CN117678988B - Blood pressure measuring method and electronic equipment - Google Patents

Abstract

The present application discloses a blood pressure measurement method and an electronic device, the method comprising: obtaining a first pressure signal on the radial artery of a target object and a second pressure signal on the ulnar artery of the target object; determining a waveform phase difference between the first pressure signal and the second pressure signal, a cardiac cycle corresponding to the first pressure signal, a first difference between the contraction amplitude of the first pressure signal and the contraction amplitude of the second pressure signal, and a second difference between the diastolic amplitude of the first pressure signal and the diastolic amplitude of the second pressure signal; determining a pulse time difference between the radial artery and the ulnar artery based on the waveform phase difference, the cardiac cycle, the first difference, and the second difference; determining the diastolic pressure of the target object and the systolic pressure of the target object based on the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery. Through the present application, the accuracy of blood pressure measurement can be improved.

Description

Blood pressure measuring method and electronic device

Technical Field

The embodiments of the present application relate to the field of computers, and in particular to a blood pressure measurement method and an electronic device.

Background Art

Blood pressure is an important physiological parameter that reflects the state of the human cardiovascular system, and blood pressure monitoring is an indispensable part of personal health management. At present, the incidence of hypertension in the population is increasing, and it often causes complications such as heart disease and stroke, which seriously threatens human health. Therefore, early screening and daily monitoring of hypertension are essential. Common blood pressure measurement methods can be divided into cuff type and cuffless type. Cuff-type blood pressure measurement requires the cuff to be inflated and deflated to measure blood pressure. It can only provide a snapshot of dynamic blood pressure, but cannot provide continuous changes in blood pressure during the day and night, and the wearing comfort is poor. Therefore, it is particularly important to develop a cuffless blood pressure measurement method suitable for continuous blood pressure monitoring.

For cuffless blood pressure measurement methods, photoelectric method (photoplethysmography (PPG)), photoelectric-electrocardiogram (PPG-electrocardiogram (ECG)), etc. can be used. Among them, PPG is to determine blood pressure data by emitting a photoelectric signal to the skin and collecting the pulse wave at the wrist through the sensor; PPG-ECG is based on the emission of photoelectric signals, and adds a guide to collect ECG signals, and the blood pressure data is determined by the combination of the two collected signals. However, due to the accuracy of the sensor and the defects of the processing circuit, signal distortion and information loss will occur, thereby reducing the accuracy of blood pressure measurement.

Summary of the invention

The present application provides a blood pressure measurement method and electronic equipment, which can improve the accuracy of blood pressure measurement.

In a first aspect, the present application provides a blood pressure measurement method, comprising: obtaining a first pressure signal on the radial artery of a target object and a second pressure signal on the ulnar artery of the target object; determining a waveform phase difference between the first pressure signal and the second pressure signal, a cardiac cycle corresponding to the first pressure signal, a first difference between the contraction amplitude of the first pressure signal and the contraction amplitude of the second pressure signal, and a second difference between the diastolic amplitude of the first pressure signal and the diastolic amplitude of the second pressure signal; determining a pulse time difference between the radial artery and the ulnar artery based on the waveform phase difference, the cardiac cycle, the first difference, and the second difference; determining the diastolic pressure of the target object and the systolic pressure of the target object based on the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery.

Based on the method described in the first aspect, after the second electronic device obtains the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object, it analyzes the first pressure signal and the second pressure signal to determine four parameters, namely, the waveform phase difference between the first pressure signal and the second pressure signal, the cardiac cycle corresponding to the first pressure signal, the first difference between the contraction amplitude of the first pressure signal and the contraction amplitude of the second pressure signal, and the second difference between the diastolic amplitude of the first pressure signal and the diastolic amplitude of the second pressure signal; the pulse time difference between the radial artery and the ulnar artery is determined by these four parameters to calibrate the waveform phase difference; finally, the diastolic pressure and the systolic pressure of the target object are determined using the characteristic information in the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery. Since the pulse time difference between the radial artery and the ulnar artery has been calibrated, the parameters affecting blood pressure (i.e., characteristic information in the waveform of the first pressure signal, the contraction amplitude of the first pressure signal, the relaxation amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery) are used together with the pulse time difference to establish a model to further optimize the parameters, thereby improving the accuracy of blood pressure measurement.

In a possible implementation, the pulse time difference between the radial artery and the ulnar artery is determined based on the waveform phase difference, the cardiac cycle, the first difference, and the second difference, including: calling a first model to process the waveform phase difference, the cardiac cycle, the first difference, and the second difference to obtain the pulse time difference between the radial artery and the ulnar artery; the first model is trained based on a first training sample and a corresponding pulse time difference label. Based on this method, the accuracy of the pulse time difference between the radial artery and the ulnar artery can be improved.

In a possible implementation, the diastolic pressure and the systolic pressure of the target object are determined based on the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery, including: determining first information based on the waveform of the first pressure signal, the first information including the peak amplitude to trough amplitude ratio, the pulse wave amplitude ratio, the area enclosed by the dicrotic wave peak to the end point curve, and the arteriosclerosis index; determining the diastolic pressure and the systolic pressure of the target object based on the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery. Based on this method, the accuracy of blood pressure measurement can be improved.

In a possible implementation, based on the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery, the diastolic pressure of the target object and the systolic pressure of the target object are determined, including: calling a second model to process the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the diastolic pressure of the target object; the second model is trained based on the second training sample and the corresponding diastolic pressure label; calling a third model to process the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the systolic pressure of the target object; the third model is trained based on the second training sample and the corresponding systolic pressure label. Based on this method, the accuracy of blood pressure measurement can be further improved.

In a possible implementation, obtaining a first pressure signal on the radial artery of a target object and a second pressure signal on the ulnar artery of the target object includes: obtaining a first original pressure signal on the radial artery of the target object, a second original pressure signal on the ulnar artery of the target object, and acceleration information of the target object within a preset time; determining the state of the target object based on the acceleration information; determining the first time when the target object is in motion; if the first time is less than or equal to a first preset threshold, aligning and splicing the first original pressure signal and the second original pressure signal according to the timestamp to obtain a third pressure signal; determining the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object based on the third pressure signal. Based on this method, it is possible to ensure that the target object is in a relatively static state, thereby improving the accuracy of blood pressure measurement.

In one possible implementation, obtaining a first pressure signal on the radial artery of a target object and a second pressure signal on the ulnar artery of the target object includes: receiving the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object from a second electronic device. Based on this method, multiple devices assist in processing, which can improve the efficiency of data processing.

In a possible implementation, determining a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object based on the third pressure signal includes: filtering the third pressure signal to obtain a fourth pressure signal; and blind source separation of the fourth pressure signal to obtain the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object. Based on this method, the interference between the first pressure signal and the second pressure signal can be reduced, and the accuracy of the first pressure signal and the second pressure signal can be improved.

In a possible implementation, determining the state of the target object based on the acceleration information includes: when the acceleration in the acceleration information is less than or equal to a second preset threshold, determining that the target object is in a stationary state; when the acceleration in the acceleration information is greater than the second preset threshold, determining that the target object is in a moving state. Based on this approach, the accuracy of determining the state of the target object can be improved.

In a second aspect, the present application provides a blood pressure measuring device, which may be an electronic device, or a device in an electronic device, or a device that can be used in combination with an electronic device; wherein the blood pressure measuring device may also be a chip system, and the blood pressure measuring device may execute the method executed by the electronic device in the first aspect. The functions of the blood pressure measuring device may be implemented by hardware, or by hardware executing corresponding software. The hardware or software includes one or more units corresponding to the above functions. The unit may be software and/or hardware. The operations and beneficial effects performed by the blood pressure measuring device may refer to the methods and beneficial effects described in the first aspect above, and the repeated parts will not be repeated.

In a third aspect, the present application provides an electronic device, comprising one or more processors and one or more memories. The one or more memories are coupled to the one or more processors, and the one or more memories are used to store computer program codes, and the computer program codes include computer instructions, and when the one or more processors execute the computer instructions, the blood pressure measurement device performs the blood pressure measurement method in any possible implementation of the first aspect.

In a fourth aspect, the present application provides a blood pressure measurement device, which includes a function or unit for executing any method described in the first aspect.

In a fifth aspect, the present application provides a computer-readable storage medium, which stores a computer program. The computer program includes program instructions. When the program instructions are executed on an electronic device, the electronic device executes the blood pressure measurement method in any possible implementation of the first aspect.

