Blood pressure measurement method and wearable device

Abstract

Disclosed are a blood pressure measurement method and a wearable device, relating to the technical field of blood pressure measurement. The blood pressure measurement function can be achieved on the basis of blood pressure monitoring without changing the form of the wearable device, such as without needing to integrate devices like an air pump and a pressure sensor. The method is applied to the wearable device. According to the method, the wearable device can measure a pulse wave signal of a user by means of a PPG sensor, and measure an electrocardiogram signal of the user by means of a wireless sensor, so as to calculate a measured PTT value according to the pulse wave signal and the electrocardiogram signal, thereby achieving blood pressure measurement according to the measured PTT value.

Description

Blood pressure detection method and wearable device

[0001] The present application claims priority to the Chinese patent application No. 202411312062.6, filed on September 19, 2024, and entitled "Blood pressure detection method and wearable device", the whole content of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present application relates to the technical field of blood pressure measurement, in particular to a blood pressure detection method and a wearable device. BACKGROUND

[0003] Portable blood pressure detection is beneficial for users to know blood pressure signs in time, evaluate their own health conditions, and prevent related cardiovascular diseases. Common non-invasive blood pressure detection methods mainly include a flat tension method based on a pressure sensor, a constant volume method based on blood volume change monitoring, and a photoplethysmography (PPG) method based on a PPG sensor.

[0004] The wearable device such as a wearable watch detects blood pressure based on the flat tension method, adopts a micro air pump combined with a pressure sensor to measure systolic pressure and diastolic pressure in the air exhaust process, so as to obtain a blood pressure measurement value. This method needs to integrate a micro air pump device on the wearable watch, changes the common form of the wearable watch, and cannot be used on a general wearable watch, thereby reducing the aesthetic degree.

[0005] Therefore, how to realize the blood pressure detection function on the basis of monitoring blood pressure without changing the form of the wearable device such as without integrating an air pump, a pressure sensor and other devices is needed to be researched. SUMMARY

[0006] The present application provides a blood pressure detection method and a wearable device, which can detect blood pressure through a wearable device integrated with a PPG sensor and a wireless sensor, so that the wearable device can measure user blood pressure without additional devices such as an air bag, and realizes the blood pressure measurement function of the user while maintaining the original appearance of the wearable device.

[0007] To achieve the above purpose, the present application adopts the following technical solutions:

[0008] In a first aspect, a blood pressure detection method is provided, which is applied to a wearable device including a photoplethysmographic (PPG) sensor and a wireless sensor. In the method, the PPG sensor is used to send a light signal to a wrist part of a user to measure a first pulse wave signal of the user. The wireless sensor is used to send a wireless radio frequency signal to a heart part of the user to measure a first electrocardio signal of the user. A pulse transit time (PTT) value is determined according to the first pulse wave signal and the first electrocardio signal, and the PTT value is used to determine a blood pressure detection value of the user.

[0009] In the method, the wearable device integrated with the PPG sensor and the wireless sensor can simultaneously measure the pulse wave signal of the user by using the PPG sensor and measure the electrocardio signal of the user by using the wireless sensor, so that the PTT value can be calculated according to the pulse wave signal and the electrocardio signal. In this way, the wearable device does not need to be provided with an air bag or other additional devices to measure the blood pressure of the user, and the original appearance of the wearable watch is maintained, and the blood pressure measurement function of the user is also realized. The blood pressure detection value can include a pulse wave conduction velocity, a systolic pressure and a diastolic pressure.

[0010] In a possible design, the determination of the pulse transit time (PTT) value according to the first pulse wave signal and the first electrocardio signal can include: performing trough point detection on the electrocardio signal in the first electrocardio signal within a quasi-static time period to determine K segment signals, the segment signal including a pulse wave signal and an electrocardio signal between two adjacent trough points, K being a positive integer. An effective segment signal set is determined according to the time lengths of the K segment signals, the effective segment signal set including K segment signals arranged in a descending order of time length proportion probability, and K and N being positive integers. A first segment signal in the effective segment signal set, in which a maximum peak time of the electrocardio signal is less than a maximum peak time of the pulse wave signal, is used to calculate a PTT value corresponding to the first segment signal, and the PTT value corresponding to the first segment signal is equal to the maximum peak time of the pulse wave signal in the first segment signal minus the maximum peak time of the electrocardio signal in the first segment signal. The PTT value is determined according to the PTT value corresponding to the first segment signal. In this way, the wearable device can calculate the PTT value between the electrocardio signal and the pulse wave signal by performing signal segmentation processing on the first electrocardio signal and the first pulse wave signal, and performing time length consistency evaluation on the segment signals, so as to realize blood pressure detection.

[0011] In a possible design, the method of the first aspect can further include: when the ratio of the measured PTT value to the reference PTT value is greater than a first PTT threshold or less than a second PTT threshold, performing blood pressure abnormality warning, and the reference PTT value is determined according to a PTT value corresponding to a historical normal blood pressure of the user. In this way, the wearable device can further determine whether the blood pressure of the user is abnormal according to the measured PTT value calculated by the final measurement, and perform warning processing if the blood pressure is abnormal, so as to timely remind the user.

