Blood pressure measurement method, electronic device and system

Abstract

The present disclosure provides a blood pressure measurement method, an electronic device and a system. The method comprises: acquiring physiological data of a target user collected by a plurality of data collection devices; determining whether the target user meets a blood pressure measurement condition according to the physiological data collected by the plurality of data collection devices; and measuring blood pressure of the target user if the target user meets the blood pressure measurement condition.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to the technical field of blood pressure measurement, and more particularly, to a blood pressure measurement method, an electronic device and a system. BACKGROUND

[0002] Hypertension is the most common cardiovascular disease, which is increasingly valued and concerned by people, and blood pressure measurement has become an essential means for effective monitoring of hypertension.

[0003] In the prior art, the blood pressure of a user is usually measured when the user meets the blood pressure measurement condition. If the user moves during the measurement process, or the muscle of the user's blood pressure measurement part contracts, or the user is in an environment with excessively high or low temperature, the blood pressure measurement result will be inaccurate. SUMMARY

[0004] An object of embodiments of the present disclosure is to provide a blood pressure measurement method, an electronic device and a system.

[0005] According to a first aspect of embodiments of the present disclosure, a blood pressure measurement method is provided, comprising:

[0006] acquiring physiological data of a target user collected by a plurality of data collection devices;

[0007] determining whether the target user meets a blood pressure measurement condition according to the physiological data collected by the plurality of data collection devices;

[0008] measuring the blood pressure of the target user when the target user meets the blood pressure measurement condition.

[0009] Optionally, the physiological data collected by at least one of the plurality of data collection devices includes an electromyography signal of a hand of the target user.

[0010] The determining whether the hand state of the target user meets the blood pressure measurement condition according to the physiological data collected by the plurality of data collection devices comprises:

[0011] performing signal analysis and processing on the electromyography signal to obtain a target feature of the electromyography signal;

[0012] determining whether the target user meets the blood pressure measurement condition according to the target feature.

[0013] Optionally, the target feature includes at least one of the following: root mean square, integrated electromyography, median number of power distribution, average frequency of power spectrum.

[0014] Optionally, before the signal analysis and processing of the electromyography signal to obtain the target feature of the electromyography signal, the method further comprises:

[0015] The electromyography signal is pre-processed, and the pre-processing mode comprises at least one of the following: filtering processing, full-wave rectification processing, linear envelope processing, and amplitude normalization processing.

[0016] Optionally, the physiological data collected by the at least one data collection device comprises inertia data of the target user's measurement site within a second set period;

[0017] The physiological data collected by the plurality of data collection devices is used to determine whether the target user meets the blood pressure measurement condition, comprising:

[0018] According to the inertia data, a first variance of acceleration of the target user's measurement site within the second set period is determined;

[0019] According to the inertia data, a second variance of angular velocity change amount of the target user's measurement site within a plurality of third set periods is determined; wherein the second set period includes the plurality of third set periods;

[0020] According to the first variance and the second variance, it is determined whether the target user meets the blood pressure measurement condition.

[0021] Optionally, the physiological data collected by the at least one data collection device comprises temperature data of the environment in which the target user is located within a fourth set period;

[0022] The physiological data collected by the plurality of data collection devices is used to determine whether the target user meets the blood pressure measurement condition, comprising:

[0023] The mean and standard deviation of the temperature data are determined;

[0024] According to the mean and the standard deviation, it is determined whether the target user meets the blood pressure measurement condition.

[0025] Optionally, the method comprises:

[0026] Obtain the clock bias of each data collection device;

[0027] According to the clock bias, the physiological data collected by the plurality of data collection devices is time-aligned.

[0028] Optionally, obtaining the clock bias of any data collection device comprises:

[0029] A target data packet is sent to the any data collection device, and a first time stamp of sending the target data packet is obtained.

[0030] Receive a second timestamp and a third timestamp sent by any of the data acquisition devices, wherein the second timestamp is the timestamp at which any of the data acquisition devices receives the target data packet, and the third timestamp is the timestamp at which any of the data acquisition devices sends the second timestamp;

[0031] Obtain the fourth timestamp that was received from the second timestamp and the third timestamp;

[0032] The clock deviation of any data acquisition device is determined based on the first timestamp, the second timestamp, the third timestamp, and the fourth timestamp.

