Wearable physiological signal sensing system

Abstract

The invention discloses a wearable physiological signal sensing system which comprises a system circuit board provided with an upper surface and a lower surface, a stethoscope arranged on the lower surface and used for sensing heart sound signals of a user, a plurality of electrocardio electrodes arranged on the lower surface and adjacent to the stethoscope and used for sensing electrocardio signals of the user, and an oximeter arranged on the upper surface and used for detecting the heart sound signals of the user. The blood oxygen sensor is used for sensing blood oxygen concentration and pulse wave signals of a user. The system circuit board is electrically connected with the stethoscope, the plurality of electrocardio electrodes and the oximeter, the system circuit board obtains the pulse wave transmission time of the user by comparing the electrocardio signal with the pulse wave signal or comparing the heart sound signal with the pulse wave signal, and the continuous blood pressure of the user is calculated according to the pulse wave transmission time.

Description

Technical Field

[0001] This invention relates to the technical field of physiological signal sensing, and specifically to a wearable physiological signal sensing system. Background Technology

[0002] As people pay increasing attention to their health, physiological monitoring systems are becoming increasingly sophisticated. For patients with chronic diseases, long-term, accurate monitoring of physiological parameters can effectively reduce disease risk and provide valuable data for treatment. Traditional physiological parameter monitoring equipment, including simple medical and healthcare devices that measure heart rate, respiratory rate, blood pressure, blood oxygen saturation, and body temperature, provides a basis for assessing the health status of the circulatory and respiratory systems, and has broad application prospects in home healthcare, telemedicine, and clinical medicine.

[0003] The development of medical testing instruments is trending towards portability and networking. Traditional physiological parameter testing instruments suffer from limitations such as single functionality and large size, failing to meet the increasing demand for long-term and real-time testing. However, with the continuous improvement of sensor technology integration and intelligence, it has become possible to integrate multiple sensors into a single unit for medical testing while maintaining low costs.

[0004] Heart failure is a prevalent public health problem worldwide, placing a huge burden on overall healthcare costs. In recent years, with increased public awareness of health, health management methods that monitor physical and mental well-being in daily life by recording and analyzing physiological information over long periods, ranging from hours to months, have become more widespread.

[0005] With an aging population, health early warning and care products are becoming a growing trend. To detect symptoms early, especially psychogenic diseases with high rates of sudden death, wearable physiological signal sensing systems can provide real-time and effective detection and recording of abnormal heartbeat signals, as well as key physiological signals such as blood oxygen and blood pressure. Physicians can then analyze these real-time recorded physiological signals to provide health early warning and care solutions.

[0006] Therefore, it is necessary and of great practical value to propose a wearable physiological signal detection system that can be applied to home care, mobile care, workplace health management, and autonomous health early warning systems. Summary of the Invention

[0007] To achieve the aforementioned objectives, this invention discloses a wearable physiological signal sensing system, comprising a system circuit board having upper and lower surfaces, a stethoscope disposed on the lower surface for sensing the user's heart sound signals, multiple electrocardiogram (ECG) electrodes disposed on the lower surface adjacent to the stethoscope for sensing the user's ECG signals, and a pulse oximeter disposed on the upper surface for sensing the user's blood oxygen concentration and pulse wave signals. The system circuit board is electrically connected to the stethoscope, the multiple ECG electrodes, and the pulse oximeter. The system circuit board obtains the user's pulse wave transit time by comparing the ECG signals with the pulse wave signals, or by comparing the heart sound signals with the pulse wave signals, and calculates the user's continuous blood pressure accordingly.

[0008] In one embodiment, the user's continuous blood pressure is estimated by predicting blood pressure using an artificial intelligence (AI) algorithm. The AI ​​algorithm uses the time-domain characteristics of the accelerated pulse wave signal, the pulse wave transmission time, and the user's height parameters to jointly establish a multivariate linear model.

[0009] In one embodiment, the stethoscope includes: a diaphragm, a piezoelectric sensor, and a sound-insulating ring; wherein the diaphragm is disposed on the lower surface of a circuit board; the sound-insulating ring is disposed on the lower surface, surrounds the diaphragm, and forms a resonant cavity with the circuit board; the piezoelectric sensor is disposed on the side of the sound-insulating ring that is not in contact with the circuit board, wherein the piezoelectric sensor is attached to the user's skin.

[0010] In one embodiment, the pulse oximeter includes an infrared light source, a red light source, and a photosensor for sensing the user's fingertip pulse wave. The circuit board includes at least a signal preprocessing circuit for filtering, amplifying, and performing analog-to-digital conversion on the heart sound signal, electrocardiogram signal, and pulse wave signal; and a microprocessor for receiving the digitized heart sound signal, electrocardiogram signal, and pulse wave signal, and processing them to obtain preprocessed digitized heart sound signal, electrocardiogram signal, and pulse wave signal.

[0011] In one embodiment, the wearable physiological signal sensing system is attached to the user's chest to continuously monitor the aforementioned heart sound signals and electrocardiogram signals. The blood oxygen concentration and pulse wave signals are obtained while the user is pressing the pulse oximeter.

[0012] In one embodiment, the wearable physiological signal sensing system is connected to an external mobile device to facilitate the transmission of physiological signals. The external mobile device can be connected to a cloud server or an edge device to facilitate the processing and analysis of physiological signals, which include one or any combination of electrocardiogram (ECG) signals, pulse wave signals, heart sound signals, and blood oxygen saturation. In another embodiment, the wearable physiological signal sensing system includes an embedded SIM card on the system circuit board. In one embodiment, the wearable physiological signal sensing system is connected to one of the external mobile device, a cloud server, or an edge computing device via the embedded SIM card to facilitate the transmission of the physiological signals.

[0013] In one embodiment, the system circuit board performs the following steps to measure blood pressure, including sensing a user's heart sound signal, electrocardiogram signal, and blood oxygen concentration; comparing the electrocardiogram signal with the pulse wave signal, or comparing the heart sound signal with the pulse wave signal, to obtain the pulse wave transit time (PTT); and obtaining the user's blood pressure using an AI algorithm.

[0014] In one embodiment, a wearable physiological signal sensing system includes a system circuit board with upper and lower surfaces; a stethoscope disposed on the lower surface and electrically connected to the system circuit board for sensing the user's heart sound signals; at least one patch disposed on the lower surface for attaching to the user's skin; a plurality of electrocardiogram (ECG) electrodes disposed on the lower surface for sensing the user's ECG signals; and a pulse oximeter disposed on the upper surface for sensing the user's blood oxygen concentration and pulse wave signals. In one embodiment, the system includes comparing ECG signals with pulse wave signals, or comparing heart sound signals with pulse wave signals, to obtain the user's pulse wave transit time, thereby calculating the user's continuous blood pressure; wherein continuous blood pressure is predicted using an artificial intelligence (AI) algorithm, which utilizes the temporal characteristics of the pulse wave signal, the pulse wave transit time, and the user's height to establish a multivariate linear model. Attached Figure Description

[0015] Figure 1 This invention demonstrates the system architecture proposed in this invention.

[0016] Figure 2(a) shows a side view of the piezoelectric sensor structure proposed in this invention.

[0017] Figure 2(b) shows the piezoelectric patch structure proposed in this invention.

[0018] Figures 3(a)-3(c) Different design embodiments of the piezoelectric patch structure are shown respectively.

[0019] Figures 4(a)-4(c) This demonstrates the method for testing the attachment of piezoelectric patch structures.

[0020] Figures 5(a)-5(c) An example of a pressure sensor configuration is shown.

[0021] Figure 6(a) shows a stethoscope according to an embodiment of the present invention.

[0022] Figure 6(b) shows a stethoscope according to another embodiment of the present invention.

[0023] Figure 7 This diagram shows a functional block diagram of a stethoscope according to an embodiment of the present invention.