[0012] In a possible design, the method of the first aspect can further include: displaying the blood pressure detection value on a display interface of the wearable device. In this way, the wearable device can further display the detected blood pressure detection value on the display interface, so as to facilitate the user to obtain the blood pressure detection value.

[0013] In a second aspect, a wearable device is provided, which includes: a PPG sensor, a wireless sensor, and a processor. The PPG sensor is configured to send an optical signal to a wrist part of a user and measure a first pulse wave signal of the user. The wireless sensor is configured to send a wireless radio frequency signal to a heart part of the user and measure a first electrocardio signal of the user. The processor is configured to determine a measured PTT value according to the first pulse wave signal and the first electrocardio signal, and the measured PTT value is used to determine a blood pressure detection value of the user.

[0014] In a possible design, the processor is configured to determine a measured pulse wave transmission time (PTT) value according to the first pulse wave signal and the first electrocardio signal, and specifically includes: the processor is configured to perform trough point detection on the electrocardio signal in the first electrocardio signal within a quasi-static time period, to determine K segment signals, the segment signal includes a pulse wave signal and an electrocardio signal between two adjacent trough points, and K is a positive integer. The processor is configured to determine an effective segment signal set according to the time length of the K segment signals, and the effective segment signal set includes K segment signals arranged from high to low in time length proportion probability within the first N segment signals, and K and N are positive integers. The processor is configured to calculate a PTT value corresponding to a first segment signal in the effective segment signal set, and the maximum peak time of the electrocardio signal of the first segment signal is less than the maximum peak time of the pulse wave signal. The PTT value corresponding to the first segment signal is equal to the maximum peak time of the pulse wave signal in the first segment signal minus the maximum peak time of the electrocardio signal in the first segment signal. The processor is configured to determine the measured PTT value according to the PTT value corresponding to the first segment signal.

[0015] In a possible design, the wearable device further includes a voice system; when the ratio of the measured PTT value to the reference PTT value is greater than a first PTT threshold value or less than a second PTT threshold value, the voice system is configured to send an abnormal blood pressure warning according to the alarm signal sent by the processor, and the reference PTT value is determined according to a PTT value corresponding to a historical normal blood pressure of the user.

[0016] In a possible design, the wearable device further includes a display interface, and the display interface is configured to display the blood pressure detection value.

[0017] In a third aspect, a wearable device is provided, including a processor and a memory, where the memory is configured to store a computer program, and the processor is configured to invoke the computer program to enable the wearable device to perform the method in the first aspect.

[0018] In a fourth aspect, a chip is provided, including a processing circuit configured to perform the method in the first aspect.

[0019] In a fifth aspect, a computer readable storage medium is provided, and the computer readable storage medium stores a computer program or instructions, which, when executed, implement the method in the first aspect.

[0020] In a sixth aspect, a computer program product is provided, and the computer program product includes computer executable instructions, which, when executed, implement the method in the first aspect. BRIEF DESCRIPTION OF DRAWINGS

[0021] FIG. 1 is a structural schematic diagram of a wearable device for blood pressure detection according to an embodiment of the present application;

[0022] FIG. 2 is a schematic diagram of a wearable device in the form of a wearable watch according to an embodiment of the present application;

[0023] FIG. 3 is a schematic diagram of a posture of a user using a wearable device for blood pressure detection according to an embodiment of the present application;

[0024] FIG. 4 is a flowchart of a blood pressure detection method according to an embodiment of the present application;

[0025] FIG. 5 is a waveform diagram of a first pulse wave signal measured by a PPG sensor and a first electrocardio signal measured by a wireless sensor according to an embodiment of the present application;

[0026] FIG. 6 is a time length statistical histogram of a segment signal according to an embodiment of the present application;

[0027] FIG. 7 is a schematic diagram of a fitting curve according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second", etc. are used to distinguish the same or similar items with basically the same function and role. For example, the first value and the second value are only used to distinguish different values, and the order is not limited. Those skilled in the art can understand that the terms "first", "second", etc. do not limit the quantity and execution order, and the terms "first", "second", etc. also do not mean that they must be different.

[0029] In the embodiments of the present application, the descriptions such as "when", "in the case of", "if", etc. mean that the device will make corresponding processing under certain objective circumstances, not limited to time, and also does not require the device to have a judgment action when implemented, and does not mean that there are other limitations.

[0030] In the embodiments of the present application, the words "exemplary" or "for example" are used to indicate an example, illustration or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the words "exemplary" or "for example" are intended to present the relevant concept in a specific manner, and to facilitate understanding.

[0031] In the present application, "at least one" means one or more, and "multiple" means two or more. The association relationship between the associated objects is described by "and / or", which means that there can be three relationships, for example, A and / or B, which can represent the following three cases: A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after it. "At least one of the following" or similar expressions means any combination of these items, including any combination of single item or multiple items. For example, at least one of a, b, or c, can represent a, b, c, a and b, a and c, b and c, or a, b and c, where a, b, and c can be single or multiple.

[0032] Finally, the network architecture and business scenarios described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems as the network architecture evolves and new business scenarios appear.