[0033] According to a second aspect of this disclosure, an electronic device is provided, including a processor and a memory, the memory being used to store a computer program, and the processor being used to perform the method as described in the first aspect of this disclosure under the control of the computer program.

[0034] According to a third aspect of this disclosure, a blood pressure measurement system is provided, including a plurality of data acquisition devices and an electronic device as described in a second aspect of this disclosure, the data acquisition devices being used to acquire physiological data of a target user.

[0035] According to a fourth aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the method described in the first aspect of this disclosure.

[0036] Through the embodiments of this disclosure, based on physiological data collected by multiple data acquisition devices, it is determined whether a target user meets the conditions for blood pressure measurement, and the blood pressure of the target user is measured if the conditions for blood pressure measurement are met, which can improve the accuracy of blood pressure measurement results.

[0037] Other features and advantages of the invention will become clear from the following detailed description of exemplary embodiments of the invention with reference to the accompanying drawings. Attached Figure Description

[0038] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the invention and, together with their description, serve to explain the principles of the invention.

[0039] Figure 1 This is a block diagram illustrating the hardware configuration of an electronic device that can implement embodiments of the present disclosure;

[0040] Figure 2 This is a flowchart of a blood pressure measurement method according to an embodiment of the present disclosure;

[0041] Figure 3This is a schematic diagram of measuring clock deviation according to an embodiment of the present disclosure;

[0042] Figure 4 This is a block diagram of an electronic device according to an embodiment of the present disclosure;

[0043] Figure 5 This is a block diagram of a blood pressure measurement system according to an embodiment of the present disclosure. Detailed Implementation

[0044] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention.

[0045] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0046] Techniques, methods, and apparatus known to those skilled in the art in the relevant field may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification.

[0047] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0048] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0049] <Hardware Configuration>

[0050] Figure 1 This is a block diagram illustrating the hardware configuration of an electronic device that can implement embodiments of the present disclosure.

[0051] Electronic device 1000 can be a portable computer, desktop computer, mobile phone, tablet computer, etc. For example... Figure 1As shown, the electronic device 1000 may include a processor 1100, a memory 1200, an interface device 1300, a communication device 1400, a display device 1500, an input device 1600, a speaker 1700, a microphone 1800, etc. The processor 1100 may be a CPU, a microprocessor (MCU), etc. The memory 1200 may include, for example, ROM (Read-Only Memory), RAM (Random Access Memory), or non-volatile memory such as a hard disk. The interface device 1300 may include, for example, a USB interface, a headphone jack, etc. The communication device 1400 may be capable of wired or wireless communication, specifically including Wi-Fi communication, Bluetooth communication, 2G / 3G / 4G / 5G communication, etc. The display device 1500 may be, for example, an LCD screen, a touch screen, etc. The input device 1600 may include, for example, a touch screen, a keyboard, motion input, etc. Users can input / output voice information through the speaker 1700 and the microphone 1800.

[0052] Figure 1 The electronic devices shown are merely illustrative and in no way intended to limit this disclosure, its application, or use. In embodiments applied to this disclosure, the memory 1200 of the electronic device 1000 is used to store instructions for controlling the processor 1100 to operate to perform any of the methods provided in the embodiments of this disclosure. Those skilled in the art will understand that, although... Figure 1 The electronic device 1000 is shown with multiple devices shown; however, this disclosure may relate only to some of these devices. For example, electronic device 1000 may only relate to processor 1100 and memory 1200. Those skilled in the art can design instructions based on the schemes disclosed herein. How the instructions control the processor to operate is well known in the art and will not be described in detail here.

[0053] <Method Implementation>

[0054] This disclosure provides a method for measuring blood pressure, which can be performed by an electronic device. The electronic device can be, for example,... Figure 1 The electronic device shown is 1000.

[0055] Figure 2 This is a flowchart of a blood pressure measurement method according to an embodiment of the present disclosure.

