelectric response. The method 1400 then continues to step 1210.

[0094] At step 1210, the example system converts at least one cardiopulmonary signal to a digital signal. The method 1400 then continues to step 1220. At step 1220, the example system generates at least one respiratory signal based on the digital signal. The method 1400 then continues to step 1230. At step 1230, the example system generates at least one heartbeat signal based on the digital signal. The method 1400 then continues to step 1502.

[0095] Fig. 15 illustrates a further example method of managing cardiopulmonary activity further to the example method of Fig. 14. In some implementations, the example system 100 performs method 1500 according to present implementations. In some implementations, the method 1500 begins at step 1502. The method 1500 then continues to step 1310. It is to be understood that steps 1310, 1320, 1330, 1340, 1350 and 1360 of Fig. 15 can correspond at least partially to steps 1310, 1320, 1330, 1340, 1350 and 1360 of Fig. 13.

[0096] At step 1310, the example system identifies a body position based on a body position grid response. The method 1500 then continues to step 1320. At step 1320, the example system classifies respirator signals according to one or more waveform characteristics. The method 1500 then continues to step 1330.

[0097] At step 1330, the example system determines whether a respiratory signal corresponds to a target respiratory signal classification. In accordance with a determination that the respiratory signal corresponds to the target respiratory signal classification, the method 1500 continues to step 1340. Alternatively, in accordance with a determination that the respiratory signal does not correspond to the target respiratory signal classification, the method 1500 continues to step 1102.

[0098] At step 1340, the example system classifies the body position to a sleep position. The method 1500 then continues to step 1350.

[0099] At step 1350, the example system determines whether the sleep position corresponds to a target sleep position classification after a predetermined delay period. In accordance with a determination that the sleep position corresponds to the target sleep position classification after the predetermined delay period, the method 1300 continues to step 1360. Alternatively, in accordance with a determination that the sleep position does not correspond to the target sleep position classification after the predetermined delay period, the method 1500 continues to step 1102

[00100] At step 1360, the example system generates an emergency response. In some implementations, the method 1500 ends at step 1360.

[00101] The herein described subject matter sometimes illustrates different components contained within, or connected with, different other components. It is to be understood that such depicted architectures are illustrative, and that in fact many other architectures can be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively "associated" such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality can be seen as "associated with" each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated can also be viewed as being "operably connected," or "operably coupled," to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being "operably couplable," to each other to achieve the desired functionality. Specific examples of operably couplable include but are not limited to physically mateable and/or physically interacting components and/or wirelessly interactable and/or wirelessly interacting components and/or logically interacting and/or logically interactable components

[00102] With respect to the use of plural and/or singular terms herein, those having skill in the art can translate from the plural to the singular and/or from the singular to the plural as is appropriate to the context and/or application. The various singular/plural permutations may be expressly set forth herein for sake of clarity.

[00103] It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as "open" terms (e.g., the term "including" should be interpreted as "including but not limited to," the term "having" should be interpreted as "having at least," the term "includes" should be interpreted as "includes but is not limited to," etc.).

[00104] Although the figures and description may illustrate a specific order of method steps, the order of such steps may differ from what is depicted and described, unless specified differently above. Also, two or more steps may be performed concurrently or with partial concurrence, unless specified differently above. Such variation may depend, for example, on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations of the described methods could be accomplished with standard programming techniques with rule-based logic and other logic to accomplish the various connection steps, processing steps, comparison steps, and decision steps.

[00105] It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation, no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases "at least one" and "one or more" to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles "a" or "an" limits any particular claim containing such introduced claim recitation to inventions containing only one such recitation, even when the same claim includes the introductory phrases "one or more" or "at least one" and indefinite articles such as "a" or "an" (e.g., "a" and/or "an" should typically be interpreted to mean "at least one" or "one or more"); the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should typically be interpreted to mean at least the recited number (e.g., the bare recitation of "two recitations," without other modifiers, typically means at least two recitations, or two or more recitations).

[00106] Furthermore, in those instances where a convention analogous to "at least one of A, B, and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B, and C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). In those instances where a convention analogous to "at least one of A, B, or C, etc." is used, in general, such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B, or C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and/or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase "A or B" will be understood to include the possibilities of "A" or "B" or "A and B." [00107] Further, unless otherwise noted, the use of the words “approximate,” “about,” “around,” “substantially,” etc., mean plus or minus ten percent.

[00108] The foregoing description of illustrative implementations has been presented for purposes of illustration and of description. It is not intended to be exhaustive or limiting with respect to the precise form disclosed, and modifications and variations are possible in light of the above teachings or may be acquired from practice of the disclosed implementations. It is intended that the scope of the invention be defined by the claims appended hereto and their equivalents.