[0033] Various aspects, embodiments or features described herein can be presented in terms of systems that can include a number of devices, components, modules, and the like. It should be appreciated that various systems can include additional devices, components, modules, etc. and / or can not include all of the devices, components, modules etc. discussed in connection with the figures. A combination of these approaches can also be used.

[0034] Portable blood pressure detection is beneficial for users to know blood pressure signs in time, evaluate their own health conditions, and prevent related cardiovascular diseases. Common non-invasive blood pressure detection methods mainly include a flat tension method based on a pressure sensor, a constant volume method based on blood volume change monitoring, and a photoplethysmography (PPG) method based on a PPG sensor.

[0035] A wearable device such as a wearable watch is currently used as a portable blood pressure detection method. The wearable watch uses a micro air pump combined with a pressure sensor to measure systolic pressure and diastolic pressure in the gas exhaust process based on the flat tension method, so as to obtain a blood pressure measurement value. However, this method needs to integrate a micro air pump device on a watchband of the wearable watch, changes a common form of the watch, cannot be used on a general wearable watch, and reduces the aesthetic degree.

[0036] Another blood pressure measurement method based on pulse transit time (PTT) requires simultaneous use of an electrocardiogram (ECG) probe to measure a heart beat signal and a watchband PPG sensor to measure a pulse wave for simultaneous measurement. This requires a traditional wearable watch to simultaneously and synchronously measure the PPG sensor and the ECG probe, which is difficult to implement.

[0037] Therefore, how to realize blood pressure detection function without changing the form of a wearable device such as without integrating an air pump, a pressure sensor, and the like to monitor blood pressure is a problem to be solved.

[0038] To this end, an embodiment of the present application provides a blood pressure detection method and a wearable device. A PTT measurement value is obtained by integrating a wireless sensor to measure an ECG signal and a PPG sensor to measure a pulse wave signal on the wearable device, and blood pressure estimation and abnormal alarm are performed through the PTT measurement value.

[0039] Referring to FIG. 1, it is a structural schematic diagram of a wearable device suitable for blood pressure detection according to an embodiment of the present application. As shown in FIG. 1, the wearable device includes a processor and a PPG sensor and a wireless sensor connected to the processor.

[0040] The processor is the control center of the wearable device, used to implement the processing function or capability of the wearable device, and can be one processor or a collective term of multiple processing elements. The processor can include one or more processing units, for example: the processor can include an application processor (AP), a modem processor, a graphics processing unit (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. Among them, different processing units can be independent devices, or can be integrated in one or more processors.

[0041] For another example, the processor includes one or more central processing units (CPUs), and can also be an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application, such as one or more microprocessors (digital signal processors, DSPs), or one or more field programmable gate arrays (FPGAs).

[0042] In a specific implementation, as an embodiment, the processor can include one or more CPUs, such as CPU0 and CPU1.

[0043] In a specific implementation, as an embodiment, the wearable device can also include multiple processors. Each of these processors can be a single-core processor or a multi-core processor. The processor here can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0044] The controller can generate operation control signals according to instruction operation codes and timing signals to complete the control of fetching and executing instructions.

[0045] The processor can further include a memory for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. The memory can hold instructions or data that the processor has just used or is using repeatedly. If the processor needs to use the instructions or data again, it can be directly called from the memory. This avoids repeated access and reduces the waiting time of the processor, thereby improving the efficiency of the system.

[0046] In a possible design, the memory can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magneto-optical disk, a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.

[0047] In a possible design, the processor can perform various functions of the wearable device by running or executing software programs stored in the memory and calling data stored in the memory. The memory is configured to store software programs for implementing the solutions of the present application and is controlled by the processor to perform the software programs. For details, refer to the method embodiments described above, which will not be described here again. It should be understood that the memory and the processor can also be independently arranged.

[0048] In the embodiments of the present application, the processor can be configured to perform synchronization processing on the PPG signal and the wireless signal, extract the pulse wave signal and the electrocardio signal, perform PTT calculation, obtain a blood pressure detection value, and output and display, etc.

[0049] The wireless sensor can include an antenna for transmitting a sensing signal, such as a wireless radio frequency signal transmitted by the wireless sensor through the antenna.

[0050] The PPG sensor is an optoelectronic sensor that detects changes in blood flow by transmitting light signals and measuring changes in the intensity of reflected or transmitted light. When the heart beats, the flow of blood in the arteries causes changes in the volume of the blood vessels, which are captured by the optoelectronic sensor and converted into an electrical signal, i.e., a PPG signal.

[0051] The wireless sensor is a wireless radio frequency sensor that detects changes in heartbeats by transmitting wireless radio frequency signals and measuring reflected signals. For example, the wireless sensor can be an ultra wideband (UWB) sensor, a wireless fidelity (Wi-Fi) sensor, a Bluetooth sensor, or other sensors that can be used for short-range communication, and the wireless radio frequency signal can be a radar signal or other sensing signals, such as a stepped frequency continuous waveform (SFCW) signal, a continuous wave (CW) signal, a frequency modulated continuous waveform (FMCW) signal, a linear frequency modulated (LFM) signal, or the like.