In a sixth aspect, the present application provides a computer program product. When the computer program product runs on a computer, it enables the computer to execute the blood pressure measurement method in any possible implementation of the first aspect above.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of a radial artery and an ulnar artery provided in an embodiment of the present application;

FIG2 is a schematic diagram of the hardware structure of a first electronic device provided in an embodiment of the present application;

FIG3 is a software structure block diagram of a first electronic device provided in an embodiment of the present application;

FIG4 is a schematic diagram of the hardware structure of a second electronic device provided in an embodiment of the present application;

FIG5 is a schematic diagram of a physical structure of a first sensor module and a second sensor module provided in an embodiment of the present application;

FIG6A is a schematic diagram of a smart watch provided in an embodiment of the present application;

6B is a schematic diagram of measuring pressure signals of radial artery and ulnar artery when a user wears a smart watch provided by an embodiment of the present application;

6C is a cross-sectional view of a smart watch provided by an embodiment of the present application when detecting pressure signals of the radial artery and the ulnar artery;

FIG7 is a flow chart of a blood pressure measurement method provided in an embodiment of the present application;

FIG8A is a schematic diagram of a blood pressure detection APP installed on a smart watch provided in an embodiment of the present application;

FIG8B is a schematic diagram of a blood pressure detection interface provided in an embodiment of the present application;

FIG8C is a schematic diagram of a blood pressure measurement interface provided in an embodiment of the present application;

FIG8D is a schematic diagram of another blood pressure detection interface provided in an embodiment of the present application;

FIG8E is a schematic diagram of another blood pressure detection interface provided in an embodiment of the present application;

FIG8F is a schematic diagram of another blood pressure detection interface provided in an embodiment of the present application;

FIG9 is a schematic diagram of a first original pressure signal, a second original pressure signal, and a third pressure signal provided in an embodiment of the present application;

FIG10A is a schematic diagram of a waveform phase difference between a first pressure signal and a second pressure signal provided in an embodiment of the present application;

FIG10B is a schematic diagram of a cardiac cycle corresponding to a first pressure signal provided in an embodiment of the present application;

10C is a schematic diagram of a first difference between a contraction amplitude of a first pressure signal and a contraction amplitude of a second pressure signal provided in an embodiment of the present application;

10D is a schematic diagram of a second difference between a diastolic amplitude of a first pressure signal and a diastolic amplitude of a second pressure signal provided in an embodiment of the present application;

FIG11A is a schematic diagram of a ratio of a peak amplitude to a trough amplitude provided in an embodiment of the present application;

FIG11B is a schematic diagram of a pulse wave amplitude ratio provided in an embodiment of the present application;

FIG11C is a schematic diagram of an area enclosed by a curve from the peak to the end point of a dicrotic wave provided in an embodiment of the present application;

FIG11D is a schematic diagram of an arteriosclerosis index provided in an embodiment of the present application;

FIG11E is a schematic flow chart of another blood pressure measurement method provided in an embodiment of the present application;

FIG12 is a flow chart of another blood pressure measurement method provided in an embodiment of the present application;

FIG13A is a schematic diagram of a health APP installed on a mobile phone provided in an embodiment of the present application;

FIG13B is a schematic diagram of a health data interface provided in an embodiment of the present application;

FIG13C is a schematic diagram of a blood pressure data interface provided in an embodiment of the present application;

FIG14 is a schematic diagram of the structure of a blood pressure measurement device provided in an embodiment of the present application;

FIG. 15 is a schematic diagram of the structure of a chip provided in an embodiment of the present application.

DETAILED DESCRIPTION

The technical solutions in the embodiments of the present application will be described clearly and in detail below in conjunction with the accompanying drawings. In the description of the embodiments of the present application, unless otherwise specified, "/" means or, for example, A/B can mean A or B; "and/or" in the text is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and/or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more.

The term "user interface (UI)" in the following embodiments of the present application refers to a medium interface for interaction and information exchange between an application or operating system and a user, which realizes the conversion between the internal form of information and the form acceptable to the user. The user interface is a source code written in a specific computer language such as Java and extensible markup language (XML). The interface source code is parsed and rendered on an electronic device, and finally presented as content that the user can recognize. The commonly used form of user interface is a graphical user interface (GUI), which refers to a user interface related to computer operations that is displayed in a graphical manner. It can be a visual interface element such as time, date, text, icon, button, menu, tab, text box, dialog box, status bar, navigation bar, widget, etc. displayed on the display screen of an electronic device.

In order to facilitate understanding of the solution provided by the embodiments of the present application, the following describes the relevant concepts involved in the embodiments of the present application:

1. Radial artery

As shown in Figure 1, the radial artery is one of the terminal branches of the brachial artery and is slightly smaller than the ulnar artery. After it is derived from the brachial artery, it first runs between the brachioradialis and pronator teres, and then descends between the brachioradialis tendon and the radial flexor carpi tendon. It is located superficially and its pulsation can be felt. It is the most commonly used pulse point in clinical practice.

2. Ulnar artery

As shown in Figure 1, the radial artery is one of the terminal branches of the brachial artery and is slightly larger than the radial artery. After being derived from the brachial artery, it descends along the radial side of the flexor carpi ulnaris, passes the radial side of the pisiform bone, and penetrates into the palm through the palmar ligament. Its terminal end anastomoses with the superficial branch of the radial artery to form the superficial palmar arch.

3. Blood pressure

Blood pressure refers to the lateral pressure exerted on the wall of a blood vessel per unit area when blood flows in the blood vessels. The blood pressure measured in the examination is generally the arterial blood pressure of the systemic circulation, including systolic pressure and diastolic pressure. Among them, systolic pressure is the pressure in the arteries when the heart beats; diastolic pressure is the pressure in the arteries when the heart rests between two beats. For each heartbeat, blood pressure varies between systolic pressure and diastolic pressure. Systolic pressure is the peak pressure in the arteries, which occurs near the end of the cardiac cycle when the ventricles contract. Diastolic pressure is the minimum pressure in the arteries, which occurs near the beginning of the cardiac cycle when the ventricles are filled with blood. The so-called cardiac cycle refers to the process that the cardiovascular system goes through from the beginning of one heartbeat to the beginning of the next heartbeat.

Blood pressure is an important physiological parameter that reflects the state of the human cardiovascular system. Blood pressure monitoring is an indispensable part of personal health management. At present, the incidence of hypertension in the population is increasing, and it often causes complications such as heart disease and stroke, which seriously threatens human health. Therefore, early screening and daily monitoring of hypertension are essential. Common blood pressure measurement methods can be divided into two types: cuff type and cuffless type. Cuff-type blood pressure measurement requires blood pressure measurement by inflating and deflating the cuff. It can only provide a snapshot of dynamic blood pressure, but cannot provide continuous changes in blood pressure during the day and night, and the wearing comfort is poor. Cuffless blood pressure measurement can measure blood pressure in real time, which can ensure continuous blood pressure monitoring and is more convenient for patients. Therefore, it is particularly important to develop a cuffless blood pressure measurement method suitable for continuous blood pressure monitoring.

Commonly used cuffless blood pressure measurement methods include photoelectric method (photoplethysmography (PPG)), photoelectric-electrocardiogram (PPG-electrocardiogram (ECG)), etc. Among them, PPG is to determine blood pressure data by emitting a photoelectric signal to the skin and collecting the pulse wave at the wrist through the sensor; PPG-ECG is based on the emission of photoelectric signals to the skin, and adds a guide for collecting ECG signals, and comprehensively determines blood pressure data through the two signals collected (i.e., the pulse wave at the wrist and the ECG signal). In addition, cuffless blood pressure measurement technology can also be embedded in wearable devices, smart phones and other devices to estimate blood pressure data through signal processing and algorithms. However, due to the accuracy of the sensor and the defects of the processing circuit, signal distortion, information loss, etc. will still occur, thereby reducing the accuracy of blood pressure measurement.

In order to improve the accuracy of blood pressure measurement, the present application provides a blood pressure measurement method and an electronic device. In a specific implementation, the electronic device may include a first electronic device 100 and a second electronic device 200. The above-mentioned blood pressure measurement method can be performed jointly by the first electronic device 100 and the second electronic device 200, or by the second electronic device 200, without limitation herein. The electronic device may be configured with a display screen and a preset application (application, APP) installed, and the user can measure the user's blood pressure through a preset APP (such as a blood pressure detection APP). The first electronic device 100 and the second electronic device 200 are introduced below.

(1) First electronic device 100

The first electronic device 100 can be a mobile phone, a tablet computer, a laptop computer, a desktop computer, a wireless terminal in a smart home, etc., but is not limited thereto. The hardware structure of the first electronic device 100 is introduced below. Please refer to Figure 2, which is a schematic diagram of the hardware structure of a first electronic device 100 provided in an embodiment of the present application.

The first electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, an air pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on the first electronic device 100. In other embodiments of the present application, the first electronic device 100 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

The processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and/or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

The controller may be the nerve center and command center of the first electronic device 100. The controller may generate an operation control signal according to the instruction operation code and the timing signal to complete the control of fetching and executing instructions.

A memory may also be provided in the processor 110 for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may store instructions or data that the processor 110 has just used or cyclically used. If the processor 110 needs to use the instruction or data again, it may be directly called from the memory. Repeated access is avoided, and the waiting time of the processor 110 is reduced, thereby improving the efficiency of the system. The processor 110 calls the instructions or data stored in the memory, so that the first electronic device 100 executes the blood pressure measurement method executed by the electronic device in the following method embodiment.

In some embodiments, the processor 110 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver/transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input/output (GPIO) interface, a subscriber identity module (SIM) interface, and/or a universal serial bus (USB) interface, etc.

The charging management module 140 is used to receive charging input from a charger, where the charger can be a wireless charger or a wired charger.

The power management module 141 is used to connect the battery 142, the charging management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and/or the charging management module 140 to power the processor 110, the internal memory 121, the external memory, the display screen 194, the camera 193, and the wireless communication module 160. In some other embodiments, the power management module 141 can also be set in the processor 110.

The wireless communication function of the first electronic device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in the first electronic device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve the utilization of the antennas. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.

The mobile communication module 150 can provide solutions for wireless communications including 2G/3G/4G/5G applied to the first electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the same device as at least some of the modules of the processor 110.

The modulation and demodulation processor may include a modulator and a demodulator. The modulator is used to modulate the low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After being processed by the baseband processor, the low-frequency baseband signal is transmitted to the application processor.

The wireless communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as Wi-Fi networks), Bluetooth (BT), BLE broadcast, global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), etc., applied on the first electronic device 100. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, modulates the frequency of the electromagnetic wave signal and filters it, and sends the processed signal to the processor 110. The wireless communication module 160 can also receive the signal to be sent from the processor 110, modulate the frequency of it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2.

In some embodiments, antenna 1 of the first electronic device 100 is coupled to mobile communication module 150, and antenna 2 is coupled to wireless communication module 160, so that the first electronic device 100 can communicate with the network and other devices through wireless communication technology.

The first electronic device 100 implements a display function through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, which connects the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs that execute program instructions to generate or change display information.

The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. In some embodiments, the first electronic device 100 may include 1 or N display screens 194, where N is a positive integer greater than 1.