[0056] like Figure 2 As shown, the method includes the following steps S2100 to S2300:

[0057] Step S2100: Acquire physiological data of the target user collected by multiple data acquisition devices.

[0058] In one embodiment, the electronic device may receive a blood pressure measurement command, send data acquisition commands to multiple data acquisition devices respectively, and the data acquisition devices respond to the data acquisition commands, collect physiological data of the target user, and send the collected physiological data to the electronic device.

[0059] Furthermore, the blood pressure measurement command can be triggered by the target user through voice input, gesture execution, or operation (such as clicking the blood pressure measurement button).

[0060] In this embodiment, multiple data acquisition devices can communicate with the electronic device performing the method of this embodiment via wireless connection such as Bluetooth or WiFi, or via wired connection.

[0061] In this embodiment, the physiological data collected by multiple data acquisition devices may be of the same or different types, and no limitation is made here.

[0062] The physiological data in this embodiment may include electrical signals such as electrocardiogram, electromyography, and electroencephalogram, as well as non-electrical signals such as body temperature, pulse, and heart sounds.

[0063] Specifically, data acquisition devices for collecting electrocardiogram (ECG) signals can be ECG sensors that utilize the principle of bioelectrodes; data acquisition devices for collecting pulse signals can be PPG sensors that utilize optical properties; data acquisition devices for collecting heart sound signals can be PCG sensors that detect mechanical vibrations; data acquisition devices for collecting electromyographic (EMG) signals can be EMG sensors that detect the propagation of motor potentials in muscle fibers; data acquisition devices for collecting temperature data can be ambient temperature (TMP) sensors that utilize the principle of heat conduction; and data acquisition devices for collecting inertial data can be inertial measurement units (IMU) sensors that utilize the law of inertia.

[0064] In one embodiment of this disclosure, the data acquisition device may be a wearable device worn by the target user, such as a watch, headphones, ring, glasses, etc.

[0065] In one embodiment of this disclosure, when physiological data collected by multiple data acquisition devices are obtained, the method may further include: acquiring the clock offset of each data acquisition device; and performing time-series alignment of the physiological data collected by the multiple data acquisition devices based on the clock offset.

[0066] In this embodiment, the clock deviation of the data acquisition device can be the clock deviation of the data acquisition device relative to the electronic device executing this embodiment.

[0067] In this embodiment, the timing alignment of physiological data collected by multiple data acquisition devices is performed based on clock deviation. This can be done on a per-data acquisition device basis, or by adjusting the timing of the physiological data collected by the corresponding data acquisition device based on the clock deviation, so that the timing of the physiological data collected by multiple data acquisition devices is aligned.

[0068] In one embodiment of this disclosure, obtaining the clock deviation of any data acquisition device may include the following steps S2101 to S2104:

[0069] Step S2101: Send the target data packet to any data acquisition device and obtain the first timestamp of the sent target data packet.

[0070] In this embodiment, the first timestamp may be added to the target data packet and sent to any data acquisition device.

[0071] Step S2102: Receive a second timestamp and a third timestamp sent by any data acquisition device, wherein the second timestamp is the timestamp at which any data acquisition device receives the target data packet, and the third timestamp is the timestamp at which any data acquisition device sends the second timestamp.

[0072] In this embodiment, when any data acquisition device receives the target data packet, it may obtain a second timestamp of the target data packet received by the data acquisition device and send the second timestamp to the electronic device.

[0073] Furthermore, any data acquisition device may also send a third timestamp, which sends the second timestamp, to the electronic device.

[0074] Furthermore, any data acquisition device may add a second timestamp and a third timestamp to the target data packet.

[0075] Step S2103: Obtain the fourth timestamp that was received from the second and third timestamps.

[0076] Step S2104: Determine the clock deviation of any data acquisition device based on the first timestamp, the second timestamp, the third timestamp, and the fourth timestamp.

[0077] Given that the first timestamp is T1, the second timestamp is T2, the third timestamp is T3, and the fourth timestamp is T4, a schematic diagram of the clock deviation measurement of the electronic device can be as follows: Figure 3 As shown.