[0052] In the embodiments of the present application, the devices or modules in the wearable device specifically include the following functions:

[0053] The PPG sensor is configured to transmit an optical signal to a wrist part of the user and measure a first pulse wave signal of the user. That is, the PPG sensor is configured to collect a pulse wave signal of the wrist part of the user.

[0054] The wireless sensor is configured to transmit a wireless radio frequency signal to a heart part of the user and measure a first electrocardio signal of the user. That is, the wireless sensor is configured to collect an electrocardio signal of the heart of the user.

[0055] The processor is configured to determine a measured PTT value according to the first pulse wave signal and the first electrocardio signal, and the measured PTT value is used to determine a blood pressure detection value of the user.

[0056] In a possible design, the processor is configured to determine a measured pulse wave transmission time (PTT) value according to the first pulse wave signal and the first electrocardiosignal, specifically including: the processor is configured to perform trough point detection on the electrocardiosignal in the first electrocardiosignal within a quasi-static time period, to determine K segment signals, the segment signal including a pulse wave signal and an electrocardiosignal between two adjacent trough points, K being a positive integer. The processor is configured to determine an effective segment signal set according to the time length of the K segment signals, the effective segment signal set including the segment signals in the K segment signals arranged from high to low in terms of time length proportion probability, K and N being positive integers. The processor is configured to calculate a PTT value corresponding to a first segment signal in the effective segment signal set, the first segment signal being a segment signal in which the maximum peak time of the electrocardiosignal is less than the maximum peak time of the pulse wave signal. The PTT value corresponding to the first segment signal is equal to the maximum peak time of the pulse wave signal in the first segment signal minus the maximum peak time of the electrocardiosignal in the first segment signal. The processor is configured to determine the measured PTT value according to the PTT value corresponding to the first segment signal.

[0057] Optionally, the wearable device further includes a display interface and a voice system connected with the processor. The display interface is configured to display images, texts, videos, etc. The display interface is, for example, a display screen. The voice system is configured to realize audio functions, such as music playing, voice playing, recording, etc. The voice system can include an audio module, a loudspeaker, a receiver, a microphone, etc.

[0058] The audio module is configured to convert digital audio information into an analog audio signal output, and is also configured to convert an analog audio input into a digital audio signal. The loudspeaker, also known as a "horn", is configured to convert an audio electrical signal into a sound signal. The receiver, also known as a "earpiece", is configured to convert an audio electrical signal into a sound signal. The microphone, also known as a "microphone", "sound receiver", is configured to convert a sound signal into an electrical signal.

[0059] In the embodiments of the present application, the display interface is configured to display a blood pressure detection value. After the processor calculates the blood pressure detection value, the processor can send a signal to the display interface to display the blood pressure detection value on the display interface. The voice system is configured to voice prompt, such as prompting a user to start and end blood pressure detection, prompting a user to display a blood pressure detection result, alarming a user of blood pressure abnormality, etc. The present application is not limited in this regard.

[0060] In the embodiments of the present application, when the ratio of the measured PTT value to the reference PTT value is greater than a first PTT threshold value or less than a second PTT threshold value, the voice system is configured to alarm a blood pressure abnormality according to an alarm signal sent by the processor. The reference PTT value is determined according to a PTT value corresponding to a historical normal blood pressure of the user.

[0061] The specific implementation of the functions of the modules in the wearable device shown in FIG. 1 can be seen from the following method embodiments, and will not be repeated here.

[0062] The sensor in the embodiments of the present application can be a chip, an integrated module, etc., and is not limited in this regard. It should be understood that the wearable device can also be integrated with other functional sensors, modules, or chips, etc., such as a temperature sensor, a barometric pressure sensor, a camera, etc., and is not limited in this regard.

[0063] For example, the wearable device is a wearable watch, and as shown in FIG. 2, the wearable watch is integrated with a PPG sensor and a wireless sensor. When the user uses the wearable watch to detect blood pressure, the user can adopt a lying position or a sitting position for measurement. As shown in (a) of FIG. 3, the user adopts a lying position for measurement, and as shown in (b) of FIG. 3, the user adopts a sitting position for measurement. During the measurement process, the user's wrist is close to / near the heart position, is level with the heart, and remains stationary for blood pressure measurement. It is recommended that the wireless sensor antenna side be close to / near the user's heart side to ensure the accuracy of the wireless measurement of the electrocardiogram signal. The left hand is best for measurement, and is placed against the chest to maximize the reduction of the influence of the respiratory harmonic on the wireless sensor electrocardiogram signal detection. After the measurement preparation is completed, the blood pressure measurement is started, and a voice prompt is given to indicate that the measurement has started.

[0064] The method for detecting blood pressure based on the wearable device shown in FIG. 1 in the posture shown in FIG. 3 is as follows:

[0065] For example, FIG. 4 is a blood pressure detection method provided by the embodiments of the present application, which is applied to the wearable device shown in FIG. 1 or FIG. 2. The subject performing the actions of the wearable device in the method can also be a device / module in the wearable device, such as a chip, a processor, a processing unit, etc., in the wearable device, and the embodiments of the present application are not limited in this regard.