[0024] Figure 8 This diagram shows a flowchart of a heart sound detection system according to an embodiment of the present invention.

[0025] Figure 9 A schematic diagram showing an embodiment of the charging state according to the present invention is displayed.

[0026] Figure 10 A schematic diagram showing an embodiment of the charging state according to the present invention is displayed.

[0027] Figure 11 This invention demonstrates the method for obtaining pulse wave transit time (PTT) disclosed in this invention.

[0028] Figure 12 This invention demonstrates the method for measuring blood pressure disclosed in this invention.

[0029] Figure 13(a) shows a cross-sectional schematic diagram of a wearable physiological signal sensing system according to one embodiment of the present invention. Figure 13(b) shows a cross-sectional schematic diagram of a wearable physiological signal sensing system according to another embodiment of the present invention. Figure 13(c) shows a cross-sectional schematic diagram of a wearable physiological signal sensing system according to yet another embodiment of the present invention.

[0030] Figure 13(d) shows a cross-sectional schematic diagram of a wearable physiological signal sensing system according to another embodiment of the present invention.

[0031] Figure 14 This shows a functional block diagram of the wearable physiological signal sensing system proposed in an embodiment of the present invention.

[0032] Figure 15(a) shows a system architecture diagram proposed in an embodiment of the present invention.

[0033] Figure 15(b) shows a system architecture diagram proposed in another embodiment of the present invention.

[0034] Figure 16 This illustrates an example of a processing system according to an embodiment of the present invention.

[0035] Symbol explanation:

[0036] 10: Users

[0037] 100: Heart Sound Detection System

[0038] 101: Heart sound acquisition device (stethoscope)

[0039] 103: Mobile Device

[0040] 107: Cloud Server

[0041] 19: Piezoelectric sensor structure

[0042] 201: Piezoelectric material layer

[0043] 203a, 203b: Metal electrodes

[0044] 205: Circuit Board

[0045] 20: Piezoelectric patch structure

[0046] 207:Substrate

[0047] 209: Anti-allergy gel

[0048] 211a, 211b, 211c: Bottom electrodes

[0049] 213: Insulation layer

[0050] 201: Piezoelectric material layer

[0051] 203: Metal leads

[0052] 205: Circuit Board

[0053] 204: Electrical Connections

[0054] 215: Cover plate

[0055] 217: Encapsulating adhesive

[0056] 220: Substrate

[0057] 206: Paste

[0058] S401, S403, S405: Step 231: Skin resistance

[0059] 503: Pressure sensor

[0060] 501: Capacitive Sensor

[0061] 505: Circuit Board

[0062] 507: Soundproofing ring

[0063] 601: Heart sound acquisition device (stethoscope)

[0064] 601a: Diaphragm

[0065] 607: Frame (Soundproofing Ring)

[0066] 605: Circuit Board

[0067] 603: Piezoelectric sensor

[0068] 604: Line

[0069] 631: Human skin

[0070] 640: Multiple holes

[0071] 701: Capacitive Sensor

[0072] 703: Piezoelectric sensor

[0073] 725: Microprocessor

[0074] 727: Storage Unit

[0075] 729: Wireless Transmission Module

[0076] 729a: Antenna

[0077] 731, 731a: Amplifier

[0078] 733, 733a: Low-pass filter

[0079] 735, 735a: Analog-to-Digital Converter (ADC)

[0080] 737: Battery Pack

[0081] 739: Power Management Unit

[0082] 741: Charging coil

[0083] S801, S802, S803, S804, S805, S806, S807, S808, S809, S810, S811, S812, S813, S814: Steps

[0084] 900: Stethoscope charging device

[0085] 902: Wireless Transmitting Coil

[0086] 904: Battery

[0087] 1102: Pulse wave signal (PPG)

[0088] 1104: Electrocardiogram (ECG) signal

[0089] 1106: Pulse wave transit time (PTT)

[0090] 1200: Method

[0091] S1201, S1202, S1203, S1204: Steps

[0092] 1300, 1300a, 1400, 1500: Wearable physiological signal sensing system

[0093] 1301: Circuit Board

[0094] 1301a: First surface

[0095] 1301b Second Surface

[0096] 1302: Stethoscope

[0097] 1302a: Diaphragm

[0098] 1302b: Frame (Soundproofing Ring)

[0099] 1302c: Piezoelectric sensor

[0100] 1303: Electrocardiogram stethoscope device

[0101] 1304: Multiple ECG patches

[0102] 1304a: First ECG Patch

[0103] 1304b: Second ECG patch

[0104] 1306: Pulse Oximeter

[0105] 1306a: Body Temperature Sensor

[0106] 1411: Signal preprocessing circuit

[0107] 1411a, 1411b, 1411c: Signal preprocessing channels

[0108] 1415: Microprocessor

[0109] 1417: Storage Unit

[0110] 1419: Wireless Transmission Module

[0111] 1421: Battery Pack

[0112] 1423: Power Management Module

[0113] 1425: Charging coil

[0114] 1503: Mobile Device

[0115] 1505: Cloud Network

[0116] 1507: Cloud Server

[0117] 1601: Processor

[0118] 1602: Main Memory

[0119] 1603: Wireless transceiver

[0120] 1605: Control device

[0121] 1607: Video Monitor

[0122] 1609: Input / Output (I / O) Devices

[0123] 6011: Communication Connection Bus

[0124] 1613: Signal generating device

[0125] 1650: Processing System Detailed Implementation

[0126] This invention will be described in detail here with reference to specific embodiments and their viewpoints. Such descriptions are for illustrative purposes only, explaining the structure or steps of the invention, and are not intended to limit the scope of the patent application. Therefore, in addition to the specific and preferred embodiments described in the specification, the invention can also be widely implemented in other different embodiments. The following specific embodiments illustrate the implementation of the invention, and those skilled in the art can easily understand the effectiveness and advantages of the invention through the content disclosed in this specification. Furthermore, the invention can also be used and implemented through other specific embodiments, and the various details set forth in this specification can be applied based on different needs, and various modifications or changes can be made without departing from the spirit of the invention.

[0127] This invention proposes a wearable heart sound detection system, which mainly utilizes a heart sound detection device worn on the human body, combining a sound sensing device and wireless transmission, serving as a portable heart sound collection device that can be connected to the Internet of Things. The collected physiological data (e.g., personal heart sounds) is processed by a handheld electronic computing device (mobile device), and then transmitted and stored on a cloud server via a cloud network.

[0128] Figure 1A wearable heart sound detection system 100 is shown. Its main architecture includes a heart sound acquisition device 101, which is attached to a user 10 in the form of a monitoring patch. The heart sound acquisition device 101 is communicatively connected to a mobile device (e.g., a smartphone, tablet, or other external computing electronic device) 103. Heart sound data collected by the wearable heart sound acquisition device 101 can be wirelessly transmitted (e.g., via Bluetooth, WiFi, or other wireless communication methods) from the mobile device 103 to a cloud server 107 via a cloud network 105. The data is stored in a cloud database on the cloud server. The system also includes an application installed on the mobile device, which contains instructions for receiving and sending data between the wearable heart sound acquisition device 101, the mobile device 103, and the cloud server 105. The aforementioned application can operate on Android, Windows 10, or iOS operating system platforms. It can upload the collected data / signals, such as heart sounds and their waveforms, to the cloud server 105 for storage. After analyzing and processing the data through data analysis and feature extraction algorithms, it generates an evaluation report and provides medical advice accordingly.