[0078] In this embodiment, the time taken for any data acquisition device to process data is T3-T2, the time taken for the entire transmission process is T4-T1, the transmission time of data in the transmission link is duration=(T4-T1)–(T3–T2), and the clock deviation of any data acquisition device can be offset=[(T2–T1)+(T3-T4)] / 2.

[0079] By aligning the physiological data collected by multiple data acquisition devices in a time sequence, the accuracy of the determination of whether the target user meets the blood pressure measurement conditions can be guaranteed. This provides a data foundation for subsequent blood pressure measurement and calculation, thereby ensuring the accuracy of the blood pressure measurement results.

[0080] Step S2200: Based on the physiological data collected by multiple data acquisition devices, determine whether the target user meets the conditions for blood pressure measurement.

[0081] In this embodiment, the blood pressure measurement conditions may include at least one of the following: relaxed hand posture, stable posture of the measurement site, and suitable ambient temperature.

[0082] In one embodiment of this disclosure, at least one of the multiple data acquisition devices acquires physiological data including electromyographic signals of the target user's hand.

[0083] In one example, the electromyographic signal can be the electromyographic signal within a first set time period. The duration of the first set time period can be preset according to the application scenario or specific needs; for example, the duration of the first set time period can be 5 seconds.

[0084] In this embodiment, based on physiological data collected by multiple data acquisition devices, it is determined whether the target user meets the conditions for blood pressure measurement, including the following steps S2211 to S2212:

[0085] Step S2211: Perform signal analysis and processing on the electromyographic signal to obtain the target features of the electromyographic signal.

[0086] In one embodiment of this disclosure, the target features include at least one of the following: root mean square, integral electromyography, median number of power distribution, and average frequency of power spectrum.

[0087] In embodiments where the target feature includes the root mean square (RMS), the RMS can be obtained using the following formula:

[0088]

[0089] Where RMS represents the root mean square, N represents the number of the first sampling times within the first set time period, and x i This represents the amplitude of the electromyographic signal at the i-th first sampling moment within the first set time period.

[0090] In embodiments where the target feature includes integral electromyography (EMG), the integral EMG can be obtained using the following formula:

[0091]

[0092] Where iEMG represents integrated electromyography, x(t) represents the amplitude of the electromyographic signal at the first sampling time t within the first set time period, t1 represents the start time of the first set time period, and t2 represents the end time of the first set time period.

[0093] In embodiments where the target feature includes the median number of the power distribution, the electromyographic signal can first be subjected to Fourier transform processing to obtain the power spectral density; then, based on the power spectral density, the median number of the power distribution, MidF, can be obtained.

[0094] In embodiments where the target feature includes the average frequency of the power spectrum, the electromyographic signal can first be subjected to Fourier transform processing to obtain the power spectral density; then the average frequency MeanF of the power spectrum can be calculated.

[0095] In one embodiment of this disclosure, before performing signal analysis processing on the electromyographic signal in step S2211 to obtain the target features of the electromyographic signal, the method further includes: preprocessing the electromyographic signal, the preprocessing method including at least one of the following: filtering processing, full-wave rectification processing, linear envelope processing, amplitude normalization processing.

[0096] In embodiments where preprocessing includes filtering, the method may include using a Gaussian filter to eliminate the DC component in the signal; removing the signal's offset in the overall horizontal direction; and may also include using a bandpass filter to remove noise and non-electromyographic signal components that are not within that range.

[0097] In embodiments where preprocessing methods include full-wave rectification, the negative portion of the electromyographic signal may be converted to a positive one to facilitate analysis of the overall amplitude of the electromyographic signal.

[0098] In embodiments where preprocessing includes linear envelope processing, a low-pass filter can be used to obtain the linear envelope of the electromyographic signal, further smoothing the electromyographic signal.

[0099] In embodiments where the preprocessing method includes amplitude normalization, the amplitude of the electromyographic signal may be normalized based on the maximum amplitude of the electromyographic signal within a first set time period.

[0100] In this embodiment, preprocessing the electromyographic signal facilitates signal analysis and processing.

[0101] Step S2212: Based on the target characteristics, determine whether the target user meets the conditions for blood pressure measurement.