[0066] As shown in FIG. 4, the blood pressure detection method includes the following steps.

[0067] S401, the wearable device sends an optical signal to the wrist of the user through the PPG sensor to measure a first pulse wave signal of the user.

[0068] After the user starts the wearable device to detect blood pressure, the wearable device sends an optical signal to the wrist of the user through the PPG sensor. The optical signal is absorbed by the radial artery and reflected to the PPG sensor after passing through the skin of the user. The reflected optical signal is converted into a PPG signal by the PPG sensor through photoelectric conversion, so that the PPG sensor can obtain a periodic first pulse wave signal through sampling and processing of the PPG signal. The specific implementation of the measurement of the pulse wave signal by the PPG sensor can be seen from the existing implementation, and will not be repeated here.

[0069] For example, the sampling frequency of the PPG sensor can be greater than or equal to 100 hertz (Hz). It should be understood that the greater the sampling frequency, the smaller the distortion rate of the signal, which can ensure the integrity and accuracy of the signal.

[0070] In S402, the wearable device sends a wireless radio frequency signal to the heart of the user through the wireless sensor to measure the first electrocardio signal of the user.

[0071] In addition to measuring the pulse wave, the wearable device also sends a wireless radio frequency signal to the heart of the user through the wireless sensor, for example, the wireless radio frequency signal is a radar signal, the wireless sensor continuously sends a CW signal or a FMCW signal pulse to the heart of the user in radar mode, so that the wireless sensor receives the CW signal or the FMCW signal reflected by the heart, i.e., a radar echo signal, and processes the received CW signal or FMCW signal to obtain the first electrocardio signal.

[0072] For example, the signal frame rate of the wireless sensor sending the wireless radio frequency signal can be consistent with the sampling frequency of the PPG sensor, such as greater than or equal to 100 Hz.

[0073] For example, the wireless sensor performs in-phase quadrature (IQ) phase unwrapping on the received CW / FMCW signal, and the unwrapping method can obtain a time sequence phase change signal waveform by using an existing arctan / differantiate and cross-multiply (DACM) / modified differantiate and cross-multiply (MDACM) method. At the same time, the wireless sensor also performs Doppler measurement based on the received CW / FMCW signal to analyze whether the current scene is a quasi-static scene, and if the current scene is a quasi-static scene, the phase value of the current unwrapping signal is taken as a valid value. The valid time sequence phase value is band-pass filtered to obtain an electrocardio signal waveform (ECG), i.e., the first electrocardio signal.

[0074] As shown in FIG. 5, it is a waveform diagram of the first pulse wave signal measured by the PPG sensor and the first electrocardio signal measured by the wireless sensor of a wearable device, which shows the changes of the pulse wave signal and the electrocardio signal of the user in the body movement time, and the changes of the pulse wave signal and the electrocardio signal in the quasi-static time period.

[0075] It should be understood that the wearable device processes the first pulse wave signal and the first electrocardio signal collected in the same time period, which can be considered as the duration of blood pressure detection of the wearable device.

[0076] The wearable device sends the light signal through the PPG sensor, which can be understood as the wearable device sending the light signal based on the PPG sensor or using the PPG sensor to send the light signal. The wearable device sends the wireless radio frequency signal through the wireless sensor, which can be understood as the wearable device sending the wireless radio frequency signal based on / using the wireless sensor. In one possible implementation, after the processor in the wearable device receives the start signal of blood pressure detection, it can send trigger signals to the PPG sensor and the wireless sensor respectively to perform measurement of the pulse wave signal and the electrocardio signal respectively.

[0077] S403, the wearable device determines a measurement PTT value according to the first pulse wave signal and the first electrocardio signal, and the measurement PTT value is used to determine the blood pressure detection value of the user.

[0078] After the wearable device obtains the first pulse wave signal based on the PPG sensor and the first electrocardio signal based on the wireless sensor, it performs PTT value calculation on the first pulse wave signal and the first electrocardio signal to obtain the measurement PTT value, so as to calculate the blood pressure detection value of the user according to the measurement PTT value. The blood pressure detection value used to measure the blood pressure state of the user can include pulse wave velocity (PWV), systolic blood pressure (SBP) and diastolic blood pressure (DBP).

[0079] The specific implementation process of the wearable device for determining the measurement PTT value according to the first pulse wave signal and the first electrocardio signal can be as follows:

[0080] (1) The wearable device can perform trough point detection on the electrocardio signal in the first electrocardio signal located in the quasi-static time period to determine K segment signals.

[0081] Among them, the segment signal includes the pulse wave signal and the electrocardio signal located between two adjacent trough points, and K is a positive integer.

[0082] That is, the wearable device detects the trough points of the electrocardiosignal in the quasi-static time period in the first electrocardiosignal, and takes the electrocardiosignal between the adjacent two trough points in the first electrocardiosignal and the pulse wave signal between the adjacent two trough points in the first pulse wave signal as a segment signal, that is, the segment signal includes the electrocardiosignal and the pulse wave signal in the same time period, which is the time between the adjacent two trough points of the electrocardiosignal in the quasi-static time period in the first electrocardiosignal. Thus, the wearable device can perform signal segmentation processing on the first pulse wave signal and the first electrocardiosignal according to the number of trough points of the electrocardiosignal in the quasi-static time period in the first electrocardiosignal, to obtain K segment signals. It can be understood that the number K of segment signals is the total number of trough points minus one.