[0129] For ease of wear, the stethoscope (heart sound acquisition device) 101 can be attached to the chest of the user 10 via a monitoring patch. It detects human sound signals through built-in acoustic sensors. The acoustic sensors mainly consist of a piezoelectric sensor and a microphone. The piezoelectric sensor primarily comprises a piezoelectric material layer (e.g., polyvinylidene fluoride (PVDF) polymer piezoelectric film, lead zirconate titanate (PZT), etc.), with conductive metals (e.g., aluminum (Al), copper (Cu), etc.) plated on its upper and lower surfaces. A lead is extended from each of the upper and lower metal layers to connect to a circuit board, which can be used to measure the voltage signal generated by vibration. The microphone primarily consists of a typical capacitive sensor, which uses an ultra-thin material as a diaphragm (e.g., 30μm thick glass), plated with a conductive material, and encapsulated with adhesive to the circuit board to form a resonant chamber. The purpose is to use the sound of the heartbeat to vibrate the diaphragm, causing a change in capacitance between the diaphragm and the circuit board. The heart sound acquisition device captures this change to record the heartbeat.

[0130] Referring to Figure 2(a), a side view of the piezoelectric sensor structure 19 proposed in this invention is shown. The upper part of the figure shows that the piezoelectric sensor mainly consists of a piezoelectric material layer (e.g., a polyvinylidene fluoride (PVDF) polymer piezoelectric film, lead zirconate titanate (PZT), etc.) 201, with conductive metals (e.g., aluminum (Al), copper (Cu), etc.) plated on its upper and lower surfaces. The lower part of the figure shows a top view of the piezoelectric sensor structure 19, wherein each of the upper and lower metal electrodes (203a, 203b) has a lead wire extending from it and connected to a circuit board 205, which can be used to measure the voltage signal generated by vibration. In one embodiment, the thickness of the piezoelectric sensor is less than 50 μm.

[0131] Figure 2(b) shows the piezoelectric patch structure 20 proposed in this invention. The upper part of the figure is a side view of the piezoelectric patch structure, which includes a substrate 207, a skin-contact anti-allergy gel 209 coated on the underside of the substrate, multiple bottom electrodes (211a, 211b, 211c) disposed under the substrate 207, exposing the outer side of the gel layer 209, used to determine whether the piezoelectric patch 20 has been successfully attached, an insulating layer 213 disposed on the substrate 207 as a planarization layer, also having a planarization function, a piezoelectric material layer 201 attached to the insulating layer 213, metal leads 203 extending to connect with the adjacent circuit board 205 (the electrical connection 204 can be conductive adhesive, snap-fit ​​connector, etc.), a cover plate 215, and an encapsulating adhesive 217. The encapsulating adhesive 217 is used to bond and encapsulate the cover plate 215 and the substrate 207 by hot pressing or rolling, as a protective layer. The lower part of the figure is a front view of the piezoelectric patch structure 20 proposed in this invention. The insulating layer 213, the substrate 207, and the gel layer 209 are stacked from bottom to top to form the substrate 220.

[0132] In one embodiment, the substrate 207 may be made of glass, or plastics such as polyimide (PI) or polyethylene terephthalate (PET), or textiles. In one embodiment, the encapsulating adhesive 217 may be ethylene / vinyl acetate copolymer (EVA). In one embodiment, the cover plate 215 may be made of glass, or plastics such as polyimide (PI) or polyethylene terephthalate (PET), or textiles.

[0133] In one embodiment, the thickness of the piezoelectric patch structure 20 is less than 2000 μm, wherein the thickness of the gel layer 209 is less than 700 μm; the thickness of the substrate 207 is less than 300 μm; the thickness of the insulating layer 213 is less than 50 μm; the thickness of the piezoelectric material layer 201 is less than 50 μm; the thickness of the circuit board 205 is less than 200 μm; and the thickness of the encapsulating adhesive 217 is less than 300 μm. In one embodiment, the piezoelectric sensor can also be replaced by an accelerometer, gyroscope, or other sensors.

[0134] Figures 3(a)-(c) show different designs of the piezoelectric patch structure 20. In Figure 3(a), the piezoelectric patch structure 20 has a circuit board 205 placed on top of the piezoelectric material 201. The piezoelectric material layer 201 is attached to the insulating layer 213. The circuit board 205 is attached to the piezoelectric material 201 with adhesive 206. The electrical connection 204 between the circuit board 205 and the metal leads 203 plated on the piezoelectric material 201 is created by conductive glue or a snap-fit ​​connector. Figure 3(b) shows the piezoelectric material 201 directly attached to the circuit board 205, and the metal leads 203 of the piezoelectric sensor structure 19 are electrically connected to a system board 230. Figure 3(c) shows the piezoelectric material 201 directly attached to the circuit board 205, and the circuit board 205 is a flexible circuit board that can be directly bent onto the piezoelectric sensor structure 19.

[0135] Figure 4 shows the method of attaching and testing the piezoelectric patch structure 20. Taking the piezoelectric patch structure 20 shown in Figure 4(a) as an example, its stacking method is the same as shown in Figure 2(b). For construction details, please refer to the previous description. This structure includes multiple bottom electrodes (211a, 211b, 211c) disposed below the substrate 207 and exposed on the outside of the gel layer 209. The multiple bottom electrodes (211a, 211b, 211c) can be referred to as the first electrode P1, the second electrode P2, and the third electrode P3, respectively, as shown in Figure 4(b). A switch configuration circuit is designed between the multiple bottom electrodes to perform attachment testing of the piezoelectric patch structure 20 to the skin resistance 231 of human skin. The aforementioned switch configuration circuit is configured such that the first switch SW1 (switch 1) and the second switch SW2 (switch 2) are connected in series in the loop connecting the first electrode P1 and the third electrode P3; the first switch SW1 (switch 1) and the third switch SW3 (switch 3) are connected in series in the loop connecting the first electrode P1 and the second electrode P2; and the second switch SW2 (switch 2) and the third switch SW3 (switch 3) are connected in series in the loop connecting the third electrode P3 and the second electrode P2. When the switch configuration circuit is set as shown in Figure 4(b), the method for testing the attachment of the piezoelectric patch structure 20 is as follows: First, in step S401, connect the first switch SW1 (switch 1) and the second switch SW2 (switch 2), and disconnect the third switch SW3 (switch 3). Check if any resistance is measured. If not, the attachment is incomplete. If so, proceed to step S403, connect the first switch SW1 (switch 1) and the third switch SW3 (switch 3), and disconnect the second switch SW2 (switch 2). Check if any resistance is measured. If not, the attachment is incomplete. If so, proceed to step S405, connect the first switch SW2 (switch 2) and the third switch SW3 (switch 3), and disconnect the first switch SW1 (switch 1). Check if any resistance is measured. If not, the attachment is incomplete. If so, the attachment is complete.

[0136] Another embodiment of the stethoscope (heart sound acquisition device) 101 is a microphone composed of a capacitive sensor. The main component of the microphone is a general capacitive sensor, which uses an ultra-thin material as a diaphragm (e.g., 30μm thick glass), coated with a conductive material, and encapsulates this diaphragm to a circuit board using a frame adhesive to form a resonant chamber. The purpose is to use the sound emitted by the heartbeat to vibrate the diaphragm, causing a change in capacitance between the diaphragm and the circuit board. The heart sound acquisition device captures this change to record the heartbeat.

[0137] Wearable capacitive sensors, due to environmental noise and other issues, require careful monitoring of contact with the body during use. Therefore, this invention proposes placing a pressure sensor on the sound-absorbing ring of the capacitive sensor. This pressure sensor can incorporate piezoelectric, capacitive, or resistive technologies, and its placement can be between the sound-absorbing ring and the circuit board or below the circuit board. Essentially, the pressure sensor generates a corresponding pressure signal based on the degree of pressure applied, thus allowing it to determine the degree of contact between the wearable capacitive sensor and the user.

[0138] The capacitive sensor proposed in this invention, as shown in Figures 5(a)-(c), illustrates several possible embodiments of the pressure sensor configuration, wherein the left view of each figure is a side view and the right view is a top view. Referring to Figures 5(a)-(b), the pressure sensor 503 is disposed between the circuit board 505 of the capacitive sensor 501 and the sound insulation ring 507; alternatively, as shown in Figure 5(c), the pressure sensor 503 can be disposed below the sound insulation ring 507.