The first electronic device 100 can realize the shooting function through ISP, camera 193, video codec, GPU, display screen 194 and application processor. ISP is used to process the data fed back by camera 193. Camera 193 is used to capture static images or videos. Digital signal processor is used to process digital signals, and can process other digital signals in addition to digital image signals. Video codec is used to compress or decompress digital video. The first electronic device 100 can support one or more video codecs.

NPU is a neural-network (NN) computing processor. It can quickly process input information by drawing on the structure of biological neural networks, such as the transmission mode between neurons in the human brain, and can also continuously self-learn.

The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the first electronic device 100. The external memory card communicates with the processor 110 via the external memory interface 120 to implement a data storage function.

The internal memory 121 can be used to store computer executable program codes, which include instructions. The processor 110 executes various functional applications and data processing of the first electronic device 100 by running the instructions stored in the internal memory 121. The internal memory 121 may include a program storage area and a data storage area. Among them, the program storage area may store an operating system, an application required for at least one function (such as a sound playback function), etc. The data storage area may store data (such as audio data) created during the use of the first electronic device 100, etc. In addition, the internal memory 121 may include a high-speed random access memory, and may also include a non-volatile memory, such as a flash memory device, etc.

The first electronic device 100 can implement audio functions such as music playing and recording through the audio module 170, the speaker 170A, the receiver 170B, the microphone 170C, the headphone interface 170D, and the application processor.

The audio module 170 is used to convert digital audio information into analog audio signal output, and is also used to convert analog audio input into digital audio signals. The audio module 170 can also be used to encode and decode audio signals. In some embodiments, the audio module 170 can be arranged in the processor 110, or some functional modules of the audio module 170 can be arranged in the processor 110.

Speaker 170A, also known as "speaker", is used to convert audio electrical signals into sound signals. Receiver 170B, also known as "earpiece", is used to convert audio electrical signals into sound signals. Microphone 170C, also known as "microphone" and "microphone", is used to convert sound signals into electrical signals, such as error microphone, etc. Headphone interface 170D is used to connect wired headphones. Pressure sensor 180A is used to sense pressure signals and can convert pressure signals into electrical signals. In some embodiments, pressure sensor 180A can be set on display screen 194. Gyroscope sensor 180B can be used to determine the motion posture of first electronic device 100. Air pressure sensor 180C is used to measure air pressure. Magnetic sensor 180D includes Hall sensor. Acceleration sensor 180E can detect the magnitude of acceleration of first electronic device 100 in various directions (generally three axes). Distance sensor 180F is used to measure distance. Proximity light sensor 180G can include, for example, light emitting diode (LED) and light detector. Ambient light sensor 180L is used to sense ambient light brightness. The fingerprint sensor 180H is used to collect fingerprints. The temperature sensor 180J is used to detect temperature. The touch sensor 180K is also called a "touch panel". The touch sensor 180K can be set on the display screen 194, and the touch sensor 180K and the display screen 194 form a touch screen, also called a "touch screen". The touch sensor 180K is used to detect touch operations acting on or near it. The bone conduction sensor 180M can obtain vibration signals. The buttons 190 include a power button, a volume button, etc. The motor 191 can generate vibration prompts. The indicator 192 can be an indicator light, which can be used to indicate the charging status, power changes, and can also be used to indicate messages, missed calls, notifications, etc. The SIM card interface 195 is used to connect a SIM card.

The software system of the first electronic device 100 can adopt a layered architecture, an event-driven architecture, a micro-core architecture, a microservice architecture, or a cloud architecture. The embodiment of the present invention takes the Android system of the layered architecture as an example to exemplify the software structure of the first electronic device 100. Figure 3 is a software structure block diagram of the first electronic device 100 of the embodiment of the present application. The layered architecture divides the software into several layers, and each layer has a clear role and division of labor. The layers communicate with each other through software interfaces. In some embodiments, the Android system is divided into four layers, from top to bottom, respectively, the application layer, the application framework layer, the Android runtime (Android runtime) and the system library, and the kernel layer.

The application layer may include a series of application packages. As shown in FIG3 , the application layer may include applications such as camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music, video, short message, etc.

The application framework layer provides an application programming interface (API) and a programming framework for the applications in the application layer. The application framework layer includes some predefined functions. As shown in FIG3 , the application framework layer may include a window manager, a content provider, a view system, a phone manager, a resource manager, a notification manager, etc.

The window manager is used to manage window programs. The window manager can obtain the display screen size, determine whether there is a status bar, lock the screen, capture the screen, etc.

Content providers are used to store and retrieve data and make it accessible to applications. The data may include videos, images, audio, calls made and received, browsing history and bookmarks, phone books, etc.

The view system includes visual controls, such as controls for displaying text, controls for displaying images, etc. The view system can be used to build applications. A display interface can be composed of one or more views. For example, a display interface including a text notification icon can include a view for displaying text and a view for displaying images.

The phone manager is used to provide communication functions of the first electronic device 100, such as management of call status (including connecting, hanging up, etc.).

The resource manager provides various resources for applications, such as localized strings, icons, images, layout files, video files, and so on.

The notification manager enables applications to display notification information in the status bar. It can be used to convey notification-type messages and can disappear automatically after a short stay without user interaction. For example, the notification manager is used to notify download completion, message reminders, etc. The notification manager can also be a notification that appears in the system top status bar in the form of a chart or scroll bar text, such as notifications of applications running in the background, or a notification that appears on the screen in the form of a dialog window. For example, a text message is displayed in the status bar, a prompt sound is emitted, an electronic device vibrates, an indicator light flashes, etc.

Android runtime includes core libraries and virtual machines. Android runtime is responsible for scheduling and management of the Android system.

The core library consists of two parts: one part is the function that needs to be called by the Java language, and the other part is the Android core library.

The application layer and the application framework layer run in a virtual machine. The virtual machine executes the Java files of the application layer and the application framework layer as binary files. The virtual machine is used to perform functions such as object life cycle management, stack management, thread management, security and exception management, and garbage collection.

The system library may include multiple functional modules, such as surface manager, media libraries, 3D graphics processing library (such as OpenGL ES), 2D graphics engine (such as SGL), etc.

The surface manager is used to manage the display subsystem and provide the fusion of 2D and 3D layers for multiple applications.

The media library supports playback and recording of a variety of commonly used audio and video formats, as well as static image files, etc. The media library can support a variety of audio and video encoding formats.

The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.

A 2D graphics engine is a drawing engine for 2D drawings.

The kernel layer is the layer between hardware and software. The kernel layer contains at least display driver, camera driver, audio driver, and sensor driver.

(2) Second electronic device 200

The second electronic device 200 may be a wearable terminal device (such as a smart watch) with a wireless communication function, but is not limited thereto. Taking the second electronic device 200 as a smart watch as an example, the hardware structure of the second electronic device 200 is introduced below. Please refer to FIG. 4, which is a schematic diagram of the hardware structure of a second electronic device 200 provided in an embodiment of the present application.

The second electronic device 200 may include a processor 210, an antenna 1, an antenna 2, a mobile communication module 220, a wireless communication module 230, a memory 240, a display screen 250, a power supply 260, a first sensor module 270, a second sensor module 280, and the like.

It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on the second electronic device 200. In other embodiments of the present application, the second electronic device 200 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

The processor 210 may include one or more processing units, for example, the processor 210 may include an AP, a modem processor, a GPU, an ISP, a controller, a memory, a video codec, a DSP, a baseband processor, and/or an NPU, etc. Different processing units may be independent devices or integrated into one or more processors.

The controller may be the nerve center and command center of the second electronic device 200. The controller may generate an operation control signal according to the instruction operation code and the timing signal to complete the control of fetching and executing instructions.

A memory may also be provided in the processor 210 for storing instructions and data. In some embodiments, the memory in the processor 210 is a cache memory. The memory may store instructions or data that the processor 210 has just used or cyclically used. If the processor 210 needs to use the instruction or data again, it may be directly called from the memory. Repeated access is avoided, and the waiting time of the processor 210 is reduced, thereby improving the efficiency of the system. The processor 210 calls the instructions or data stored in the memory, so that the second electronic device 200 executes the blood pressure measurement method executed by the electronic device in the following method embodiment.

In some embodiments, the processor 210 may include one or more interfaces. The interface may include an I2C interface, an I2S interface, a PCM interface, a UART interface, a MIPI, a GPIO interface, a SIM interface, and/or a USB interface, etc.

The memory 240 is coupled to the processor 210 and is used to store various software programs and/or multiple sets of instructions. In a specific implementation, the memory 240 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more disk storage devices, flash memory devices or other non-volatile solid-state storage devices. The memory 240 may store an operating system, such as an embedded operating system such as uCOS, VxWorks, RTLinux, etc. The memory 240 may also store a communication program, which may be used to communicate with the second electronic device 200, one or more servers, or an additional device.

The wireless communication function of the second electronic device 200 can be implemented through the antenna 1, the antenna 2, the mobile communication module 220, the wireless communication module 230, the modem processor and the baseband processor.

Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in the second electronic device 200 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve the utilization of the antennas. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.

The mobile communication module 220 can provide solutions for wireless communications including 2G/3G/4G/5G, etc., applied to the second electronic device 200. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, an LNA, etc. The mobile communication module 220 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 220 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the mobile communication module 220 can be set in the processor 210. In some embodiments, at least some of the functional modules of the mobile communication module 220 can be set in the same device as at least some of the modules of the processor 210.

The modulation and demodulation processor may include a modulator and a demodulator. The modulator is used to modulate the low-frequency baseband signal to be transmitted into a medium-high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After being processed by the baseband processor, the low-frequency baseband signal is transmitted to the application processor.

The wireless communication module 230 can provide solutions for wireless communications including WLAN (such as Wi-Fi network), BT, BLE broadcast, GNSS, FM, NFC, IR, etc. applied to the second electronic device 200. The wireless communication module 230 can be one or more devices integrating at least one communication processing module. The wireless communication module 230 receives electromagnetic waves via the antenna 2, modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 210. The wireless communication module 230 can also receive the signal to be sent from the processor 210, modulate the frequency, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2.