[0083] For example, referring to the first electrocardiosignal waveform and the first pulse wave signal waveform shown in FIG. 5, the wearable device detects that the electrocardiosignal in the quasi-static time period in the first electrocardiosignal has 3 trough points, i.e. trough point 1-trough point 3, then the wearable device takes the electrocardiosignal between the trough point 1 and the trough point 2 in the first electrocardiosignal and the pulse wave signal between the trough point 1 and the trough point 2 in the first pulse wave signal as a segment signal, i.e. segment signal 1, and the time length of the segment signal 1 is the time difference between the trough point 1 and the trough point 2 such as Δt1, takes the electrocardiosignal between the trough point 2 and the trough point 3 in the first electrocardiosignal and the pulse wave signal between the trough point 2 and the trough point 3 in the first pulse wave signal as a segment signal, i.e. segment signal 2, and the time length of the segment signal 2 is the time length of the segment signal 1, which is the time difference between the trough point 2 and the trough point 3 such as Δt2. Thus, the wearable device obtains two segment signals, and the time lengths of the two segment signals are Δt1 and Δt2 respectively.

[0084] In the embodiments of the present application, the time length of the segment signal can also be referred to as the period of the segment signal, which is not limited.

[0085] (2) The wearable device can determine the effective segment signal set according to the time lengths of the K segment signals.

[0086] The effective segment signal set includes the segment signals with the top N time length proportion from high to low in the K segment signals, and K and N are positive integers.

[0087] That is, the wearable device can evaluate the consistency of the time length of the K segment signals according to the wave trough points of the electrocardiosignal in the quasi-static time period, that is, judge the difference between the time length of each segment signal. For example, the wearable device can perform histogram statistics on the time length of the K segment signals, and count the segment signals with the same time length or with a particularly small time length difference (e.g., less than a first threshold) as the same time length segment signals. The number of segment signals corresponding to each time length is counted, as shown in FIG. 6. The K segment signals are counted to obtain time lengths t_1, t_2, t_3, t_4, t_5, t_6, and t_7.

[0088] Therefore, the wearable device arranges the probability (or proportion) of the number of segment signals corresponding to each time length in the K segment signals in descending order, and arranges the segment signals corresponding to the time length with the top N probability as effective segment signals, such as the segment signals corresponding to the time length t_3, t_4, and t_5 in FIG. 6, to form an effective segment signal set.

[0089] In some embodiments, the wearable device can also arrange the number of segment signals corresponding to each time length in descending order, and arrange the segment signals corresponding to the time length with the top N number as effective segment signals to form an effective segment signal set, which is not limited.

[0090] For example, N = 2 and K = 10, that is, there are 10 segment signals, the time length of segment signal 1 to segment signal 4 corresponds to time length 1, the time length of segment signal 5 and segment signal 6 corresponds to time length 2, the time length of segment signal 7 to segment signal 9 corresponds to time length 3, and the time length of segment signal 10 corresponds to time length 4. Therefore, the wearable device can determine that the proportion of the segment signals corresponding to time length 1 and time length 4 is in the top 2, and then the wearable device arranges segment signal 1 to segment signal 4 and segment signal 7 to segment signal 9 as effective segment signals to form an effective segment signal set, that is, the effective segment signal set includes segment signal 1 to segment signal 4 and segment signal 7 to segment signal 9.

[0091] (3) The wearable device can calculate the PTT value corresponding to the first segment signal in the effective segment signal set, where the maximum peak time of the electrocardiosignal is less than the maximum peak time of the pulse wave signal.

[0092] The PTT value corresponding to the first segment signal is equal to the maximum peak time of the pulse wave signal in the first segment signal minus the maximum peak time of the electrocardiosignal in the first segment signal.

[0093] That is, after the wearable device obtains the set of valid segment signals, it can determine which of the valid segment signals in the set of valid segment signals has a maximum peak time of the electrocardiogram signal smaller than a maximum peak time of the pulse wave signal. For example, the wearable device can search for the maximum peak of the pulse wave signal and the electrocardiogram signal in each valid segment signal, and determine the valid segment signal whose electrocardiogram signal has a maximum peak time smaller than the maximum peak time of the pulse wave signal as a first segment signal, and calculate the PTT value corresponding to the first segment signal. It should be understood that there can be multiple first segment signals, and the wearable device can calculate the PTT value corresponding to each first segment signal.