[0102] In this embodiment, a first threshold can be set in advance for each target feature according to the application scenario or specific needs, and then each target feature can be compared with the corresponding first threshold. For example, the first threshold corresponding to the root mean square can be set to 5, the first threshold corresponding to the integral electromyography can be set to 3, the first threshold corresponding to the median number of the power distribution can be set to 120, and the first threshold corresponding to the average frequency of the power spectrum can be set to 110.

[0103] In this embodiment, the target user's hand posture can be determined to be relaxed if all target features are less than or equal to the corresponding first threshold; and the target user's hand posture can be determined to be not relaxed if any one or more target features are greater than the corresponding first threshold.

[0104] Muscle contraction causes changes in blood vessels, resulting in altered blood flow and consequently affecting blood pressure measurements. Electromyography (EMG) signals can reflect the amplitude and strength of muscle contractions; denser and higher-amplitude EMG signals indicate stronger muscle contractions. Therefore, EMG signals can be used to determine whether the muscles in the hand are relaxed.

[0105] In one embodiment of this disclosure, the physiological data collected by at least one data acquisition device includes inertial data of the target user's body part during a second set time period. The duration of the second set time period can be preset according to the application scenario or specific needs; for example, the duration of the second set time period can be 3 seconds.

[0106] Furthermore, the area to be tested can be the target user's arm, wrist, or other similar parts.

[0107] In this embodiment, based on physiological data collected by multiple data acquisition devices, it is determined whether the target user meets the conditions for blood pressure measurement, including the following steps S2221 to S2223:

[0108] Step S2221: Determine the first variance of the acceleration of the target user's part to be measured within the second set time period based on the inertial data.

[0109] In this embodiment, the inertial data may include triaxial acceleration data. Therefore, for each axis, the variance of the acceleration at all second sampling times within a second set time period can be determined in advance, namely ax, ay, and az. Then, the first variance a = ax + ay + az can be obtained based on the variance of the acceleration for each axis.

[0110] Step S2222: Determine the second variance of the change in angular velocity of the target user's part within multiple third set time periods based on inertial data; wherein, the second set time periods include multiple third set time periods.

[0111] In this embodiment, the second predetermined time period can be pre-divided into multiple third predetermined time periods. Specifically, the second predetermined time period can be divided according to the duration of the third predetermined time period, or it can be divided according to the number of third predetermined time periods. The duration or number of third predetermined time periods can be pre-set according to the application scenario or specific requirements. For example, the duration of the third predetermined time period can be 100 milliseconds, and the number of third predetermined time periods can be 100.

[0112] In this embodiment, the inertial data may include three-axis angular velocity data. Therefore, the angular velocity changes rx, ry, and rz within each third set time period can be determined in advance for each axis.

[0113] Specifically, the change in angular velocity over a third predetermined time interval relative to the x-axis can be determined using the following formula:

[0114]

[0115] Where rx represents the change in angular velocity over a third set time period relative to the x-axis, Δt represents the time interval between two adjacent second sampling moments, ωx(n) represents the angular velocity of the j-th second sampling moment corresponding to the x-axis within the third set time period, and m represents the number of second sampling moments within a third set time period.

[0116] Correspondingly, the change in angular velocity over a third predetermined time period relative to the y-axis can be determined using the following formula:

[0117]

[0118] Where ry represents the change in angular velocity within a third set time period for the y-axis, Δt represents the time interval between two adjacent second sampling moments, ωy(n) represents the angular velocity of the y-axis corresponding to the j-th second sampling moment within the third set time period, and m represents the number of second sampling moments within a third set time period.

[0119] Correspondingly, the change in angular velocity over a third predetermined time period with respect to the z-axis can be determined using the following formula:

[0120]

[0121] Where rz represents the change in angular velocity over a third set time period relative to the z-axis, Δt represents the time interval between two adjacent second sampling moments, ωz(n) represents the angular velocity of the z-axis corresponding to the j-th second sampling moment within the third set time period, and m represents the number of second sampling moments within a third set time period.