[0139] Based on the above-mentioned problems that wearable capacitive sensors may face, such as poor response at low frequencies and high environmental noise, this invention proposes a wearable heart sound acquisition device that integrates the piezoelectric sensor structure disclosed in Figures 3-4 and the capacitive sensor disclosed in Figure 5. The integrated wearable heart sound acquisition device will be discussed in subsequent paragraphs.

[0140] Figure 6(a) shows a stethoscope (heart sound acquisition device) 601 according to an embodiment of the present invention, which includes a diaphragm 601a coated with a conductive material. The diaphragm 601a is encapsulated with a plastic frame (soundproof ring) 607 and a circuit board 605 (the resonant cavity formed by the soundproof ring 607 and the circuit board 605, combined with the diaphragm 601a, forms a microphone structure). A piezoelectric sensor 603 is disposed below the soundproof ring 607 and electrically connected to the circuit board 605 via a line 604. By contacting human skin 631, it can be used to measure the voltage signal generated by vibration. That is, the piezoelectric sensor 603 can serve as a diaphragm and can be used to assist conventional capacitive sensors in responding poorly to low-frequency signals, such as the third and fourth heart sounds, which have frequencies around 20Hz.

[0141] In one embodiment, the piezoelectric sensor 603 can be formed on a flexible substrate (refer to FIG. 2) and fabricated as a patch. Multiple electrodes are disposed at the bottom of the flexible substrate to determine whether attachment is complete. In another embodiment, the stethoscope (heart sound acquisition device) 601 can be directly attached to the skin 631 above the user's heart via the patch to measure heart sound signals.

[0142] Figure 6(b) shows a stethoscope (heart sound acquisition device) 601 according to another embodiment of the present invention, which includes a diaphragm 601a coated with a conductive material. The diaphragm 601 is encapsulated with a plastic frame (soundproof ring) 607 and a circuit board 605. A piezoelectric sensor 603 with multiple holes 640 is disposed below the soundproof ring 607 and electrically connected to the circuit board 605 via a line 604, and can be used to measure the voltage signal generated by vibration. This design allows sound to enter through the holes, without necessarily requiring contact with the human body for measurement.

[0143] In one embodiment, the size of the aperture in the piezoelectric sensor 603 ranges from 10μm to 1000μm. In another embodiment, in the integrated wearable heart sound acquisition device 601 with the aperture in the piezoelectric sensor 603, the distance d between the piezoelectric sensor 603 and the human skin 631 ranges from 0 to... <d<5cm。

[0144] The aforementioned sensors are primarily designed to receive signals, specifically heartbeat signals. The integrated wearable heartbeat acquisition device proposed in this invention can receive heartbeat signals using both capacitive and piezoelectric sensors. In this integrated wearable heartbeat acquisition device, the circuit board includes several amplifiers, filters, a power management system, an identification system, Bluetooth connectivity, and a processor.

[0145] Figure 7 The diagram shows the function of a stethoscope (heart sound acquisition device) 601, a wearable heart sound acquisition device 601 that can obtain heart sound signals from the human body through a capacitive sensor 701 and a piezoelectric sensor 703, respectively. This wearable body sound acquisition device 601 can receive and transmit data and execute software applications, and includes a microprocessor, a storage unit, and a wireless transmission module.

[0146] The microprocessor 725 may be a microcontroller, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic circuit, or other digital data processing device that executes instructions to perform processing operations according to the present invention. The microprocessor 725 may execute various application programs stored in the storage unit, including executing firmware algorithms.

[0147] Storage unit 727 may include read-only memory (ROM), random access memory (RAM), electrically erasable programmable ROM (EEPROM), flash memory, or any memory commonly used in computers.

[0148] The wireless transmission module 729 is connected to the antenna 729a, which is configured to transmit output data and receive input data via a wireless communication channel. The wireless communication channel can be a digital wireless communication channel, such as WiFi, Bluetooth, RFID, NFC, 3G / 4G / 5G, or any other future wireless communication interface.

[0149] The aforementioned capacitive sensor 701 and piezoelectric sensor 703 individually acquire heart sound signals from the human body. These signals are amplified by first and second amplifiers 731 and 731a, respectively, and then filtered for noise by first and second low-pass filters 733 and 733a. The filtered heart sound signals are then converted from analog to digital signals by first and second analog-to-digital converters (ADCs) 735 and 735a, and processed by microprocessor 725 to obtain de-noising and stable heart sound signals. Microprocessor 725 can store the de-noising and stable ECG and body sound signals in a storage unit via instructions or programs, or transmit the signals to a mobile device, such as a smartphone, via wireless transmission module 729 for further analysis.

[0150] The battery pack 737 provides power to the wearable body audio acquisition device 601 and can work with the power management unit 739 to optimize power usage. In addition, the battery pack 737 can also be wirelessly charged via a charging coil 741.

[0151] In one embodiment, the microprocessor 725, storage unit 727, wireless transmission module 729, amplifiers 731, 731a, low-pass filters 733, 733a, analog-to-digital converters (ADCs) 735, 735a, and power management module 739 can be integrated into a single circuit module.

[0152] Based on Figures 2-7 and related embodiments, the present invention will establish a set of... Figure 1 The wearable heart sound detection system shown mainly consists of a heart sound acquisition device 601 and a mobile device (such as a smartphone or tablet) 103. It provides continuous monitoring of the heart's health during normal times, and in case of an emergency, it can send an alarm through the mobile device 103 to call for help. The system's execution flow is as follows: Figure 8 As shown.

[0153] First, in step S801, the stethoscope (heart sound acquisition device) 601 is confirmed to be attached to a user's body 10. If it is not fully attached, the mobile device 103 will continuously notify (step S802). The next step will only proceed if the attachment is confirmed to be complete. Next, in step S803, the user's biometrics are collected. Then, in step S804, the collected biometrics are used to confirm the user's identity. After confirming the identity, the next step S805 is performed. In this step, the wearable stethoscope (heart sound acquisition device) 601 is used to acquire the user's heartbeat signal, including heart sound signal collection. Next, in step S806, the heart sound signal is filtered and amplified. In step S807, a preliminary heart rhythm analysis is performed. After the heart rhythm analysis, in step S808, it is first checked for any emergency situations. If there are any problems (such as no heartbeat is detected...), The system immediately connects to mobile device 103 for comparison with other sensors (step S809). If a critical situation is identified, mobile device 103 immediately issues an alarm (step S810). If normal, the heart sound signal is handed over to mobile device 103 for detailed signal processing and signal collection continues (step S811). After receiving a normal heart sound signal, mobile device 103 performs signal processing, such as filtering, wavelet analysis, Fourier transform, etc., and extracts heart sound signal feature points (step S812). Then, in step S813, the feature points are compared with the database and previous data using artificial intelligence (AI) to classify the situation and understand whether there are any abnormal signs. Then, in step S813, the results of the above comparison and situation classification are transmitted to the database for archiving as a reference for subsequent comparisons and are handed over to medical units for interpretation and to provide medical-related advice. In one embodiment, the above database can be a cloud database built on a cloud server.

[0154] In one embodiment, the aforementioned AI comparison and condition classification are performed by an AI algorithm installed on the mobile device 103 to initially classify normal and abnormal heart sound signals. The AI ​​algorithm may include a series of steps: pre-filtering and normalizing the input heart sound signal, extracting time-domain and frequency-domain features, and outputting the classification result using a Convolutional Neural Network (CNN) model. In one embodiment, the pre-filtering and normalization of the heart sound signal are performed using software computation.