[0094] For example, referring to FIG. 5, segment signal 1 and segment signal 2 are both valid segment signals, and the maximum peak time of the electrocardiogram signal in segment signal 1 is smaller than the maximum peak time of the pulse wave signal, and the maximum peak time of the electrocardiogram signal in segment signal 2 is smaller than the maximum peak time of the pulse wave signal, i.e., segment signal 1 and segment signal 2 are both first segment signals. Thus, the wearable device can calculate the PTT value corresponding to segment signal 1 as the maximum peak time t_p1 of the pulse wave signal in segment signal 1 minus the maximum peak time t_e1 of the electrocardiogram signal in the first segment signal, i.e., t_p1-t_e1, and calculate the PTT value corresponding to segment signal 1 as the maximum peak time t_p2 of the pulse wave signal in segment signal 2 minus the maximum peak time t_e2 of the electrocardiogram signal in the first segment signal, i.e., t_p2-t_e2.

[0095] (4) The wearable device can determine the measured PTT value according to the PTT value corresponding to the first segment signal.

[0096] After the wearable device obtains the PTT values corresponding to the multiple first segment signals, it can calculate the mean value, weighted value, etc. of the multiple PTT values to obtain a measured PTT value, so that the PWV, SBP and DBP of the user can be calculated according to the measured PTT value.

[0097] For example, the PWV can be calculated according to the following formula: PWV=L / PTT d ;

[0098] Wherein, L is the arm length of the user, and PTT d is the measured PTT value.

[0099] The SBP and DBP can be calculated according to the following formulas, respectively:

[0100] Wherein, SBP0, DBP0, PTT0 and γ are statistical values for a certain population, which can also be referred to as reference values.

[0101] Since the calculation of SBP and DBP are both associated with the statistical values of a certain population, considering the difference of individual population, the user can input the reference value of user's daily SBP and DBP (such as the SBP and DBP measured by other blood pressure measuring devices) into the wearable device to obtain the fitting curve y=k1x+b1 of the gold standard correction value as shown in FIG. 7. Then, the wearable device can obtain the DBP / SBP according to the statistical PTT main distribution interval value of the user (such as the hollow circle point in FIG. 7) to obtain the fitting curve y=k0x+b0 of the DBP / SBP calculated according to the measured PTT value calculated by the wearable device, as shown in FIG. 7. Thus, the wearable device can obtain the following correction formula, that is, the individual blood pressure measurement value is corrected according to the correction curve function on the basis of the above formula and the corrected measurement value is given:

[0102] Therefore, the wearable device can output the corrected DBP and SBP as the final blood pressure detection value.

[0103] In a possible design, after obtaining the measured PTT value, the wearable device can perform proportional conversion on the measured PTT value and the reference PTT value, and perform blood pressure abnormality warning when the proportion exceeds the threshold, wherein the reference PTT value is determined according to the PTT value corresponding to the historical normal blood pressure of the user.

[0104] When the proportion of the measured PTT value relative to the reference PTT value (i.e., the ratio of the measured PTT value to the reference PTT value) is greater than a first PTT threshold (or greater than or equal to the first PTT threshold), it can be considered that the user's blood pressure is high, and the wearable device performs blood pressure abnormality warning; or when the proportion of the measured PTT value relative to the reference PTT value is less than a second PTT threshold (or less than or equal to the first PTT threshold), it can be considered that the user's blood pressure is low, and the wearable device performs blood pressure abnormality warning. Thus, the user can be reminded that the measured blood pressure state is abnormal.

[0105] After the wearable device ends or completes blood pressure detection, the wearable device can also display the blood pressure detection value on its display interface.

[0106] In the blood pressure detection method shown in FIG. 4, the wearable device integrated with the PPG sensor and the wireless sensor can simultaneously measure the pulse wave signal of the user by using the PPG sensor and measure the electrocardio signal of the user by using the wireless sensor, so as to calculate the PTT value according to the pulse wave signal and the electrocardio signal. In this way, the wearable device does not need to be provided with an air bag or other additional devices to measure the blood pressure of the user, and the original appearance of the wearable watch is maintained, and the blood pressure measurement function of the user is also realized.

[0107] It can be understood that, in each of the above embodiments, the method and / or steps implemented by the wearable device can also be implemented by components (such as a processor, a chip, a chip system, a circuit, a logic module, or software) available to the wearable device.

[0108] In another aspect, the embodiments of the present application further provide a chip, comprising a processing circuit configured to perform the method according to the above embodiments.

[0109] In another aspect, the embodiments of the present application further provide a computer program product comprising instructions, and the computer program product comprises computer executable instructions, which, when executed, implement the method according to the above embodiments.

[0110] In another aspect, the embodiments of the present application further provide a computer readable storage medium. The computer readable storage medium stores a computer program or instructions, which, when executed, implement the method according to the above embodiments.

[0111] Those skilled in the art can understand that the modules and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0112] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and module can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0113] In several embodiments of the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, for example, the division of the modules is only a logical function division, and actual implementation can have another division manner, for example, a plurality of modules or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interface, device or module, which can be electrical, mechanical or other forms.

[0114] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, i.e., may be located in one device or distributed over multiple devices. Some or all of the modules can be selected according to actual needs to achieve the purposes of the embodiments of the present application.

[0115] In addition, the functional modules in the various embodiments of the present application can be integrated in one device, or each module can exist physically alone, or two or more modules can be integrated in one device.

