Blood pressure monitoring method and device, wearable equipment and medium

Abstract

The invention provides a blood pressure monitoring method and device, wearable equipment and a medium, the method is applied to the wearable equipment, and the method comprises the steps that under the condition that a blood pressure monitoring function is in an on state, PPG signals of a wearer are continuously collected through a PPG sensor of the wearable equipment; according to the PPG signal in the latest time period and a set blood pressure mutation recognition model, obtaining a blood pressure mutation recognition result of the wearer in the latest time period; and when the blood pressure mutation recognition result is blood pressure mutation, outputting a prompt that the blood pressure mutation recognition result is blood pressure mutation to a wearer.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the technical field of wearable devices, and more specifically, to a blood pressure monitoring method, apparatus, wearable device, and medium. Background Art

[0002] Blood pressure changes, especially short-term blood pressure mutations, are a very important health indicator, which is of great significance for early disease intervention and patients under clinical observation. The onset of many hypertension-related diseases is characterized by a sharp rise in blood pressure, which may lead to serious life-threatening consequences in a short period of time. However, severe blood pressure elevation may actually have no or only mild symptoms, which makes blood pressure mutation monitoring crucial.

[0003] In the related art, the commonly used technology for blood pressure monitoring on non-cuff wearable devices is to collect the wearer's current photoplethysmography (PPG) signal, electrocardiogram (ECG) signal, and phonocardiogram (PCG) signal, and calculate the current blood pressure value based on the current PPG signal, current ECG signal, and current PCG signal to determine whether the user is at risk of hypertension or hypotension.

[0004] However, when monitoring the current blood pressure value, it is necessary to use PPG signals in combination with ECG signals and PCG signals. But when collecting ECG signals and PCG signals, not only do users need to wear the wearable device correctly, but they also need to keep the set posture and stay still, which affects the user's daily life. Moreover, this type of blood pressure monitoring lacks tracking of the user's blood pressure change trend, and can only rely on the user to actively and repeatedly monitor the blood pressure values ​​at different times throughout the day. Summary of the invention

[0005] One purpose of the embodiments of the present disclosure is to provide a new technical solution for blood pressure monitoring.

[0006] According to a first aspect of an embodiment of the present disclosure, a blood pressure monitoring method is provided, which is applied to a wearable device, and the method includes:

[0007] When the blood pressure monitoring function is turned on, the PPG signal of the wearer is continuously collected through the PPG sensor of the wearable device;

[0008] Obtaining a blood pressure mutation recognition result of the wearer in the latest time period according to the PPG signal in the latest time period and the set blood pressure mutation recognition model;

[0009] When the blood pressure mutation recognition result is a blood pressure mutation, a prompt indicating that the blood pressure mutation recognition result is a blood pressure mutation is output to the wearer.

[0010] Optionally, obtaining the blood pressure mutation recognition result of the wearer in the latest time period according to the PPG signal in the latest time period and setting the blood pressure mutation recognition model includes:

[0011] Obtaining a first-order derivative PPG signal of the PPG signal in the latest time period;

[0012] Acquire a second-order derivative PPG signal of the PPG signal in the latest time period;

[0013] According to the PPG signal, the first-order derivative PPG signal, the second-order derivative PPG signal and the set blood pressure mutation recognition model in the latest time period, the wearer's blood pressure mutation recognition result in the latest time period is obtained.

[0014] Optionally, obtaining a blood pressure mutation recognition result of the wearer in the latest time period according to the PPG signal, the first-order derivative PPG signal, the second-order derivative PPG signal and the set blood pressure mutation recognition model in the latest time period includes:

[0015] Performing feature extraction on the PPG signal, the first-order derivative PPG signal and the second-order derivative PPG signal in the latest time period through the feature extraction network in the set blood pressure mutation recognition model to obtain time series feature information;

[0016] The prediction network in the set blood pressure mutation recognition model is used to predict blood pressure mutation based on the time series feature information to obtain the wearer's blood pressure mutation recognition result within the latest time period.

[0017] Optionally, when the blood pressure monitoring function is turned on, after continuously collecting the wearer's PPG signal through the PPG sensor of the wearable device, the method further includes:

[0018] Writing the PPG signal continuously collected by the PPG sensor into a storage module;

[0019] Read the latest N consecutive frames of PPG signals from the storage module as the PPG signals in the latest time period;

[0020] Wherein, N is a positive integer.