[0155] Figure 9The diagram illustrates the wireless charging functionality of this invention. The stethoscope (heart sound acquisition device) charging device 900 includes a battery 904 and multiple wireless transmitting coils 902, which can be paired with, for example, multiple stethoscopes (heart sound acquisition devices) 601. Wireless charging (also known as inductive charging) utilizes inductive coupling, whereby the stethoscope charging device 900 transfers energy to the heart sound acquisition device 601, charging the battery 737 of the heart sound acquisition device 601 via the charging coil 741. Energy is transferred between the stethoscope charging device 900 and the stethoscope (heart sound acquisition device) 601 via inductive coupling, eliminating the need for a wired connection. The Wireless Power Consortium (WPC) Qi standard, or the AirFuel Alliance (AFA) AirFuelResonant (A4WP) and AirFuel Inductive (PMA) standards can be used. The contactless design avoids the risk of electric shock. In implanted medical devices, the device can be charged without damaging body tissue, eliminating the need for wires to pass through the skin and other tissues, thus avoiding the risk of infection. No wire connection is required during charging; simply placing the device near the charger is sufficient. The stethoscope charging device 900 of this invention can simultaneously charge multiple heart sound acquisition devices 601, eliminating the need for multiple chargers, power outlets, and tangled wires when multiple devices are in use.

[0156] The stethoscope charging device 900 has built-in control circuitry for power transmission and reception, eliminating the need for an external microcontroller. This makes it suitable for wearable devices with long-term wearability and large battery capacity. In one embodiment, a high-frequency band of 13.56MHz is used, thus also supporting the same frequency-based contactless communication standard, Near Field Communication (NFC).

[0157] In another embodiment, the plurality of wireless transmitting coils 902 can be partially overlapped. This is beneficial for mitigating misalignment errors when the stethoscope (heart sound acquisition device) 601 is placed on the charging pad. Even with slight positional errors, the stethoscope (heart sound acquisition device) 601 can still be effectively charged when placed on the charging pad. Please refer to [link to relevant documentation]. Figure 10 .

[0158] This invention mainly discloses a wearable physiological parameter sensing system for real-time monitoring of key physiological signals of the human body, including heart sounds, electrocardiogram, blood oxygen concentration, and blood pressure, or any combination thereof.

[0159] Of the key physiological signals mentioned above, heart sounds, electrocardiogram (ECG), and blood oxygen saturation can be directly measured by sensors, while blood pressure requires the pulse transit time (PTT) to be obtained from ECG, pulse wave (PPG), and blood oxygen saturation signals.

[0160] The heart's function reveals a wealth of valuable information about the human body. In conventional medical devices, monitoring heart rate and cardiac activity is accomplished by measuring electrophysiological signals and performing an electrocardiogram (ECG). Electrodes are attached to the body to measure signals of electrical activity generated in the heart tissue. Furthermore, a pressure wave travels through blood vessels with each heartbeat, slightly altering the vessel diameter. Therefore, in addition to ECG, pulse waves can be obtained by measuring the photoplethysmography (PPG) of blood flow using a light source and photoelectric sensors. The pulse wave measured using this technique is thus called a PPG signal, an optical technology that obtains information about cardiac function without measuring bioelectrical signals. PPG technology is primarily used to measure blood oxygen saturation (SpO2), but it can also provide information about cardiac function without bioelectrical signal measurement. Using PPG technology, heart rate monitors can be integrated into wearable devices for continuous monitoring applications.

[0161] Please see Figure 11 As shown, the pulse wave transit time (PTT) 1106 can be obtained by comparing the pulse wave signal (PPG) 1102 and the electrocardiogram (ECG) signal (ECG) 1104. Based on the individual physiological characteristics of the pulse wave signal (PPG) 1102 and the electrocardiogram (ECG) signal (ECG) 1104, the peak value of the ECG signal (ECG) 1102 comes from the contraction of the ventricle, while the peak value of the pulse wave signal (PPG) 1104 is caused by vasoconstriction. Therefore, we can obtain the transit time of blood from the heart to the measurement site, which is the pulse wave transit time (PTT) 1106. Specifically, widely used methods for obtaining pulse wave transit time (PTT) include measuring the time delay between the R peak (marked by the dashed line) of the electrocardiogram (ECG) signal 1102 and characteristic points of the pulse wave signal (PPG) 1104, such as the pulse wave signal (PPG) peak (marked by the dashed line), and utilizing the time delay required for the pressure pulse to travel from the proximal to the distal end. Similarly, pulse wave transit time (PTT) can also be obtained by comparing the pulse wave signal (PPG) 1102 with the heart sound signal.

[0162] Since the speed of pulse wave transmission is directly related to blood pressure, the pulse wave transmission is faster when blood pressure is high and slower when blood pressure is low. Therefore, the pulse wave transmission time (PTT) can be obtained by using the electrocardiogram (ECG) signal (1102) and the pulse wave signal (PPG) (1104). By adding some conventional body parameters (such as height and weight), the pulse wave transmission speed can be obtained. By establishing a characteristic equation, the systolic and diastolic blood pressure of the human pulse can be estimated, and non-invasive continuous blood pressure measurement can be achieved.

[0163] Figure 2 shows the blood pressure measurement method 1200 disclosed in this invention, which includes the following steps: First, in step S1201, the heart sound sensing device 1302, the electrocardiogram sensing device 1304 (e.g., an ECG patch (ECG+, ECG-)) and the pulse oximeter 306 (i.e., a pulse wave signal sensing device) of the wearable physiological parameter sensing system 1300 (refer to Figure 13A) respectively sense a user's heart sound signal, electrocardiogram signal and blood oxygen signal, wherein the blood oxygen... The signals include blood oxygen concentration and pulse wave signals (e.g., fingertip pulse wave signals); then, in step S1202, the pulse wave transit time (PTT) is calculated by comparing the blood oxygen signal (pulse wave signal) with the electrocardiogram signal or by comparing the blood oxygen signal (pulse wave signal) with the heart sound signal; next, in step S1203, the user's blood pressure is determined using an artificial intelligence (AI) algorithm; and then, in step S1204, the blood pressure value is obtained based on the results of the AI ​​algorithm.

[0164] According to embodiments of the present invention, the aforementioned artificial intelligence (AI) algorithm for blood pressure prediction is a method based on pulse wave propagation time and pulse wave propagation velocity. This method primarily utilizes the time-domain characteristics of the accelerated pulse wave, pulse wave propagation time (PTT), and the user's height parameters to jointly establish a multivariate linear model.

[0165] Figure 13A shows a cross-sectional schematic diagram of a wearable physiological signal sensing system 1300 disclosed according to an example of the present invention. It includes a circuit board 1301, a stethoscope 1302 and multiple ECG patches 1304 disposed on a first surface (lower surface) 1301a of the circuit board 1301, and a pulse oximeter 1306 disposed on a second surface (located on the opposite side of the first surface, i.e., the upper surface) 1301b of the circuit board 1301. For ease of wear, the wearable physiological signal sensing system 1300 can be attached to the chest of a user 10 in the form of patches. Specifically, when using the wearable physiological signal sensing system 1300, multiple ECG patches 1304 (e.g., a pair of ECG+ and ECG- electrodes) are attached to the skin of the user 10's chest.

[0166] In one embodiment, the stethoscope 1302 includes a diaphragm 1302a coated with a conductive material. The diaphragm 1302a is encapsulated with a plastic frame (sound-insulating ring) 1302b and the circuit board 1301 (the resonant cavity formed by the sound-insulating ring 1302b and the circuit board 1301, combined with the diaphragm 1302a, forms a microphone structure). A piezoelectric sensor 1302c is disposed below the sound-insulating ring and connected to a circuit board (not shown) via a circuit. By contacting the user's skin, it can measure the voltage signal generated by vibration. That is, the piezoelectric sensor 1302c can serve as another diaphragm to assist conventional capacitive sensors in addressing the poor response to low-frequency signals, such as the frequencies of the third and fourth heart sounds (around 20Hz).