[0122] Furthermore, it can be to determine the variance rdx of the angular velocity change over all third set time periods for the x-axis, the variance rdy of the angular velocity change over all third set time periods for the y-axis, and the variance rdz of the angular velocity change over all third set time periods for the z-axis.

[0123] Furthermore, the second variance rd = rdx + rdy + rdz can be obtained from the variances rdx, rdy, and rdz of the angular velocity changes corresponding to each axis.

[0124] Step S2223: Determine whether the target user meets the blood pressure measurement conditions based on the first variance and / or the second variance.

[0125] In this embodiment, the second and third thresholds can be preset according to the application scenario or specific requirements. For example, the second threshold can be set to 0.1 m / s. 2 Set the third threshold to 0.1 rad. 2 .

[0126] In an embodiment of determining whether a target user meets the blood pressure measurement conditions based on a first variance and a second variance, the first variance may be compared with a second threshold, and the second variance may be compared with a third threshold. If the first variance is less than or equal to the second threshold and the second variance is less than or equal to the third threshold, the posture of the target user's measurement site is determined to be stable. If the first variance is greater than the second threshold and / or the second variance is greater than the third threshold, the posture of the target user's measurement site is determined to be unstable.

[0127] In an embodiment of determining whether a target user meets the blood pressure measurement conditions based on a first variance, the first variance may be compared with a second threshold. If the first variance is less than or equal to the second threshold, the posture of the target user's measurement site is determined to be stable; if the first variance is greater than the second threshold, the posture of the target user's measurement site is determined to be unstable.

[0128] In an embodiment of determining whether a target user meets the blood pressure measurement conditions based on the second variance, the second variance may be compared with a third threshold. If the second variance is less than or equal to the third threshold, the posture of the target user's measurement site is determined to be stable; if the second variance is greater than the third threshold, the posture of the target user's measurement site is determined to be unstable.

[0129] In this embodiment, if the user's measurement site moves during the measurement process, it will affect the quality of the blood pressure measurement results. Therefore, inertial data can be used to determine whether the posture of the measurement site is stable.

[0130] In one embodiment of this disclosure, the physiological data collected by at least one data acquisition device includes temperature data of the target user's environment during a fourth preset time period. The duration of the fourth preset time period can be pre-set according to the application scenario or specific needs; for example, the duration of the fourth preset time period can be 5 seconds.

[0131] In this embodiment, based on physiological data collected by multiple data acquisition devices, it is determined whether the target user meets the conditions for blood pressure measurement, including the following steps S2231 to S2232:

[0132] Step S2231: Determine the statistical parameters of the temperature data.

[0133] The statistics for temperature data may include the mean and / or standard deviation of the temperature data.

[0134] Step S2232: Based on the statistical data of temperature, determine whether the target user meets the conditions for blood pressure measurement.

[0135] In this embodiment, the normal range for each statistic can be set in advance according to the application scenario or specific needs. For example, the normal range for the mean can be set to be greater than or equal to 20 and less than or equal to 25, and the normal range for the standard deviation can be set to be less than or equal to 0.5.

[0136] In an embodiment of determining whether a target user meets the conditions for blood pressure measurement based on the mean and standard deviation of temperature data, it can be determined whether the mean and standard deviation of the temperature data are both within the corresponding normal range. If the mean and standard deviation of the temperature data are both within the corresponding normal range, it can be determined that the ambient temperature of the target user is suitable. If the mean and / or standard deviation of the temperature data exceed the corresponding normal range, it can be determined that the ambient temperature of the target user is unsuitable.

[0137] In an embodiment of determining whether a target user meets the conditions for blood pressure measurement based on the average temperature data, it can be determined whether the average temperature data is within the corresponding normal range. If the average temperature data is within the corresponding normal range, it can be determined that the ambient temperature of the target user is suitable; if the average temperature data exceeds the corresponding normal range, it can be determined that the ambient temperature of the target user is unsuitable.

[0138] In an embodiment of determining whether a target user meets the conditions for blood pressure measurement based on the standard deviation of temperature data, it can be determined whether the standard deviation of the temperature data is within the corresponding normal range. If the standard deviation of the temperature data is within the corresponding normal range, it can be determined that the ambient temperature of the target user is suitable; if the standard deviation of the temperature data exceeds the corresponding normal range, it can be determined that the ambient temperature of the target user is unsuitable.