In some embodiments, antenna 1 of the second electronic device 200 is coupled to mobile communication module 220, and antenna 2 is coupled to wireless communication module 230, so that the second electronic device 200 can communicate with the network and other devices through wireless communication technology.

The second electronic device 200 implements a display function through a GPU, a display screen 250, and an application processor. The GPU is a microprocessor for image processing, which connects the display screen 250 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 210 may include one or more GPUs that execute program instructions to generate or change display information.

The display screen 250 is used to display images, videos, interfaces, etc. The display screen 250 includes a display panel. In some embodiments, the second electronic device 200 may include 1 or N display screens 250, where N is a positive integer greater than 1.

The power supply 260 may be used to supply power to various components included in the second electronic device 200. In some embodiments, the power supply 260 may be a battery, such as a rechargeable battery.

The first sensor module 270 is used to measure the change of blood volume in the radial artery, detect the pressure signal of the radial artery, the pulse wave velocity of the radial artery, etc. The first sensor module 270 includes a first photoelectric receiver 270A, a first red light emitting diode 270B, a first pressure sensor array 270C, a second photoelectric receiver 270D, a first green light emitting diode 270E, and a first acceleration sensor 270F.

Among them, the first red light emitting diode 270B, also known as an infrared emitting diode, is a light emitting device that can directly convert electrical energy into infrared light and radiate it, and can emit infrared light to the skin. The first photoelectric receiver 270A can receive the infrared light emitted by the first red light emitting diode 270B to the skin, and the change in blood volume in the radial artery can be measured by measuring the amount of light absorbed or reflected by the blood vessels in the living tissue. Similarly, the first green light emitting diode 270E is a light emitting device that can directly convert electrical energy into green light and radiate it, and can emit green light to the skin. The second photoelectric receiver 270D can receive the green light emitted by the first green light emitting diode 270E to the skin, and the change in blood volume in the radial artery can be measured by measuring the amount of light absorbed or reflected by the blood vessels in the living tissue. By jointly detecting the change in blood volume in the radial artery with two light emitting diodes, the accuracy of the detection can be further improved.

The first pressure sensor array 270C is an array composed of a plurality of pressure sensors, and is used to detect the pressure signal of the radial artery and obtain the pressure waveform of the radial artery.

The first acceleration sensor 270F can also be considered as an accelerometer, which is used to detect acceleration information of the second electronic device 200. The motion state of the target object carrying the second electronic device 200 can be determined according to the acceleration information.

The second sensor module 280 is used to measure the change of blood volume in the ulnar artery, detect the pressure signal of the ulnar artery, the pulse wave velocity of the ulnar artery, etc. The second sensor module 280 includes a third photoelectric receiver 280A, a second red light emitting diode 280B, a second pressure sensor array 280C, a fourth photoelectric receiver 280D, a second green light emitting diode 280E, and a second acceleration sensor 280F.

The second red LED 280B and the third photoelectric receiver 280A have the same function as the first red LED 270B and the first photoelectric receiver 270A, and the change in blood volume in the ulnar artery can be measured by measuring the amount of light absorbed or reflected by the blood vessels in the living tissue. The second green LED 280E and the fourth photoelectric receiver 280D have the same function as the first green LED 270E and the second photoelectric receiver 270D, and the change in blood volume in the ulnar artery can also be measured by measuring the amount of light absorbed or reflected by the blood vessels in the living tissue. By jointly detecting the change in blood volume in the ulnar artery with two LEDs, the accuracy of the detection can be further improved.

The second pressure sensor array 280C is also an array composed of a plurality of pressure sensors, and is used to detect the pressure signal of the ulnar artery and obtain the pressure waveform of the ulnar artery.

The second acceleration sensor 280F can also be considered as an accelerometer, which is used to detect the acceleration information of the second electronic device 200. The motion state of the target object carrying the second electronic device 200 can be determined based on the acceleration information. By detecting the acceleration information of the second electronic device 200 through two acceleration sensors, the accuracy of the detection can be further improved.

Based on the hardware structure of the second electronic device 200, the physical structure of the two sensor modules is introduced below. As shown in Figure 5, Figure 5 is a schematic diagram of the physical structure of a first sensor module 270 and a second sensor module 280 provided in an embodiment of the present application. In the first sensor module 270, the following are arranged from point A to point B: a first photoelectric receiver 270A, a first red light-emitting diode 270B, a first pressure sensor array 270C, a first green light-emitting diode 270E, a second photoelectric receiver 270D, and a first acceleration sensor 270F. In the second sensor module 280, the following are arranged from point A to point B: a third photoelectric receiver 280A, a second red light-emitting diode 280B, a second pressure sensor array 280C, a second green light-emitting diode 280E, a fourth photoelectric receiver 280D, and a second acceleration sensor 280F.

Taking the second electronic device 200 as a smart watch as an example, the following describes the method in which the second electronic device 200 detects the pressure signals of the radial artery and the ulnar artery. As shown in FIG6A , the smart watch includes a dial and a strap, and the strap is equipped with two sensor modules, namely a first sensor module (i.e., the first sensor module 270 mentioned above) and a second sensor module (i.e., the second sensor module 280 mentioned above). Among them, the dial can be round, square, or other shapes, which are not limited here. The user wears the smart watch on the wrist, as shown in FIG6B , when the user's palm is facing up, the first sensor module equipped on the strap at the wrist can detect the pressure signal on the user's radial artery, and the second sensor module equipped on the strap at the wrist can detect the pressure signal on the user's ulnar artery.

For a clearer understanding, please refer to the cross-sectional diagram of the smart watch detecting the pressure signals of the radial artery and the ulnar artery. As shown in FIG6C , the upper part of the wrist is the dial of the smart watch (i.e., the second electronic device 200), the smart watch strap fits the skin of the entire wrist, and the strap located at the lower part of the wrist is embedded with a first sensor module and a second sensor module, wherein the first sensor module can detect the pressure signal on the user's radial artery, and the second sensor module can detect the pressure signal on the user's ulnar artery.

Based on the above, the blood pressure measurement method provided in the embodiment of the present application is further described in detail below.

1. The blood pressure measurement method is performed by a second electronic device.

FIG7 is a flow chart of a blood pressure measurement method provided in an embodiment of the present application. As shown in FIG7 , the blood pressure measurement method includes the following steps S701 to S704. The method execution subject shown in FIG7 may be the second electronic device mentioned above (i.e., the second electronic device 200). Alternatively, the method execution subject shown in FIG7 may be a chip in the second electronic device, which is not limited in the embodiment of the present application. FIG7 is illustrated by taking the second electronic device as the execution subject of the method as an example.

S701: The second electronic device obtains a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object.

In an embodiment of the present application, a preset APP (such as a blood pressure detection APP) can be installed on the second electronic device to measure the blood pressure of the target object. Among them, blood pressure includes diastolic pressure and systolic pressure. When the target object opens the preset APP, the second electronic device enters the blood pressure measurement mode and starts to obtain the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object.

Specifically, the two sensor modules equipped with the second electronic device can be used to measure the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object respectively. For example, the second electronic device can be equipped with the first sensor module and the second sensor module mentioned above, the first sensor module is used to measure the first pressure signal on the radial artery of the target object, and the second sensor module is used to measure the second pressure signal on the ulnar artery of the target object. At this time, the first pressure signal and the second pressure signal can be the signals originally measured by the sensor module, or they can be the signals obtained by the second electronic device after preprocessing the original measured signals, which is not limited here.

It should be noted that the target object mentioned here can be a user or other object, which is not limited here. The embodiment of the present application is explained by taking the target object as an example that the user is the target object. When the target object is the user, the first pressure signal on the radial artery, the second pressure signal on the ulnar artery, the diastolic amplitude, the systolic amplitude and other related data involved in the embodiment of the present application are all obtained after the user's authorization. In addition, when the embodiment of the present application is applied to a specific product or technology, the data involved in the use needs to obtain the user's permission or consent, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions.

Assume that the second electronic device is a smart watch and the target object is the user. As shown in FIG8A , a blood pressure detection APP is installed on the smart watch, and the user can click the blood pressure detection APP to enter the blood pressure detection interface. As shown in FIG8B , the blood pressure detection interface includes a blood pressure display frame and a measurement button. Among them, the blood pressure display frame includes a high pressure (systolic pressure) display frame and a low pressure (diastolic pressure) display frame. The user can click the measurement button in the blood pressure detection interface to enter the blood pressure measurement interface, at which time the smart watch starts to obtain the first pressure signal on the user's radial artery and the second pressure signal on the user's ulnar artery. As shown in FIG8C , the blood pressure measurement interface includes a prompt box and a time box, the prompt box is used to prompt the user to "save still during measurement, pay attention to the correct wearing of the watch"; the time box is used to display the countdown of the blood pressure measurement time. After the measurement is completed, as shown in FIG8D , it automatically returns to the blood pressure detection interface, and the high pressure (systolic pressure) and low pressure (diastolic pressure) currently measured by the user are displayed in the blood pressure display box.

In addition, the second electronic device can also realize dynamic blood pressure measurement. The so-called dynamic blood pressure is to measure the blood pressure value of the user at a certain interval within 24 hours during the day and night. It is a non-invasive and continuous blood pressure monitoring, which can more accurately and comprehensively reflect the overall blood pressure of the user. As shown in Figure 8E, the blood pressure detection interface can also include a dynamic blood pressure measurement button. If the user clicks the blood pressure measurement button, the second electronic device will measure the blood pressure once every first preset time period within 24 hours. After the measurement is completed, it will automatically return to the blood pressure detection interface, and the dynamic blood pressure measured by the user within 24 hours will be displayed in the dynamic blood pressure display box, and the blood pressure changes of the user within 24 hours can be monitored (as shown in Figure 8F). It should be noted that the first preset time period can be 20 minutes, 1 hour, or any other arbitrary value, which is not limited here. The first preset time period can be set by the user himself or the system default value, which is not limited here.