[0167] The main component of the microphone described above is a typical capacitive sensor. It utilizes an ultra-thin material as a diaphragm 1302a (e.g., 30μm thick glass), coated with a conductive material, and encapsulates this diaphragm 302a with a frame adhesive 1302b to form a resonant chamber on a circuit board 1301. The purpose is to use the sound emitted by a heartbeat to vibrate the diaphragm 1302a, causing a capacitance change between the diaphragm 1302a and the circuit board 1301. The stethoscope 1302 (heart sound acquisition device) captures this change to record the heart sound signal.

[0168] The aforementioned piezoelectric sensor 1302c mainly consists of a piezoelectric material layer (e.g., a polyvinylidene fluoride (PVDF) polymer piezoelectric film, lead zirconate titanate (PZT), etc.), with conductive metals (e.g., aluminum (Al), copper (Cu), etc.) plated on its upper and lower surfaces. A lead is extended from each of the upper and lower metal layers to connect to a circuit board, which can be used to measure the voltage signal generated by vibration. In one embodiment, the thickness of the piezoelectric sensor is less than 50 μm.

[0169] In one embodiment, the stethoscope 1302 is used to measure the heart sound signal of the user 10. In one embodiment, the plurality of ECG patches 1304 include at least two electrodes, namely ECG+ and ECG-, for measuring the user's ECG signals. In one embodiment, the pulse oximeter 1306 is used to measure the PPG signal and blood oxygen saturation (SpO2) of the user 10. According to an embodiment of the present invention, the pulse oximeter 1306 includes an infrared light source (infrared LED), a red light source (red LED), and a photosensor for sensing the PPG signal of the user 10's fingertip, i.e., the fingertip pulse wave.

[0170] As shown in Figure 13(a), the stethoscope 1302 and multiple ECG patches 1304 in the wearable physiological signal sensing system 1300 are attached to the chest of the user 10. The stethoscope and multiple ECG patches 1304 are used to capture heart sound signals and ECG signals, respectively. The operation of the wearable physiological signal sensing system 1300 includes: (1) attaching the wearable physiological signal sensing system 300 to the chest of the user 10 to obtain the heart sound and electrocardiogram information of the user 10, and continuously monitoring the heart sound signal (PCG signals) and electrocardiogram signal (ECG signals) of the user 10; (2) pressing the pulse oximeter with the user's finger to obtain the pulse wave signal (PPG) and blood oxygen concentration (non-continuous monitoring, wherein the PPG signal and blood oxygen saturation (SpO2) are monitored only when information is needed); (3) obtaining the pulse wave transit time (PTT) from the heart to the finger of the user 10, and obtaining the blood pressure of the user 10 after calculation by the artificial intelligence (AI) algorithm (non-continuous monitoring).

[0171] Figure 13(b) shows a cross-sectional schematic diagram of a wearable physiological signal sensing system 1300a disclosed according to another example of the present invention, which includes a circuit board 1301. A stethoscope 1302 and a first ECG patch 1304a are disposed on a first surface (lower surface) 1301a of the circuit board 1301, and a pulse oximeter 1306 and a second ECG patch 1304b (integrated together) are disposed on a second surface 1301b of the circuit board 1301 (located on the opposite side of the first surface, i.e., the upper surface). In one embodiment, the stethoscope 1302 has the same structure as the stethoscope described in Figure 13A above, and will not be described again here. In one embodiment, the stethoscope 1302 is used to measure the heart sound signal of the user 110. In one embodiment, the first ECG patch 1304a and the second ECG patch 1304b are one of two electrodes (ECG+ and ECG-), respectively, and are disposed on opposite sides of the circuit board 1301 for measuring the ECG signals of the user 10. In another embodiment, the pulse oximeter 1306 is used to measure the PPG signal and blood oxygen saturation (SpO2) of the user 10.

[0172] As shown in Figure 13(b), the stethoscope and the first ECG patch 1304a in the wearable physiological signal sensing system 300a are attached to the chest of the user 10, while the second ECG patch 1304b is integrated with the pulse oximeter 1306 and is located on the opposite side of the stethoscope 1302. The stethoscope 1302 is used to capture heart sound signals. The first and second ECG patches (1304a, 1304b) are used to capture ECG signals, and the pulse oximeter 1306 is used to capture PPG signals and blood oxygen saturation (SpO2). The operation of the above-mentioned wearable physiological signal sensing system 1300a includes: (1) attaching the wearable physiological signal sensing system 100 to the user's chest to obtain the user's heart sound information and continuously monitor the user's heart sound signals (PCG signals); (2) the user 10 presses the pulse oximeter and one of the ECG electrodes (i.e., one of the first ECG patch or the second ECG patch) with their finger to obtain blood oxygen concentration, the user's fingertip pulse wave (PPG) signal and ECG signal (non-continuous monitoring, wherein the ECG signal, PPG signal and blood oxygen saturation (SpO2) are monitored only when information is needed); (3) obtaining the user 10's heart-to-finger PTT and obtaining the user 10's blood pressure after calculation by artificial intelligence (AI) algorithm (non-continuous monitoring).

[0173] Figure 13(c) shows a cross-sectional schematic diagram of a wearable physiological signal sensing system 1300 disclosed according to another example of the present invention, wherein the pulse oximeter 1306 and the electrocardiogram auscultation device 1303 are designed separately and electrically connected by a coaxial cable or metal wire. The electrocardiogram auscultation device 1303 comprises multiple electrocardiogram patches 1304, a stethoscope 1302, and a circuit board 1301. In this embodiment, the multiple electrocardiogram patches 1304 and the stethoscope 1302 of the electrocardiogram auscultation device 1303 are disposed on the same side of the circuit board 1301. The structure of the stethoscope 1302 is the same as that described in Figure 3(a), and will not be repeated here.

[0174] In this example, the stethoscope 1302 is used to measure the heart sound signal of the user 10; the multiple ECG patches 1304 include two electrodes (ECG+ and ECG-) for measuring the ECG signals of the user 10; and the pulse oximeter 1306 is used to measure the PPG signal and blood oxygen saturation (SpO2) of the user 10.

[0175] Referring to Figure 13(c), the ECG auscultation device 1303 is attached to the chest of the user 10 during use, while the pulse oximeter 1306 can be placed on the user's fingers, palms, wrists, forearms, thighs, calves, ankles, toes, ears, foreheads, or cheeks, but is not limited thereto.

[0176] Figure 13(d) shows a cross-sectional schematic diagram of a wearable physiological signal sensing system 300 disclosed according to another example of the present invention, wherein the pulse oximeter 1306 and the electrocardiogram auscultation device 1303 are designed separately and connected wirelessly (including Bluetooth, Wi-Fi, etc.). The structure and usage of the pulse oximeter 1306 and the electrocardiogram auscultation device 303 are the same as those in the example of Figure 3(c), and will not be repeated here.

[0177] According to an embodiment of the present invention, the pulse oximeter 1306 shown in Figures 13(a)-13(d) includes an infrared light source (infrared LED), a red light source (red LED), and a photosensor for sensing the fingertip PPG signal of the user 10, i.e., the fingertip pulse wave.

[0178] According to an embodiment of the present invention, the circuit board 1301 can be disposed on a flexible substrate. The flexible substrate is a fabric, polyisocyanate (PI), or polyethylene terephthalate (PET).

[0179] Figure 14 This is a functional block diagram of a wearable physiological signal sensing system 1400, in which a stethoscope 1302 can detect heart sound signals from the user's body; a pair of electrocardiogram (ECG) electrodes, namely an ECG patch 1304, can detect ECG signals from the user's body; and a pulse oximeter 1306 can detect PPG signals and blood oxygen saturation (SpO2). The aforementioned heart sound signals, ECG signals, and PPG signals can be individually filtered, amplified, and analog-to-digital converted through corresponding preprocessing channels 1411a, 1411b, and 1411c in the signal preprocessing circuit 411 to obtain preprocessed digital heart sound signals, ECG signals, and PPG signals. In one embodiment, each preprocessing channel includes a filter, a signal amplifier, and an analog-to-digital (A / D) converter.