[0139] This embodiment allows for the determination of whether a target user meets the conditions for blood pressure measurement based on at least one of electromyography signals, inertial data, and temperature data.

[0140] Step S2300: If the target user meets the blood pressure measurement conditions, measure the blood pressure of the target user.

[0141] When blood pressure measurement conditions include relaxed hand posture and / or stable posture of the measurement site, the electronic device can detect whether the target user meets the blood pressure measurement conditions based on electromyographic signals and / or inertial data at a set detection frequency upon receiving a blood pressure measurement command. During the measurement of the target user's blood pressure, if it is detected that the target user's hand posture is not relaxed and / or the posture of the measurement site is unstable, a first prompt message can be output to remind the target user to maintain a stable posture and relaxed hand posture; if the number of times the target user's hand posture is not relaxed and / or the posture of the measurement site is unstable reaches a set number, the blood pressure measurement of the target user can be stopped.

[0142] In this embodiment, the first prompt information may be text information and / or voice information, and there is no limitation on this.

[0143] Furthermore, the detection frequency and the number of times can be preset according to the application scenario or specific needs. For example, the detection frequency can be 10Hz and the number of times can be 3.

[0144] Furthermore, once the target user's blood pressure measurement results are obtained, the acquisition of the target user's electromyographic signals and / or inertial data can be stopped to reduce the power consumption of the data acquisition device and electronic equipment.

[0145] When blood pressure measurement conditions include a suitable ambient temperature, the electronic device can detect whether the target user meets the blood pressure measurement conditions based on temperature data after receiving a blood pressure measurement command. If the ambient temperature is detected to be suitable, blood pressure measurement of the target user begins; if the ambient temperature is detected to be unsuitable, a second prompt message can be output to remind the target user that the blood pressure measured in the current environment may be inaccurate. Furthermore, if the ambient temperature is detected to be unsuitable, blood pressure measurement of the target user can continue or not be performed; this is not limited to this option.

[0146] In this embodiment, the second prompt information may be text information and / or voice information, and there is no limitation on this.

[0147] Through the embodiments of this disclosure, based on physiological data collected by multiple data acquisition devices, it is determined whether a target user meets the conditions for blood pressure measurement, and the blood pressure of the target user is measured if the conditions for blood pressure measurement are met, which can improve the accuracy of blood pressure measurement results.

[0148] <Electronic Device Examples>

[0149] This embodiment provides an electronic device, such as... Figure 4 As shown, the electronic device 4000 may include a processor 4100 and a memory 4200. The memory 4200 is used to store computer programs, and the processor 4100 is used to control the electronic device to execute the methods of any embodiment of this disclosure under the control of the computer programs.

[0150] <System Implementation>

[0151] This embodiment provides a blood pressure measurement system, such as Figure 5 As shown, the blood pressure measurement system 5000 may include multiple data acquisition devices 5100 and the electronic device 4000 described in the foregoing embodiments.

[0152] The data acquisition device 5100 can be used to collect physiological data of target users.

[0153] In this embodiment, each data acquisition device 5100 can communicate with the electronic device 4000. Specifically, the data acquisition device 5100 can communicate with the electronic device 4000 via a wireless connection such as Bluetooth or WiFi, or via a wired connection.

[0154] In this embodiment, the physiological data collected by multiple data acquisition devices may be of the same or different types, and no limitation is made here.

[0155] The physiological data in this embodiment may include electrical signals such as electrocardiogram, electromyography, and electroencephalogram, as well as non-electrical signals such as body temperature, pulse, and heart sounds.

[0156] Specifically, data acquisition devices for collecting electrocardiogram (ECG) signals can be ECG sensors that utilize the principle of bioelectrodes; data acquisition devices for collecting pulse signals can be PPG sensors that utilize optical properties; data acquisition devices for collecting heart sound signals can be PCG sensors that detect mechanical vibrations; data acquisition devices for collecting electromyographic (EMG) signals can be EMG sensors that detect the propagation of motor potentials in muscle fibers; data acquisition devices for collecting temperature data can be ambient temperature (TMP) sensors that utilize the principle of heat conduction; and data acquisition devices for collecting inertial data can be inertial measurement units (IMU) sensors that utilize the law of inertia.