In one possible implementation, the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object may be signals obtained by preprocessing the original measured signal of the sensor module by the second electronic device. Therefore, when the second electronic device obtains the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object, the specific implementation method may include the following steps s11 to s16. Based on this method, the interference between the first pressure signal and the second pressure signal can be reduced, and the accuracy of the first pressure signal and the second pressure signal can be improved.

s11. Within a preset time, the second electronic device obtains a first original pressure signal on the radial artery of the target object, a second original pressure signal on the ulnar artery of the target object, and acceleration information of the target object.

In a specific implementation, the preset time may be a system default value or a value set by the manufacturer, which is not limited here. For example, the preset time may be 60 seconds. The second electronic device may be equipped with a first sensor module and a second sensor module. The first sensor module is equipped with a first acceleration sensor and a first pressure sensor array; the first sensor module is equipped with a second acceleration sensor and a second pressure sensor array.

After turning on the blood pressure measurement mode, the second electronic device can detect the first original pressure signal on the radial artery of the target object using the first pressure sensor array in the first sensor module, and detect the first acceleration information of the target object using the first acceleration sensor in the first sensor module; it can detect the second original pressure signal on the ulnar artery of the target object using the second pressure sensor array in the second sensor module, and detect the second acceleration information of the target object using the second acceleration sensor in the second sensor module. Further, the acceleration information of the target object can be determined jointly by the first acceleration information of the target object and the second acceleration information of the target object. For example, the first acceleration information and the second acceleration information can be weighted and calculated to obtain the acceleration information of the target object; the first acceleration information and the second acceleration information can also be averaged to obtain the acceleration information of the target object; this is not limited here. Based on this method, the accuracy of the acceleration information of the target object can be improved.

s12. The second electronic device determines the state of the target object based on the acceleration information.

In a specific implementation, after the second electronic device obtains the first original pressure signal on the radial artery of the target object, the second original pressure signal on the ulnar artery of the target object, and the acceleration information of the target object, the state of the target object within a preset time can be determined according to the acceleration information. Specifically, it can be the state of the target object at each time point within the preset time. The state of the target object can be a static state, a moving state, etc.

Assuming that the preset time is 60 seconds, and each second is a time point, it is necessary to determine the state of the target object at each time point within 60 seconds based on the acceleration information. For example, the state of the target object at the 1st second is a stationary state, the state of the target object at the 2nd second is a stationary state, the state of the target object at the 3rd second is a moving state, ..., the state of the target object at the 59th second is a moving state, and the state of the target object at the 60th second is a stationary state.

Optionally, when the second electronic device determines the state of the target object based on the acceleration information, the specific implementation method is as follows: Based on this method, the accuracy of determining the state of the target object can be improved.

(1) When the acceleration in the acceleration information is less than or equal to a second preset threshold, the second electronic device determines that the target object is in a stationary state.

For example, assuming that the second preset threshold is 0.6, and the acceleration at the first second in the acceleration information is 0.1, then the state of the target object at the first second is a stationary state.

(2) When the acceleration in the acceleration information is greater than a second preset threshold, the second electronic device determines that the target object is in motion.

For example, assuming that the second preset threshold is 0.6, and the acceleration at the 3rd second in the acceleration information is 0.8, then the state of the target object at the 3rd second is a moving state.

s13. The second electronic device determines the first time that the target object is in motion.

In a specific implementation, the second electronic device needs to calculate the total time that the target object is in motion, that is, the first time. For example, assuming that the target object is in a stationary state at the first second, in a stationary state at the second second, in a moving state at the third second, and in a moving state at the fourth second; then within these 4 seconds, the first time that the target object is in motion is 2 seconds.

s14. The second electronic device determines whether the first time is less than or equal to a first preset threshold.

In a specific implementation, if the first time is less than or equal to the first preset threshold, step s15 is executed; if the first time is greater than the first preset threshold, it is determined that the blood pressure test has failed, and the target object is prompted to re-test the blood pressure.

It should be noted that the first preset threshold can be a system default value or a manufacturer-defined value, which is not limited here. When the total time that the target object is in motion (i.e., the first time) is less than or equal to the first preset threshold, it means that the target object is basically in a static state and will not affect the blood pressure detection result; when the total time that the target object is in motion (i.e., the first time) is greater than the first preset threshold, it means that the target object is in motion and is not static. At this time, the blood pressure measurement result is not accurate, and the target object needs to re-test the blood pressure. Of course, in the scenario of dynamic blood pressure detection, the second electronic device can also automatically re-test the blood pressure for the target object.

s15. The second electronic device aligns and splices the first original pressure signal and the second original pressure signal according to the timestamp to obtain a third pressure signal.

For example, assuming that the first preset threshold is 15 seconds, if the total time that the target object is in motion is 10 seconds within 60 seconds, it means that the target object is basically in a static state and will not affect the blood pressure detection result. At this time, the first original pressure signal and the second original pressure signal obtained are valid.

Since the start time of collecting the first original pressure signal and the second original pressure signal is not necessarily the same, in order to facilitate subsequent signal processing, it is necessary to further align and splice the first original pressure signal and the second original pressure signal according to the timestamp to obtain the third pressure signal. The so-called timestamp refers to the time when a certain event occurs, which can be considered as the time when the pressure signal is collected.

As shown in (a) of Figure 9, the start time of collecting the first original pressure signal is inconsistent with the start time of collecting the second original pressure signal. Therefore, the starting point of the first original pressure signal and the starting point of the second original pressure signal are inconsistent. It is necessary to align the starting point of the first original pressure signal and the starting point of the second original pressure signal according to the timestamp, and splice the aligned first original pressure signal and the second original pressure signal together to obtain the third pressure signal as shown in (b) of Figure 9.

s16. The second electronic device determines a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object based on the third pressure signal.

In a specific implementation, the second electronic device can obtain a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object by processing and analyzing the third pressure signal.

Optionally, when the second electronic device determines the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object based on the third pressure signal, the specific implementation method may include the following steps A and B. Based on this method, the interference between the first pressure signal and the second pressure signal can be reduced, and the accuracy of the first pressure signal and the second pressure signal can be improved.

Step A: The second electronic device performs filtering processing on the third pressure signal to obtain a fourth pressure signal.

Since there is still an interference signal in the third pressure signal, the third pressure signal needs to be further filtered. Specifically, the second electronic device can use a Butterworth bandpass filter to filter the third pressure signal to obtain a fourth pressure signal. Among them, the Butterworth bandpass filter is a type of electronic filter, which is a low-pass filter with a maximum flat amplitude response. It has been widely used in the field of communications and has a wide range of uses in electrical measurement. It can be used as a filter for detection signals. Of course, the second electronic device can also use other filters to filter the third pressure signal, which is not limited here.

Step B: The second electronic device performs blind source separation on the fourth pressure signal to obtain a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object.

Since the fourth pressure signal is a mixed signal of the first original pressure signal and the second original pressure signal after alignment, splicing and filtering, and the fourth pressure signal may also be mixed with interference signals, etc. In order to separate each independent signal from the mixed signal and remove the aliased interference signal, the second electronic device can perform blind source separation on the fourth pressure signal, thereby separating the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object. At this time, the first pressure signal obtained is the signal obtained after preprocessing the first original pressure signal, and the second pressure signal obtained is the signal obtained after preprocessing the second original pressure signal. Among them, the so-called blind source separation is a technology that separates independent source signals from mixed signals measured by a group of sensors, using only the weak known condition that the source signals are independent of each other, in the case of unknown system transfer functions, mixing coefficients of source signals and their probability distribution.

S702. The second electronic device determines the waveform phase difference between the first pressure signal and the second pressure signal, the cardiac cycle corresponding to the first pressure signal, the first difference between the contraction amplitude of the first pressure signal and the contraction amplitude of the second pressure signal, and the second difference between the diastolic amplitude of the first pressure signal and the diastolic amplitude of the second pressure signal.

In the embodiment of the present application, wrist pulse wave velocity (PWV) refers to the pressure wave velocity propagating along the aorta wall generated by each heart beat and ejection, and is a non-invasive indicator for evaluating the degree of arteriosclerosis. Among them, PWV is related to the elastic modulus of blood vessels, and the elastic modulus is further related to blood pressure. Qualitatively speaking, the worse the elasticity of blood vessels, the higher the PWV, and the higher the blood pressure. Therefore, in order to be able to measure blood pressure, a model for measuring blood pressure can be established using PWV. According to theoretical research in the biomedical field, the radial artery and the ulnar artery originate from the brachial artery. According to the fluid continuity equation and the law of conservation of mass, assuming that the mass flow rate of blood flow remains unchanged before and after the bifurcation, that is, the flow rate of the radial artery, the ulnar artery and the brachial artery remains unchanged, then PWV can be calculated using the following formula.

S _r = PWV × t _r (1)

S _c =PWV×t _c (2)

In formula (1), PWV represents the wrist pulse wave velocity (i.e., blood flow velocity, in this case, the PWVs of the radial artery, ulnar artery, and brachial artery are all considered to be the same); S _r represents the distance from the heart to the radial artery; t _r represents the pulse wave transmission time for the radial artery, which can be considered as the time interval from the light emitting diode for the radial artery sending a photoelectric signal to the skin to the photoelectric receiver receiving the photoelectric signal (such as the time interval from the infrared light emitted by the first red light emitting diode in the first sensor module to the skin to the first photoelectric receiver receiving the infrared light, or the time interval from the green light emitted by the first green light emitting diode in the first sensor module to the skin to the second photoelectric receiver receiving the green light).