[0116] In the above embodiments, all or part can be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or data storage device including one or more servers, data centers, etc. integrated with the medium. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a digital video disk (DVD)), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0117] In addition, the communication architecture and service scenarios described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions proposed in the embodiments of the present application. Those skilled in the art can know that, as the communication architecture evolves and new service scenarios appear, the technical solutions proposed in the embodiments of the present application are also applicable to similar technical problems.

[0118] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A blood pressure detection method characterized by, Applied to a wearable device comprising a photoplethysmographic (PPG) sensor and a wireless sensor, the method comprises: sending, by the PPG sensor, an optical signal to a wrist part of a user, and measuring a first pulse wave signal of the user; sending, by the wireless sensor, a wireless radio frequency signal to a heart part of the user, and measuring a first electrocardio signal of the user; determining a measurement pulse transit time (PTT) value according to the first pulse wave signal and the first electrocardio signal, the measurement PTT value being used to determine a blood pressure detection value of the user.

2. The method of claim 1, wherein, The method further comprises: when a proportion of the measurement PTT value relative to a reference PTT value is greater than a first PTT threshold value or less than a second PTT threshold value, performing a blood pressure abnormality alarm, the reference PTT value being determined according to a PTT value corresponding to a historical normal blood pressure of the user. The method further comprises: a PPG sensor, a wireless sensor, and a processor; wherein the PPG sensor is configured to send an optical signal to a wrist part of a user, and measure a first pulse wave signal of the user; 3. The method according to claim 1 or 2, characterized in that, the wireless sensor is configured to send a wireless radio frequency signal to a heart part of the user, and measure a first electrocardio signal of the user; the processor is configured to determine a measurement PTT value according to the first pulse wave signal and the first electrocardio signal, the measurement PTT value being used to determine a blood pressure detection value of the user.

4. A wearable device, comprising: The processor is configured to determine a measurement pulse transit time (PTT) value according to the first pulse wave signal and the first electrocardio signal, comprising that the processor is configured to perform wave trough point detection on an electrocardio signal of the first electrocardio signal within a quasi-static time period, and determine K segment signals, the segment signal comprising a pulse wave signal and an electrocardio signal between adjacent two wave trough points, K being a positive integer; the processor is configured to determine an effective segment signal set according to time lengths of the K segment signals, the effective segment signal set comprising K segment signals arranged from high to low in a time length proportion probability within the K segment signals, K and N being positive integers; the processor is configured to calculate a PTT value corresponding to a first segment signal in the effective segment signal set, the first segment signal being a segment signal in which a maximum peak time of an electrocardio signal is less than a maximum peak time of a pulse wave signal, the PTT value corresponding to the first segment signal being equal to the maximum peak time of the pulse wave signal in the first segment signal minus the maximum peak time of the electrocardio signal in the first segment signal; the processor is configured to determine the measurement PTT value according to the PTT value corresponding to the first segment signal. The method further comprises:

5. The apparatus of claim 4, wherein, when a proportion of the measurement PTT value relative to a reference PTT value is greater than a first PTT threshold value or less than a second PTT threshold value, performing a blood pressure abnormality alarm, the reference PTT value being determined according to a PTT value corresponding to a historical normal blood pressure of the user. The method further comprises: a PPG sensor, a wireless sensor, and a processor; wherein the PPG sensor is configured to send an optical signal to a wrist part of a user, and measure a first pulse wave signal of the user; the wireless sensor is configured to send a wireless radio frequency signal to a heart part of the user, and measure a first electrocardio signal of the user; the processor is configured to determine a measurement PTT value according to the first pulse wave signal and the first electrocardio signal, the measurement PTT value being used to determine a blood pressure detection value of the user. The processor is configured to determine a measurement pulse transit time (PTT) value according to the first pulse wave signal and the first electrocardio signal, comprising that the processor is configured to perform wave trough point detection on an electrocardio signal of the first electrocardio signal within a quasi-static time period, and determine K segment signals, the segment signal comprising a pulse wave signal and an electrocardio signal between adjacent two wave trough points, K being a positive integer; The processor is configured to determine an effective segment signal set according to time lengths of the K segment signals, the effective segment signal set including segment signals with time lengths arranged from high to low in a probability of N first segment signals in the K segment signals, K and N being positive integers. The processor is configured to calculate a PTT value corresponding to a first segment signal in the effective segment signal set, the first segment signal being an electrocardiogram signal with a maximum peak time less than a maximum peak time of a pulse wave signal. The processor is configured to determine the measured PTT value according to the PTT value corresponding to the first segment signal.

6. The apparatus of claim 4 or 5, wherein, The wearable device further includes a voice system. When a ratio of the measured PTT value to a reference PTT value is greater than a first PTT threshold value or less than a second PTT threshold value, the voice system is configured to perform blood pressure abnormality warning according to an alarm signal sent by the processor, the reference PTT value being determined according to a PTT value corresponding to a historical normal blood pressure of the user.

7. A chip, characterized by The processing circuit is configured to perform the method of any one of claims 1-3.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program or instructions, which, when executed, implement the method of any one of claims 1-3.

9. A computer program product, characterised in that, The computer program product includes computer executable instructions, which, when executed, implement the method of any one of claims 1-3.

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