[0021] Optionally, the method further comprises:

[0022] Deleting the other PPG signals stored in the storage module except the latest M consecutive frames of PPG signals at every set time period;

[0023] Wherein, M is a positive integer, and M is greater than N.

[0024] Optionally, the method further comprises:

[0025] Receiving an input operation on the wearable device;

[0026] In response to the input operation, the blood pressure detection function is turned on.

[0027] Optionally, when the blood pressure mutation recognition result is a blood pressure mutation, outputting a prompt to the wearer that the blood pressure mutation recognition result is a blood pressure mutation includes:

[0028] When the blood pressure mutation recognition result is a blood pressure mutation, controlling the output device to prompt that the blood pressure mutation recognition result is a blood pressure mutation;

[0029] When the blood pressure mutation recognition result is a blood pressure mutation, the terminal device connected to the wearable device for communication is controlled to prompt that the blood pressure mutation recognition result is a blood pressure mutation through a target application.

[0030] According to a second aspect of an embodiment of the present disclosure, a blood pressure monitoring device is provided, which is applied to a wearable device, and the device includes:

[0031] A collection module, used for continuously collecting the wearer's PPG signal through the PPG sensor of the wearable device when the blood pressure monitoring function is turned on;

[0032] An identification module, used to obtain an identification result of a wearer's blood pressure mutation within the latest time period according to the PPG signal within the latest time period and a set blood pressure mutation identification model;

[0033] The output module is used to output a prompt to the wearer that the blood pressure mutation recognition result is a blood pressure mutation when the blood pressure mutation recognition result is a blood pressure mutation.

[0034] According to a third aspect of an embodiment of the present disclosure, a wearable device is provided, the wearable device including a PPG sensor, and the wearable device further including:

[0035] Memory for storing executable computer instructions;

[0036] A processor is used to execute the blood pressure monitoring method according to the first aspect above under the control of the executable computer instructions.

[0037] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer instructions are stored. When the computer instructions are executed by a processor, the blood pressure monitoring method described in the first aspect above is executed.

[0038] One of the beneficial effects of the disclosed embodiments is that it can make relatively accurate predictions of blood pressure mutations using only PPG signals. Users only need to wear the wearable device naturally, which can make full use of the user's large amount of free time and continuously and imperceptibly monitor blood pressure, greatly improving user-friendliness. Moreover, after the blood pressure monitoring function is turned on, the wearable device can continuously and imperceptibly collect PPG signals, and by setting a blood pressure recognition model to recognize the PPG signal of the latest time period, the blood pressure mutation recognition result within the latest time period can be obtained. That is, by monitoring the blood pressure mutation within a short period of time, more comprehensive protection can be provided for the user's health, and danger warnings can be issued in the early stages of the disease to reduce sudden injuries.

[0039] Other features and advantages of the present specification will become apparent from the following detailed description of exemplary embodiments of the present specification with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the specification and, together with the description, serve to explain the principles of the specification.

[0041] Figure 1 is a schematic diagram of the structure of a wearable device according to an embodiment of the present disclosure;

[0042] Figure 2 is a flow chart of a blood pressure monitoring method according to an embodiment of the present disclosure;

[0043] Figure 3 is a schematic diagram of management of PPG signals by a wearable device according to an embodiment of the present disclosure;

[0044] Figure 4 is a schematic diagram of the working process of setting a blood pressure mutation recognition model according to an embodiment of the present disclosure;

[0045] Figure 5 is a schematic diagram of the principle of a blood pressure monitoring device according to an embodiment of the present disclosure;

[0046] Figure 6 Schematic diagram of a wearable device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0047] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the embodiments of the present disclosure.

[0048] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.

[0049] The technologies, methods and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but where appropriate, the technologies, methods and equipment should be considered as part of the specification.

[0050] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0051] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0052] <Hardware Configuration>

[0053] Figure 1 1 is a block diagram of a hardware configuration of a wearable device 1000 according to an embodiment of the present disclosure.

[0054] The wearable device 1000 includes, for example but not limited to, a watch and a ring, which is not limited in this embodiment.