In formula (2), PWV represents the wrist pulse wave velocity (at this time, the PWVs of the radial artery, ulnar artery and brachial artery are all the same), _Sc represents the distance from the heart to the ulnar artery; _tc represents the pulse wave transmission time for the ulnar artery, which can be considered as the time interval from the light-emitting diode for the ulnar artery sending a photoelectric signal to the skin to the photoelectric receiver receiving the photoelectric signal (such as the time interval from the infrared light emitted by the second red light-emitting diode in the second sensor module to the skin to the third photoelectric receiver receiving the infrared light, or the time interval from the green light emitted by the second green light-emitting diode in the second sensor module to the skin to the fourth photoelectric receiver receiving the green light).

Combining formula (1) and formula (2), the expression of PWV can be determined, that is, formula (3). In formula (3), ΔS represents the length difference between the radial artery and the ulnar artery, that is, S _r -S _c ; Δt represents the pulse time difference between the radial artery and the ulnar artery, that is, t _r -t _c .

According to formula (3), it can be concluded that PWV is related to ΔS and Δt (i.e., the relationship between ΔS and Δt is established based on PWV), so a model for measuring blood pressure can be established based on ΔS and Δt. Since ΔS represents the length difference between the radial artery and the ulnar artery, it is a constant that requires individual correction, so the focus needs to be on ensuring the accuracy of Δt.

Similarly, assuming that the mass flow rate of blood flow is different before and after the bifurcation, that is, the flow rates of the radial artery, ulnar artery and brachial artery are different, then PWV can also be calculated using the following formula.

S _r = PWV _r × t _r (4)

S _c =PWV _c ×t _c (5)

A _g ·PWV＝A _r ·PWV _r +A _c ·PWV _c (6)

In formula (4), _PWVr represents the pulse wave velocity of the radial artery; _Sr represents the distance from the heart to the radial artery; _tr represents the pulse wave transmission time for the radial artery, which can be considered as the time interval from the light-emitting diode for the radial artery sending a photoelectric signal to the skin to the photoelectric receiver receiving the photoelectric signal (such as the time interval from the infrared light emitted by the first red light-emitting diode in the above-mentioned first sensor module to the skin to the first photoelectric receiver receiving the infrared light, or the time interval from the green light emitted by the first green light-emitting diode in the above-mentioned first sensor module to the skin to the second photoelectric receiver receiving the green light).

In formula (5), PWV _c represents the pulse wave velocity of the ulnar artery; S _r represents the distance from the heart to the radial artery; t _r represents the pulse wave transmission time for the radial artery, which can be considered as the time interval from the light-emitting diode for the radial artery sending a photoelectric signal to the skin to the photoelectric receiver receiving the photoelectric signal (such as the time interval from the infrared light emitted by the first red light-emitting diode in the first sensor module to the skin to the first photoelectric receiver receiving the infrared light, or the time interval from the green light emitted by the first green light-emitting diode in the first sensor module to the skin to the second photoelectric receiver receiving the green light).

In formula (6), PWV represents the pulse wave velocity of the brachial artery (which can be considered as the pulse wave velocity of the wrist, that is, the blood flow velocity); _Ag represents the cross-sectional area of the brachial artery; _PWVr represents the pulse wave velocity of the radial artery; _Ar represents the cross-sectional area of the radial artery; _PWVc represents the pulse wave velocity of the ulnar artery; _Ac represents the cross-sectional area of the ulnar artery.

Combining formula (4), formula (5) and formula (6), the expression of PWV can be determined (the transformation method is not limited here), that is, formula (7). Among them, S _r -S _c can be represented by ΔS, that is, the length difference between the radial artery and the ulnar artery; t _r -t _c can be represented by Δt, that is, the pulse time difference between the radial artery and the ulnar artery, thereby obtaining formula (8).

According to formula (8), it can be concluded that PWV is related to ΔS and Δt (i.e., the relationship between ΔS and Δt is established based on PWV), so a model for measuring blood pressure can be established based on ΔS and Δt. Since ΔS represents the length difference between the radial artery and the ulnar artery, it is a constant that requires individual correction, so the focus needs to be on ensuring the accuracy of Δt.

For Δt, it can be considered as the waveform phase difference between the first pressure signal and the second pressure signal. The second electronic device can determine the waveform phase difference between the first pressure signal and the second pressure signal by analyzing the waveform of the first pressure signal and the waveform of the second pressure signal (as shown in Figure 10A). However, the waveform phase difference may have certain errors due to problems such as sensors and processing circuits. If Δt is directly considered as the waveform phase difference between the first pressure signal and the second pressure signal, the accuracy of the final measured blood pressure will be reduced. Therefore, in order to improve the accuracy of blood pressure measurement, it is necessary to calibrate the waveform phase difference in the future to improve the accuracy of the waveform phase difference.

In addition, the second electronic device can calibrate the waveform phase difference by using factors that affect the waveform phase difference. Among them, the factors that affect the waveform phase difference are: the cardiac cycle corresponding to the first pressure signal, the first difference between the contraction amplitude of the first pressure signal and the contraction amplitude of the second pressure signal, and the second difference between the diastolic amplitude of the first pressure signal and the diastolic amplitude of the second pressure signal. Therefore, the second electronic device needs to determine the cardiac cycle (as shown in Figure 10B) by analyzing the waveform of the first pressure signal. The so-called cardiac cycle refers to the process experienced by the cardiovascular system from the start of one heartbeat to the start of the next heartbeat. The second electronic device also needs to determine the first difference (as shown in Figure 10C) and the second difference (as shown in Figure 10D) by analyzing the waveform of the first pressure signal and the waveform of the second pressure signal for subsequent use.

S703: The second electronic device determines the pulse time difference between the radial artery and the ulnar artery based on the waveform phase difference, the cardiac cycle, the first difference and the second difference.

In the embodiment of the present application, in order to improve the accuracy of blood pressure measurement, the waveform phase difference needs to be calibrated. The second electronic device can calibrate the waveform phase difference using the cardiac cycle, the first difference and the second difference to obtain the pulse time difference between the radial artery and the ulnar artery.

In a possible implementation, when the second electronic device determines the pulse time difference between the radial artery and the ulnar artery based on the waveform phase difference, the cardiac cycle, the first difference, and the second difference, the specific implementation may be: calling the first model to process the waveform phase difference, the cardiac cycle, the first difference, and the second difference to obtain the pulse time difference between the radial artery and the ulnar artery; the first model is trained based on the first training sample and the corresponding pulse time difference label. Based on this method, the accuracy of the pulse time difference between the radial artery and the ulnar artery can be improved.

In a specific implementation, the second electronic device uses the cardiac cycle, the first difference, and the second difference to calibrate the waveform phase difference, and a machine learning model can be used, that is, the first model can be called to process the waveform phase difference, the cardiac cycle, the first difference, and the second difference, so as to obtain the pulse time difference between the radial artery and the ulnar artery. Among them, the first model is a trained calibration model, which can be a neural network model, such as a deep neural network, a feedforward neural network, a feedback neural network, a fully connected neural network, etc., or other network models, which are not limited here.

Specifically, the first model is obtained by training with a large number of first training samples and corresponding pulse time difference labels. The first training samples include sample waveform phase difference, sample cardiac cycle, sample first difference and sample second difference. Exemplarily, assuming that the first model is a neural network model, the specific training process of the first model includes: inputting the above-mentioned multiple first training samples into the initial neural network model for training, and adjusting the parameters of the initial neural network model using the pulse time difference label annotated with each first training sample. When the training reaches the number of times, the training is completed to obtain the first model.

S704. The second electronic device determines the diastolic pressure of the target object and the systolic pressure of the target object based on the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery.

In an embodiment of the present application, in order to measure blood pressure, a model for measuring blood pressure can be established using PWV. PWV is related to ΔS and Δt. The second electronic device has determined the pulse time difference (i.e., Δt) between the radial artery and the ulnar artery, and further individual calibration is required to obtain the length difference (i.e., ΔS) between the radial artery and the ulnar artery. At present, the radial artery is often used in clinical practice to monitor blood pressure. It has the advantages of being intuitive, accurate, and easy to observe changes in blood pressure and the patient's arterial ejection waveform. It is suitable for blood pressure monitoring of surgical patients and critically ill patients. In order to improve the accuracy of the model for measuring blood pressure, the waveform characteristics and amplitude characteristics of the radial artery can also be used to build a model together. Therefore, it is also necessary to further obtain the waveform of the first pressure signal on the radial artery, the contraction amplitude of the first pressure signal, and the diastolic amplitude of the first pressure signal.

Then, the second electronic device can determine the diastolic pressure and the systolic pressure of the target object according to the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery, thus completing the blood pressure detection of the target object. Based on this method, the accuracy of blood pressure measurement can be improved.

In one possible implementation, when the second electronic device determines the diastolic pressure and the systolic pressure of the target object based on the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery, the specific implementation may include the following steps s21 and s22.

s21. The second electronic device determines first information based on the waveform of the first pressure signal, the first information including the ratio of peak amplitude to trough amplitude, the pulse wave amplitude ratio, the area enclosed by the curve from the peak to the endpoint of the dicrotic wave, and the arteriosclerosis index.

In a specific implementation, the second electronic device can analyze the first information according to the waveform of the first pressure signal, and the parameters contained in the first information are all parameters for measuring blood pressure. In the first information, the peak amplitude to valley amplitude ratio (Ratio of maximum peak intensity to valley intensity, RIPV) refers to the first ratio between the peak amplitude and the valley amplitude of the first pressure signal (taking one cardiac cycle of the first pressure signal as an example, as shown in FIG11A); the pulse wave amplitude ratio (Photoplethysmogramintensity ratio, PIR) refers to the second ratio between the peak amplitude and the starting point amplitude of the first pressure signal (taking one cardiac cycle of the first pressure signal as an example, as shown in FIG11B); the area enclosed by the dicrotic wave peak to the end point curve (which can be expressed as S4) is shown in FIG11C (taking one cardiac cycle of the first pressure signal as an example); the large artery stiffness index (LASI) refers to the reciprocal of the time interval between the peak and the dicrotic wave of the first pressure signal (taking one cardiac cycle of the first pressure signal as an example, as shown in FIG11D).

s22. The second electronic device determines the diastolic pressure and the systolic pressure of the target object based on the first information, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery.