[0180] The microprocessor 1415 can store the stable, noise-free heart sound signals, electrocardiogram (ECG) signals, and PPG signals in the storage unit 417 via instructions or programs, or transmit the signals to an external mobile device via the wireless transmission module 1419 for further analysis. The mobile device can be a smartphone. The microprocessor 1415 can calculate the pulse wave transit time (PTT) between the ECG signal and the PPG signal, or between the heart sound signal and the PPG signal, and deduce continuous blood pressure from the PTT, thus achieving the function of measuring continuous blood pressure. According to an embodiment of the present invention, the microprocessor 1415 can predict blood pressure using the aforementioned artificial intelligence (AI) algorithm.

[0181] The battery pack 1421 provides power to the integrated sensing device 1400 for heart sounds and electrocardiogram signals, and can be used in conjunction with the power management module 1423 to optimize power usage. The battery pack 1421 can also be wirelessly charged by the charging coil 1425.

[0182] In one embodiment, the aforementioned components, such as the microprocessor 1415, storage unit 1417, wireless transmission module, signal preprocessing circuit 1411, and power management module 1421, can be integrated into a single system circuit board, for example... Figure 3(a) , 3(b) In the circuit board 1301 shown.

[0183] In one embodiment, a user can view the acquired electrocardiogram (ECG), phonocardiogram (PCG), and PPG data via an externally connected computing device, and further analyze and compare the data. This externally connected computing device can be a smartphone, tablet, or cloud server.

[0184] As shown in Figure 15(a), according to one embodiment of the present invention, a wearable physiological signal sensing system 1500 includes a circuit board 1301 (refer to Figure 3(a)). A stethoscope 1302 and multiple ECG patches 1304 are disposed on a first surface (lower surface) 1301a of the circuit board 1301, and a pulse oximeter 1306 is disposed on a second surface (located on the opposite side of the first surface, i.e., the upper surface) 1301b of the circuit board 1301. The system is worn by a user 10 and communicatively connected to a mobile device (e.g., a smartphone, tablet, or other external computing electronic device) 1503. Physiological data (including heart sound signals, ECG signals, pulse oximetry signals, and blood pressure signals) collected by the wearable physiological signal sensing system 1500 can be wirelessly transmitted (e.g., via Bluetooth, WiFi, or other wireless communication methods) from the mobile device 1503 to a cloud server 1507 via a cloud network 1505. The data is stored in a cloud database on the cloud server. The system also includes an application installed on a mobile device that contains instructions for receiving and sending data between the wearable physiological signal sensing system 1500, the mobile device 1503, and the cloud server 1507. This application can operate on Android, Windows 10, or iOS operating system platforms and can upload collected data / signals, such as electrocardiogram signals, heart sound signals, blood oxygen signals, and their waveforms, to the cloud server 507 for storage. It then uses data analysis and feature extraction algorithms to analyze and process the data, generating evaluation reports and providing medical advice accordingly.

[0185] Considering that older adults are not familiar with using mobile devices, such as smartphones / tablets and other external electronic devices, according to another embodiment of the present invention, referring to Figure 5(b), an embedded SIM card (eSIM) is disposed on the circuit board 1301 of the wearable physiological signal sensing system 1500 (referring to Figure 3(a)), embedded inside the device (i.e., inside the wearable physiological signal sensing system 500). Physiological data (including heart sound signals, electrocardiogram signals, blood oxygen signals, and blood pressure signals) collected by the wearable physiological signal sensing system 1500 can be directly uploaded to the cloud server 1507 via the cloud network 1505 through wireless transmission of the eSIM card. In the cloud server 1507, the data will be stored in a cloud database. The eSIM card can be configured in hardware, firmware, or software.

[0186] Figure 16 This is a functional block diagram showing the processing system 1650 of the mobile device 1503 or the processing system 1650 running as a computing system executing as a cloud server 1507. Specifically, the processing system 1650 represents the processing system in the mobile device 1503 or the computing system executing as a cloud server 1507 (FIG. 15), which executes instructions to perform computational processing according to embodiments of the present invention, such as executing the previously described algorithm for detecting cardiac abnormalities and extracting ECG signal features. Those skilled in the art will understand that the above instructions can be stored and / or executed as hardware, software, or firmware without departing from the spirit of the invention. Furthermore, those skilled in the art will understand that the exact configuration of each processing system may differ, and the processing system 650 shown in FIG. 6 is merely an example.

[0187] In one embodiment, a mobile device 1503 is coupled to an edge computing device instead of a cloud server 1507. The aim is to reduce the amount of computation performed remotely, thereby minimizing long-distance communication between the client and server. Edge computing brings enterprise applications closer to data sources such as IoT devices, offering significant advantages including reduced response times and better bandwidth availability. Edge computing on 5G networks and mobile edge computing enable faster and more comprehensive data analysis. Therefore, in a preferred embodiment, data such as heart sounds, ECGs, and pulse waves are processed by the edge computing device using a 5G or 6G network; tasks that the edge computing device cannot handle are transmitted to an external cloud computing device. The edge computing architecture can be divided into: a "device layer" for data acquisition, an "edge layer" for real-time data processing, and a "cloud layer" responsible for secure storage and in-depth analysis. In this embodiment, each sensing device acquires physiological data through built-in sensors. In one embodiment, collected relevant data / signals, such as electrocardiogram (ECG) signals, heart sound signals, blood oxygenation signals, and their waveforms, are uploaded to an edge computing device, where they are analyzed using data analysis and feature extraction algorithms. The "edge layer," being closest to the data generation location, has a wider distribution range than traditional cloud servers. This enables real-time data processing and analysis, significantly reducing latency.

[0188] If the data requires further analysis, it will be uploaded to cloud server 1507 for further analysis. Although edge computing solves the bottleneck and latency problems of cloud computing, when the "edge layer" determines that certain data requires more detailed analysis, it will send the data to the "cloud" for deeper processing and storage.

[0189] The processing system 1650 includes a processor 1601, main memory 1602, a wireless transceiver 1603 (including a Bluetooth module, a near field communication (NFC) module, and a wireless network interface), a control device 605 (such as a keyboard and indicator device), a video display 607, an input / output (I / O) device 609, and a signal generating device 1613 for a communication connection bus 6011.

[0190] Main memory 1602, wireless transceiver 1603, video display 1607, input / output (I / O) device 1609, and any number of other peripheral devices are connected to microprocessor 1601 and exchange data with processor 1601 via bus 6011 for use in applications executed by processor.

[0191] A wireless transceiver 1603 is connected to an antenna and is configured to transmit and receive voice and data signals via a wireless telecommunication channel. In one embodiment, the wireless telecommunication channel can be a digital wireless telecommunication channel, such as WiFi, Bluetooth, RFID, NFC, 3G / 4G / 5G, eSIM, or any other future wireless communication interface. A video display 1607 receives display data from the processor 1601 and displays images on the screen for the user to view. The video display 1607 can be a liquid crystal display (LCD) or an organic light-emitting diode (OLED) display.

[0192] Main memory 1602 is a means of sending and receiving data to and from processor 1601 and storing the data. Main memory 1602 may include non-volatile memory, such as read-only memory (ROM), which stores the necessary instructions and data to operate individual subsystems of the processing system and to boot the system at startup. Those skilled in the art will understand that any number of memory units can be used to perform this function. Main memory 1602 may also include volatile memory, such as random access memory (RAM), which stores the instructions and data required by processor 1601 to execute software instructions for computational processing (such as the computational processing required by the system according to the invention). Those skilled in the art will understand that any type of memory can be used as volatile memory, and the exact type used is left to those skilled in the art as a design choice.