[0157] In one embodiment of this disclosure, the data acquisition device may be a wearable device worn by the target user, such as a watch, headphones, ring, glasses, etc.

[0158] <Example of a readable storage medium>

[0159] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, performs the methods described in any of the method embodiments of this disclosure.

[0160] This invention can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of the invention.

[0161] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0162] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0163] The computer program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of the invention.

[0164] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0165] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0166] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0167] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. It will be known to those skilled in the art that implementation in hardware, implementation in software, and implementation using a combination of software and hardware are equivalent.

[0168] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein. The scope of the invention is defined by the appended claims.

Claims

1. A method for measuring blood pressure, characterized in that, include: Acquire physiological data of the target user collected by multiple data acquisition devices; Based on the physiological data collected by the multiple data acquisition devices, it is determined whether the target user meets the blood pressure measurement conditions; the blood pressure measurement conditions include relaxed hand posture and stable posture of the body part to be measured. If the target user meets the blood pressure measurement conditions, the blood pressure of the target user shall be measured. The physiological data includes electromyographic signals of the target user's hand and inertial data of the target user's test site during a second set time period; The step of determining whether the target user's hand condition meets the blood pressure measurement conditions based on the physiological data collected by the multiple data acquisition devices includes: The electromyographic signals are subjected to signal analysis and processing to obtain the target features of the electromyographic signals; Based on the target characteristics, determine whether the target user meets the blood pressure measurement conditions of relaxed hand posture; Based on the inertial data, determine the first variance of the acceleration of the target user's measured part during the second set time period; The second variance of the change in angular velocity of the target user's measured part within multiple third set time periods is determined based on the inertial data; wherein, the second set time periods include the multiple third set time periods; Based on the first variance and the second variance, determine whether the target user meets the blood pressure measurement condition of postural stability at the test site.

2. The method according to claim 1, characterized in that, The target features include at least one of the following: root mean square, integral electromyography, median number of power distribution, and average frequency of power spectrum.

3. The method according to claim 1, characterized in that, Before performing signal analysis processing on the electromyographic signal to obtain the target features of the electromyographic signal, the method further includes: The electromyographic signal is preprocessed, and the preprocessing method includes at least one of the following: filtering, full-wave rectification, linear envelope processing, and amplitude normalization.

4. The method according to claim 1, characterized in that, The physiological data collected by at least one data acquisition device includes temperature data of the environment in which the target user is located during a fourth set time period; The step of determining whether the target user meets the blood pressure measurement conditions based on the physiological data collected by the multiple data acquisition devices includes: Determine the mean and standard deviation of the temperature data; Based on the mean and the standard deviation, determine whether the target user meets the blood pressure measurement conditions.

5. The method according to claim 1, characterized in that, The method includes: Obtain the clock offset for each data acquisition device; The physiological data collected by the multiple data acquisition devices are time-aligned according to the clock deviation.

6. The method according to claim 5, characterized in that, Obtain the clock offset of any data acquisition device, including: Send a target data packet to any of the data acquisition devices, and obtain the first timestamp of sending the target data packet; Receive a second timestamp and a third timestamp sent by any of the data acquisition devices, wherein the second timestamp is the timestamp at which any of the data acquisition devices receives the target data packet, and the third timestamp is the timestamp at which any of the data acquisition devices sends the second timestamp; Obtain the fourth timestamp that was received from the second timestamp and the third timestamp; The clock deviation of any data acquisition device is determined based on the first timestamp, the second timestamp, the third timestamp, and the fourth timestamp.

7. An electronic device, characterized in that, It includes a processor and a memory, the memory being used to store a computer program, and the processor being used, under the control of the computer program, to execute the method as described in any one of claims 1 to 6.

8. A blood pressure measurement system, characterized in that, It includes multiple data acquisition devices and the electronic device as described in claim 7, wherein the data acquisition devices are used to collect physiological data of the target user.

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