Optionally, when the second electronic device determines the diastolic pressure of the target object and the systolic pressure of the target object based on the first information, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery, the specific implementation method includes the following steps a and b. Based on this method, the accuracy of blood pressure measurement can be further improved.

Step a: The second electronic device calls a second model to process the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the diastolic pressure of the target object; the second model is trained based on the second training sample and the corresponding diastolic pressure label.

In a specific implementation, the second electronic device determines the diastolic pressure of the target object by using the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery. A machine learning model can be used, that is, the second model can be called to process the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the diastolic pressure of the target object. The second model is a trained diastolic pressure model, which can be a neural network model, such as a deep neural network, a feedforward neural network, a feedback neural network, a fully connected neural network, etc., or other network models, which are not limited here.

Specifically, the second model is obtained by training with a large number of second training samples and corresponding diastolic pressure labels. The second training samples include sample first information, sample pulse time difference, contraction amplitude of sample first pressure signal, diastolic amplitude of sample first pressure signal, and sample length difference between radial artery and ulnar artery. Exemplarily, assuming that the second model is a neural network model, the specific training process of the second model includes: inputting the above-mentioned multiple second training samples into the initial neural network model for training, and adjusting the parameters of the initial neural network model using the diastolic pressure label annotated by each second training sample. When the training reaches the number of times, the training is completed to obtain the second model.

Step b: The second electronic device calls a third model to process the first information, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the systolic pressure of the target object; the third model is trained based on the second training sample and the corresponding systolic pressure label.

In a specific implementation, the second electronic device determines the systolic pressure of the target object by using the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery. A machine learning model can be used, that is, a third model can be called to process the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the systolic pressure of the target object. The third model is a trained systolic pressure model, which can be a neural network model, such as a deep neural network, a feedforward neural network, a feedback neural network, a fully connected neural network, etc., or other network models, which are not limited here.

Specifically, the third model is obtained by training with a large number of second training samples and corresponding systolic blood pressure labels. The second training samples include sample first information, sample pulse time difference, systolic amplitude of sample first pressure signal, diastolic amplitude of sample first pressure signal, and sample length difference between radial artery and ulnar artery. Exemplarily, assuming that the third model is a neural network model, the specific training process of the third model includes: inputting the above-mentioned multiple second training samples into the initial neural network model for training, and adjusting the parameters of the initial neural network model using the systolic blood pressure label annotated by each second training sample. When the training reaches the number of times, the training is completed to obtain the third model.

It should be noted that the execution order of step a and step b is not limited.

In general, as shown in Figure 11E, the blood pressure measurement method can be divided into the following steps: first, a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object are obtained; then four parameters are analyzed from the first pressure signal and the second pressure signal, namely, the waveform phase difference (P_rc) between the first pressure signal and the second pressure signal, the cardiac cycle (H_t) corresponding to the first pressure signal, the first difference between the contraction amplitude of the first pressure signal and the contraction amplitude of the second pressure signal (SP_r-SP_c), and the second difference between the diastolic amplitude of the first pressure signal and the diastolic amplitude of the second pressure signal (DP_r-DP_c). The four parameters are input into the trained first model, and the pulse time difference (Δt) between the radial artery and the ulnar artery is output; then four characteristic information are analyzed from the waveform of the first pressure signal (i.e., the pressure signal waveform of the radial artery), namely, the peak amplitude to trough amplitude ratio (RIPV), the pulse wave amplitude ratio (PIR), the area enclosed by the dicrotic wave peak to the end point curve (S4), and the arteriosclerosis index (LASI); at the same time, the systolic amplitude (SP_r) of the first pressure signal, the diastolic amplitude (DP_r) of the first pressure signal, and the length difference (ΔS) between the radial artery and the ulnar artery are also obtained; finally, ΔS, SP_r, DP_r, Δt, RIPV, PIR, S4 and LASI are output together to the trained second model (ML_dbp) to output the diastolic pressure of the target object; ΔS, SP_r, DP_r, Δt, RIPV, PIR, S4 and LASI are output together to the trained third model (ML_sbp) to output the systolic pressure of the target object, thereby completing the blood pressure measurement of the target object.

It can be seen that based on the method described above, after the second electronic device obtains the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object, it analyzes the first pressure signal and the second pressure signal to determine four parameters, namely, the waveform phase difference between the first pressure signal and the second pressure signal, the cardiac cycle corresponding to the first pressure signal, the first difference between the contraction amplitude of the first pressure signal and the contraction amplitude of the second pressure signal, and the second difference between the diastolic amplitude of the first pressure signal and the diastolic amplitude of the second pressure signal; the pulse time difference between the radial artery and the ulnar artery is determined by these four parameters to calibrate the waveform phase difference; finally, the diastolic pressure and the systolic pressure of the target object are determined by using the characteristic information in the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery. Since the pulse time difference between the radial artery and the ulnar artery has been calibrated, the parameters affecting blood pressure (i.e., characteristic information in the waveform of the first pressure signal, the contraction amplitude of the first pressure signal, the relaxation amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery) are used together with the pulse time difference to establish a model to further optimize the parameters, thereby improving the accuracy of blood pressure measurement.

2. The blood pressure measurement method is performed jointly by the first electronic device and the second electronic device.

Figure 12 is a flow chart of another blood pressure measurement method provided in an embodiment of the present application. As shown in Figure 12, the blood pressure measurement method includes the following steps S1201 to S1205. The method execution subject shown in Figure 12 can be the first electronic device (i.e., the second electronic device 100) and the second electronic device (i.e., the second electronic device 200) mentioned above. Alternatively, the method execution subject shown in Figure 12 can be a chip in the first electronic device and a chip in the second electronic device, which is not limited in the embodiment of the present application. Figure 12 is illustrated by taking the first electronic device and the second electronic device as the execution subject of the method as an example.

S1201: The second electronic device obtains a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object.

The specific implementation of step S1201 may refer to the specific implementation of step S701, which will not be described in detail here.

S1202: The second electronic device sends the first pressure signal and the second pressure signal to the first electronic device. Correspondingly, the first electronic device receives the first pressure signal and the second pressure signal from the second electronic device.

In the embodiment of the present application, at this time, the first electronic device obtains the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object.

It should be noted that, with respect to the way in which the first electronic device obtains the first pressure signal and the second pressure signal, the first electronic device may also receive the first original pressure signal on the radial artery of the target object, the second original pressure signal on the ulnar artery of the target object, and the acceleration information of the target object from the second electronic device; then the first electronic device determines the state of the target object based on the acceleration information; the first electronic device determines the first time that the target object is in motion; the first electronic device determines whether the first time is less than or equal to the first preset threshold; the first electronic device aligns and splices the first original pressure signal and the second original pressure signal according to the timestamp to obtain a third pressure signal; finally, the first electronic device determines the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object based on the third pressure signal. The specific implementation method can refer to the above steps s11 to s16, which will not be repeated here.

S1203. The first electronic device determines the waveform phase difference between the first pressure signal and the second pressure signal, the cardiac cycle corresponding to the first pressure signal, the first difference between the contraction amplitude of the first pressure signal and the contraction amplitude of the second pressure signal, and the second difference between the diastolic amplitude of the first pressure signal and the diastolic amplitude of the second pressure signal.

S1204: The first electronic device determines the pulse time difference between the radial artery and the ulnar artery based on the waveform phase difference, the cardiac cycle, the first difference and the second difference.

S1205. The first electronic device determines the diastolic pressure of the target object and the systolic pressure of the target object based on the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery.

The specific implementation of steps S1203 to S1205 may refer to the specific implementation of steps S702 to S704 above, which will not be described in detail here.

S1206: The first electronic device sends the diastolic pressure and the systolic pressure of the target object to the second electronic device. Correspondingly, the second electronic device receives the diastolic pressure and the systolic pressure of the target object from the first electronic device.

Exemplarily, it is assumed that the first electronic device is a mobile phone, the second electronic device is a smart watch, and the target object is a user. As shown in FIG8A , a blood pressure detection APP is installed on the smart watch, and the user can click the blood pressure detection APP to enter the blood pressure detection interface. As shown in FIG8B , the blood pressure detection interface includes a blood pressure display box and a measurement button. Among them, the blood pressure display box includes a high pressure (systolic pressure) display box and a low pressure (diastolic pressure) display box. The user can click the measurement button in the blood pressure detection interface to enter the blood pressure measurement interface, at which time the smart watch starts to obtain the first pressure signal on the user's radial artery and the second pressure signal on the user's ulnar artery.

After the smart watch obtains the first pressure signal on the user's radial artery and the second pressure signal on the user's ulnar artery, the first pressure signal and the second pressure signal are sent to the mobile phone for data processing, and the mobile phone performs the operations of steps S1203 to S1205. As shown in Figure 13A, a health APP is also installed on the mobile phone, and the user can click on the health APP to enter the health data interface. As shown in Figure 13B, the health data interface includes data boxes such as steps, heart rate, blood pressure, and activity energy. Of course, the health data interface may also include other data boxes, and may also include more or fewer data boxes, which are not limited here. The user can click on the blood pressure data box to enter the blood pressure data interface. As shown in Figure 13C, the high pressure (systolic pressure) and low pressure (diastolic pressure) currently measured by the user can be viewed in the blood pressure data interface. In addition, the smart watch can also realize dynamic blood pressure measurement, and the blood pressure changes of the user within 24 hours can also be viewed in the blood pressure data box.