[0193] The Bluetooth module allows the processing system 1650 to establish communication with devices such as the wearable stethoscope device 1101 based on the Bluetooth technology standard. The Near Field Communication (NFC) module allows the integrated sensing device 1500 for heart sounds and electrocardiogram signals to establish wireless communication with another similar device by bringing them close together or near each other. Other peripheral devices that can be connected to the processor 601 include a Global Positioning System (GPS) and other positioning transceivers.

[0194] Processor 1601 is a processor, microprocessor, or any combination of processor and microprocessor, which executes execution processing instructions according to the present invention. Processor 1601 is capable of executing various applications stored in the storage unit. These applications can receive user input via a display with a touch screen or directly from a keyboard area. Some applications stored in main memory 1602 that can be executed by processor 1601 can be applications developed for UNIX, Android, iOS, Windows, Blackberry, or other platforms.

[0195] This invention utilizes a patch method to attach a wearable physiological signal sensing system to the skin, allowing direct measurement of desired physiological signals such as heart sounds, electrocardiogram (ECG), and blood oxygen saturation. This method eliminates the need to attach the sensing system to clothing; however, this method requires clothing for signal measurement, and the measurement is susceptible to noise interference caused by clothing friction, affecting the accuracy of the received signals. Noise reduction technology is required to filter out noise, which adds extra cost.

[0196] Preferably, the stethoscope can also be used to receive lung sounds; therefore, the present invention can be used to monitor lung sounds for respiratory sound analysis and respiratory health assessment. Similarly, when the device is attached to the periphery of the intestines, intestinal peristalsis sounds can also be monitored using a stethoscope. Clearly, the present invention provides for monitoring motility frequency, intensity analysis, and assessment of gastrointestinal function.

[0197] This invention provides multimodal data integration, such as the system being able to simultaneously acquire the user's body temperature, phonocardiogram (PCG), electrocardiogram (ECG), pulse wave (PPG), and blood oxygen saturation (SpO2). The user's body temperature is acquired via a body temperature sensor 1306a (refer to Figures 13(a), 13(b), 13(c), 13(d), and...). Figure 14 By fusing and analyzing multimodal features such as the RR interval of electrocardiogram, the S1-S2 interval of heart sound, the rise time of pulse wave, and changes in blood oxygen saturation, an artificial intelligence (AI) prediction model is constructed.

[0198] The multimodal data obtained by this invention improves the accuracy and stability of blood pressure estimation, which is beneficial for cardiovascular health risk assessment (e.g., detecting early signs of arrhythmia and valvular disease), monitoring respiratory health status (e.g., blood oxygen saturation and heart sound changes as indicators of respiratory abnormalities), and analyzing physiological stress load (e.g., estimating physical fatigue status from heart sound fatigue status and electrocardiogram changes).

[0199] Based on the above characteristics, this invention provides novel heart sound analysis functions, such as delay time analysis: the time interval between S1 and S2 can be used to perform preliminary detection of valvular disease and arrhythmia; heart sound variability analysis: statistically analyze the changes in the time interval between multiple heart sounds for stress response analysis; trend change monitoring: long-term S1 and S2 change trends can be used as cardiovascular health indicators.

[0200] In addition to the advantages mentioned above, the present invention also has the following technical features that are superior to any prior art, such as in terms of equipment and application: (1) The pulse oximeter module of the present invention has independent operation capability. The pulse oximeter module (including PPG sensing) can be an independent device with the functions of recording, storing and uploading heart rate and blood oxygen data. The independent pulse oximeter device can be configured on any part of the human body where PPG can be measured, including fingers, wrists, arms, etc., and has wireless transmission capability, and can perform monitoring tasks independently without relying on the main device. (2) Telemedicine application: The present invention can be applied to telemedicine related applications, such as home physiological monitoring for patients with chronic diseases (such as hypertension, cardiopulmonary diseases). Medical units can remotely receive data such as heart sounds, blood pressure, SpO2, and HR for health tracking, abnormal warning and remote intervention, highlighting the value of the present invention in telemedicine and long-term care applications.

[0201] In terms of signal processing and AI algorithms: (1) Extensibility of multimodal models in disease detection: The multimodal signal model of this invention (integrating PCG, ECG, PPG, SpO2, etc.) can be applied to the detection and risk analysis of various diseases such as arrhythmia, heart failure, valvular disease, abnormal lung sounds, and sleep apnea, and improves the accuracy of model prediction. (2) Benefits of multimodal data in signal noise reduction: This invention can perform dynamic filtering and noise reduction through cross-comparison of multimodal signals (e.g., ECG and PCG time series, PPG and SpO2 trends), reduce noise caused by motion, poor contact or external interference, improve signal stability and data credibility, and enhance the accuracy of subsequent analysis and diagnosis. The application of the multimodal AI model of this invention can integrate PCG, ECG, PPG, SpO2, etc. for disease detection and risk prediction. The algorithm and architecture of the multimodal AI model can be applied to arrhythmia, abnormal lung sounds, sleep apnea, etc., to improve the ability to analyze various physiological states.

[0202] The above description is a preferred embodiment of the present invention. Those skilled in the art should understand that it is used to illustrate the invention and not to limit the scope of the patent rights claimed by the invention. The scope of patent protection shall be determined by the appended claims and their equivalents. Any modifications or refinements made by those skilled in the art without departing from the spirit or scope of this patent are equivalent changes or designs made under the spirit disclosed in this invention and should be included within the scope of the following claims.

Claims

1. A wearable physiological signal sensing system, characterized in that, include: The system circuit board has upper and lower surfaces; A stethoscope, located on the lower surface, is electrically connected to the system circuit board and is used to sense the user's heart sounds, lung sounds, and bowel sounds. and ECG electrodes are disposed on the lower surface to sense the user's ECG signal.

2. The wearable physiological signal sensing system as claimed in claim 1, characterized in that, Includes a pulse oximeter, disposed on the upper surface, for sensing the user's blood oxygen concentration and pulse wave signal; wherein the blood oxygen concentration and pulse wave signal are acquired while the user presses the pulse oximeter.

3. The wearable physiological signal sensing system as described in claim 2, characterized in that, This includes comparing the electrocardiogram signal with the pulse wave signal, or comparing the heart sound signal with the pulse wave signal, to obtain the user's pulse wave transit time in order to estimate the user's continuous blood pressure.

4. The wearable physiological signal sensing system as described in claim 3, characterized in that, This continuous blood pressure data is used to predict blood pressure using artificial intelligence (AI) algorithms.

5. The wearable physiological signal sensing system as claimed in claim 4, characterized in that, The artificial intelligence algorithm uses the time-domain characteristics of the pulse wave signal, the pulse wave transmission time, and the user's height to establish a multivariate linear model.

6. The wearable physiological signal sensing system as claimed in claim 1, characterized in that, The stethoscopes mentioned above include: A diaphragm is disposed on the lower surface of the system circuit board; A sound-insulating ring surrounds the diaphragm and forms a resonant cavity with the system circuit board; and A piezoelectric sensor is mounted on the system circuit board and is attached to the user's skin.

7. The wearable physiological signal sensing system as claimed in claim 1, characterized in that, The wearable physiological signal sensing system connects to external mobile devices, cloud servers, or edge computing devices to facilitate the transmission of physiological signals.

8. The wearable physiological signal sensing system as claimed in claim 7, characterized in that, It also includes an e-SIM mounted on the system circuit board, through which the wearable physiological signal sensing system connects to one of the external mobile devices, cloud servers, or edge computing devices to facilitate the transmission of physiological signals.

9. The wearable physiological signal sensing system as claimed in claim 1, characterized in that, The stethoscope collects biometric data.

10. The wearable physiological signal sensing system as claimed in claim 1, characterized in that, The stethoscope analyzes the heart rate to determine if it is an emergency.

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