[0055] like Figure 1 As shown, the wearable device 1000 may include a processor 1100, a memory 1200, a communication device 1300, an input device 1400, an output device 1500 and a PPG sensor 1600. The processor 1100 may include, but is not limited to, a central processing unit CPU, a microprocessor MCU, etc. The memory 1200 includes, for example, a ROM (read-only memory), a RAM (random access memory), a non-volatile memory such as a hard disk, etc. The communication device 1300 is capable of, for example, wired or wireless communication. The input device 1400 includes, for example, a touch screen. The output device 1500 includes, for example, a vibration output device and an audio output device, wherein the vibration output device can be prompted by vibration, and the audio output device can be prompted by voice and / or a buzzer. The PPG sensor 1600 is used to collect the PPG signal of the wearer.

[0056] In this embodiment, the memory 1200 of the wearable device 1000 is used to store instructions, which are used to control the processor 1100 to operate to implement or support the implementation of the blood pressure monitoring method according to any embodiment. The technician can design instructions according to the scheme disclosed in this specification. How the instructions control the processor to operate is well known in the art, so it will not be described in detail here.

[0057] It should be understood by those skilled in the art that although Figure 1 Multiple devices of the wearable device 1000 are shown in the figure, but the wearable device 1000 of the embodiment of this specification may only involve some of the devices, or may also include other devices, which is not limited here.

[0058] Figure 1 The wearable device 1000 shown is illustrative only and is in no way intended to limit the present description, its application, or uses.

[0059] Hereinafter, various embodiments and examples according to the present disclosure are described with reference to the drawings.

[0060] <Method Example>

[0061] Figure 2 A blood pressure monitoring method according to an embodiment of the present disclosure is shown, which is applied to a wearable device. The blood pressure monitoring method according to this embodiment can be performed as follows. Figure 1 The wearable device 1000 shown is implemented.

[0062] like Figure 2 As shown, the blood pressure monitoring method of this embodiment may include the following steps S2100 to S2300.

[0063] Step S2100: When the blood pressure monitoring function is turned on, the PPG signal of the wearer is continuously collected through the PPG sensor of the wearable device.

[0064] Among them, the wearable device includes a PPG sensor, which is used to collect the wearer's PPG signal. The PPG signal can reflect the changes in blood content in blood vessels over time.

[0065] It can be understood that when the blood pressure monitoring function of the wearable device is turned on, the PPG sensor can continuously collect the wearer's PPG signal. Usually, when the PPG sensor collects the wearer's PPG signal, the user only needs to wear the wearable device naturally, and the user does not need to keep the set posture still. In this way, the user can use a lot of free time to continuously monitor blood pressure without feeling.

[0066] In this embodiment, when the user wears the wearable device and the blood pressure monitoring function of the wearable device is turned on, the wearable device can continuously collect the wearer's PPG signal through the PPG sensor.

[0067] In an optional embodiment, in step S2100, when the blood pressure monitoring function is turned on, before the PPG sensor of the wearable device continuously collects the wearer's PPG signal, the blood pressure monitoring method of the embodiment of the present disclosure further includes: receiving an input operation to the wearable device; and turning on the blood pressure monitoring function in response to the input operation.

[0068] In one example, the wearer can perform touch input on the input device of the wearable device, such as the "blood pressure monitoring control" displayed on the touch screen, and the wearable device can turn on the blood pressure monitoring function. When the blood pressure monitoring function of the wearable device is turned on, the PPG sensor can continuously collect the wearer's PPG signal.

[0069] In another example, a terminal device that establishes a communication connection with a wearable device runs a target application that is compatible with the wearable device. The wearer can turn on the blood pressure monitoring function of the wearable device through the target application run by the terminal device. When the blood pressure monitoring function of the wearable device is turned on, the PPG sensor can continuously collect the wearer's PPG signal.

[0070] When the blood pressure monitoring function is turned on in the above step S2100, the PPG sensor of the wearable device continuously collects the PPG signal of the wearer, and then proceeds to:

[0071] Step S2200, obtaining the wearer's blood pressure mutation recognition result within the latest time period based on the PPG signal within the latest time period and the set blood pressure mutation recognition model.