Of course, the mobile phone can also send the determined high pressure (systolic pressure) and low pressure (diastolic pressure) of the user to the smart watch, and the user can also view the high pressure (systolic pressure) and low pressure (diastolic pressure) currently measured by the user in the blood pressure detection APP of the smart watch (as shown in Figure 8D). Similarly, the mobile phone can also send the determined dynamic blood pressure measurement results to the smart watch, and the user can also view the blood pressure changes of the user within 24 hours in the blood pressure detection APP of the smart watch (as shown in Figure 8F).

It can be seen that based on the method described above, after the second electronic device obtains the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object, the first pressure signal and the second pressure signal are sent to the first electronic device for data processing to obtain the diastolic pressure of the target object and the systolic pressure of the target object. In the process of processing data, the first electronic device, because the pulse time difference between the radial artery and the ulnar artery has been calibrated, uses the parameters affecting blood pressure (i.e., the characteristic information in the waveform of the first pressure signal, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery) together with the pulse time difference to establish a model, further optimize the parameters, thereby improving the accuracy of blood pressure measurement; in addition, because the first electronic device assists the second electronic device in data processing, it is beneficial to save the power consumption of the second electronic device and improve the efficiency of data processing.

Please refer to FIG. 14, which shows a schematic diagram of the structure of a blood pressure measurement device 1400 according to an embodiment of the present application. The blood pressure measurement device shown in FIG. 14 can be an electronic device, or a device in an electronic device, or a device that can be used in conjunction with an electronic device. The blood pressure measurement device shown in FIG. 14 can include an acquisition unit 1401 and a determination unit 1402. Among them:

An acquisition unit 1401 is used to acquire a first pressure signal on a radial artery of a target object and a second pressure signal on an ulnar artery of the target object;

A determination unit 1402 is used to determine a waveform phase difference between the first pressure signal and the second pressure signal, a cardiac cycle corresponding to the first pressure signal, a first difference between a systolic amplitude of the first pressure signal and a systolic amplitude of the second pressure signal, and a second difference between a diastolic amplitude of the first pressure signal and a diastolic amplitude of the second pressure signal;

The determining unit 1402 is further configured to determine a pulse time difference between the radial artery and the ulnar artery based on the waveform phase difference, the cardiac cycle, the first difference, and the second difference;

The determination unit 1402 is also used to determine the diastolic pressure of the target object and the systolic pressure of the target object based on the waveform of the first pressure signal, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery.

In one possible implementation, the determination unit 1402, when determining the pulse time difference between the radial artery and the ulnar artery based on the waveform phase difference, the cardiac cycle, the first difference and the second difference, is specifically used to: call a first model to process the waveform phase difference, the cardiac cycle, the first difference and the second difference to obtain the pulse time difference between the radial artery and the ulnar artery; the first model is trained based on a first training sample and a corresponding pulse time difference label.

In a possible implementation, the determination unit 1402, when determining the diastolic pressure and the systolic pressure of the target object based on the waveform of the first pressure signal, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery, is specifically used to: determine first information based on the waveform of the first pressure signal, the first information including the ratio of peak amplitude to trough amplitude, the pulse wave amplitude ratio, the area enclosed by the dicrotic wave peak to endpoint curve, and the arteriosclerosis index; determine the diastolic pressure and the systolic pressure of the target object based on the first information, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery.

In a possible implementation, the determination unit 1402, when determining the diastolic pressure and the systolic pressure of the target object based on the first information, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery, is specifically used to: call a second model to process the first information, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the diastolic pressure of the target object; the second model is trained based on the second training sample and the corresponding diastolic pressure label; call a third model to process the first information, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the systolic pressure of the target object; the third model is trained based on the second training sample and the corresponding systolic pressure label.

In one possible implementation, the acquisition unit 1401, when acquiring a first pressure signal on the radial artery of a target object and a second pressure signal on the ulnar artery of the target object, is specifically used to: acquire a first original pressure signal on the radial artery of the target object, a second original pressure signal on the ulnar artery of the target object, and acceleration information of the target object within a preset time; determine a state of the target object based on the acceleration information; determine a first time when the target object is in a motion state; if the first time is less than or equal to a first preset threshold, align and splice the first original pressure signal and the second original pressure signal according to a timestamp to obtain a third pressure signal; and determine a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object based on the third pressure signal.

In one possible implementation, the acquisition unit 1401, when acquiring a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object, is specifically used to: receive the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object from a second electronic device.

In one possible implementation, the determination unit 1402, when determining the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object based on the third pressure signal, is specifically used to: filter the third pressure signal to obtain a fourth pressure signal; and perform blind source separation on the fourth pressure signal to obtain the first pressure signal on the radial artery of the target object and the second pressure signal on the ulnar artery of the target object.

In one possible implementation, the determination unit 1402, when determining the state of the target object based on the acceleration information, is specifically used to: when the acceleration in the acceleration information is less than or equal to a second preset threshold, determine that the target object is in a stationary state; when the acceleration in the acceleration information is greater than the second preset threshold, determine that the target object is in a moving state.

In the case where the blood pressure measuring device can be a chip or a chip system, please refer to the schematic diagram of the chip structure shown in Figure 15. The chip 1500 shown in Figure 15 includes a processor 1501 and an interface 1502. Optionally, it can also include a memory 1503. The number of processors 1501 can be one or more, and the number of interfaces 1502 can be multiple.

For the case where the chip is used to implement the electronic device (first electronic device or second electronic device) in the embodiment of the present application:

The interface 1502 is used to receive or output signals;

The processor 1501 is used to execute data processing operations of the electronic device (the first electronic device or the second electronic device).

It is understandable that some optional features in the embodiments of the present application may be implemented independently in certain scenarios without relying on other features, such as the solution on which they are currently based, to solve corresponding technical problems and achieve corresponding effects, or may be combined with other features according to needs in certain scenarios. Accordingly, the blood pressure measurement device provided in the embodiments of the present application may also realize these features or functions accordingly, which will not be elaborated here.

It should be understood that the processor in the embodiment of the present application can be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method embodiment can be completed by an integrated logic circuit of hardware in the processor or an instruction in the form of software. The above processor can be a general-purpose processor, a digital signal processor (digital signal processor, DSP), an application specific integrated circuit (application specific integrated circuit, ASIC), a field programmable gate array (field programmable gate array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

It can be understood that the memory in the embodiments of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

The present application also provides a computer-readable storage medium, in which a computer program is stored. The computer program includes program instructions. When the program instructions are executed on a blood pressure measurement device, the functions of any of the above method embodiments are implemented.

The present application also provides a computer program product. When the computer program product is executed on a computer, the computer can implement the functions of any of the above method embodiments.

In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a high-density digital video disc (DVD)), or a semiconductor medium (eg, a solid state disk (SSD)).

The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims (8)

1. A blood pressure measurement method, characterized in that the method comprises: Acquire a first pressure signal on the radial artery of a target object and a second pressure signal on the ulnar artery of the target object; Determine a waveform phase difference between the first pressure signal and the second pressure signal, a cardiac cycle corresponding to the first pressure signal, a first difference between a systolic amplitude of the first pressure signal and a systolic amplitude of the second pressure signal, and a second difference between a diastolic amplitude of the first pressure signal and a diastolic amplitude of the second pressure signal; Calling a first model to process the waveform phase difference, the cardiac cycle, the first difference, and the second difference to obtain a pulse time difference between the radial artery and the ulnar artery; the first model is obtained by training based on a first training sample and a corresponding pulse time difference label; Determining first information based on the waveform of the first pressure signal, the first information including a ratio of a peak amplitude to a trough amplitude, a pulse wave amplitude ratio, an area enclosed by a curve from a dicrotic wave peak to an endpoint, and an arteriosclerosis index; calling a second model to process the first information, the pulse time difference, the contraction amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the diastolic pressure of the target object; the second model is trained based on a second training sample and a corresponding diastolic pressure label; A third model is called to process the first information, the pulse time difference, the systolic amplitude of the first pressure signal, the diastolic amplitude of the first pressure signal, and the length difference between the radial artery and the ulnar artery to obtain the systolic pressure of the target object; the third model is trained based on the second training sample and the corresponding systolic pressure label. 2. The method according to claim 1, characterized in that the step of obtaining a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object comprises: Acquire, within a preset time, a first original pressure signal on the radial artery of a target object, a second original pressure signal on the ulnar artery of the target object, and acceleration information of the target object; Determine the state of the target object based on the acceleration information; Determining a first time when the target object is in motion; If the first time is less than or equal to a first preset threshold, aligning and splicing the first original pressure signal and the second original pressure signal according to the timestamp to obtain a third pressure signal; A first pressure signal on the radial artery of the target subject and a second pressure signal on the ulnar artery of the target subject are determined based on the third pressure signal. 3. The method according to claim 2, characterized in that the determining, based on the third pressure signal, a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object comprises: filtering the third pressure signal to obtain a fourth pressure signal; Blind source separation is performed on the fourth pressure signal to obtain a first pressure signal on the radial artery of the target object and a second pressure signal on the ulnar artery of the target object. 4. The method according to claim 2 or 3, characterized in that the determining the state of the target object based on the acceleration information comprises: When the acceleration in the acceleration information is less than or equal to a second preset threshold, determining that the target object is in a stationary state; When the acceleration in the acceleration information is greater than the second preset threshold, it is determined that the target object is in motion. 5. An electronic device, characterized in that it comprises: one or more processors and one or more memories; wherein the one or more memories are coupled to the one or more processors, and the one or more memories are used to store computer program codes, and the computer program codes include computer instructions, and when the one or more processors execute the computer instructions, the electronic device executes the method as described in any one of claims 1 to 4. 6. A chip, characterized in that it comprises a processor and an interface, wherein the processor and the interface are coupled; the interface is used to receive or output signals, and the processor is used to execute code instructions so that the method described in any one of claims 1 to 4 is executed. 7. A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed on an electronic device, the electronic device executes the method as described in any one of claims 1 to 4. 8. A computer program product, characterized in that when the computer program product is run on a computer, the computer is enabled to execute the method according to any one of claims 1 to 4.