[0072] Among them, a blood pressure mutation recognition model is set for identifying blood pressure mutations, and the blood pressure mutation recognition model is usually pre-trained based on a training data set. The input of the blood pressure mutation recognition model is set to include at least the PPG signal within the latest time period, and the output of the blood pressure mutation recognition model is set to be the blood pressure mutation recognition result within the latest time period. Usually, the blood pressure mutation recognition result includes blood pressure mutation and no blood pressure mutation. For example, when the output of the blood pressure mutation recognition model is set to "0", it indicates that the blood pressure mutation recognition result is no blood pressure mutation; for another example, when the output of the blood pressure mutation recognition model is set to "1", it indicates that the blood pressure mutation recognition result is a blood pressure mutation.

[0073] In an optional embodiment, obtaining the blood pressure mutation recognition result of the wearer in the latest time period based on the PPG signal in the latest time period and the set blood pressure mutation recognition model in this step S2200 may further include: performing feature extraction on the PPG signal in the latest time period through the feature extraction network in the set blood pressure mutation recognition model to obtain time series feature information; performing blood pressure mutation prediction based on the time series feature information through the prediction network in the set blood pressure mutation recognition model to obtain the blood pressure mutation recognition result of the wearer in the latest time period.

[0074] The feature extraction network may be a long short-term memory (LSTM) network, and the prediction network may be a fully connected layer.

[0075] In the specific implementation, the wearable device inputs the PPG signal in the latest time period into the set blood pressure mutation recognition model, firstly extracts the features of the PPG signal in the latest time period through the feature extraction network in the set blood pressure mutation recognition model to obtain the time series feature information; then, the blood pressure mutation is predicted on the time series feature information through the prediction network in the set blood pressure mutation recognition model to obtain the blood pressure mutation recognition result.

[0076] In an optional embodiment, in step S2200, obtaining the wearer's blood pressure mutation recognition result in the latest time period according to the PPG signal in the latest time period and the set blood pressure mutation recognition model may further include the following steps S2210 to S2230:

[0077] Step S2210, obtaining a first-order derivative PPG signal of the PPG signal in the latest time period.

[0078] The first-order derivative PPG signal is a differential signal of the PPG signal, which is obtained by performing a differential operation on the PPG signal. The first-order derivative PPG signal of the PPG signal can highlight the rate of change in the PPG signal, that is, the change in blood flow velocity.

[0079] Step S2220, obtaining the second-order derivative PPG signal of the PPG signal in the latest time period.

[0080] Among them, the second-order derivative PPG signal is the second-order differential signal of the PPG signal, which is obtained by performing a second differential operation on the PPG signal. The second-order derivative PPG signal further highlights the high-frequency components in the PPG signal, which are related to the tiny vibrations of the blood vessels and the acceleration changes of the blood flow.

[0081] Step S2230, obtaining the blood pressure mutation recognition result of the wearer in the latest time period according to the PPG signal, the first-order derivative PPG signal, the second-order derivative PPG signal and the set blood pressure mutation recognition model in the latest time period.

[0082] Optionally, in step S2230, obtaining the blood pressure mutation recognition result of the wearer in the latest time period according to the PPG signal, the first-order derivative PPG signal, the second-order derivative PPG signal and the set blood pressure mutation recognition model in the latest time period can further include: performing feature extraction on the PPG signal, the first-order derivative PPG signal and the second-order derivative PPG signal in the latest time period through the feature extraction network in the set blood pressure mutation recognition model to obtain time series feature information; performing blood pressure mutation prediction based on the time series feature information through the prediction network in the set blood pressure mutation recognition model to obtain the blood pressure mutation recognition result of the wearer in the latest time period.

[0083] In specific implementation, refer to Figure 4 The PPG signal, first-order derivative PPG signal, and second-order derivative PPG signal in the latest time period are input into the set blood pressure mutation recognition model. The feature extraction network in the blood pressure mutation recognition model is first used to extract the features of the PPG signal, first-order derivative PPG signal, and second-order derivative PPG signal in the latest time period to obtain time series feature information; then the prediction network in the blood pressure mutation recognition model is used to predict the blood pressure mutation on the time series feature information to obtain the blood pressure mutation recognition result.

[0084] After executing the above step S2200 to obtain the wearer's blood pressure mutation recognition result in the latest time period according to the PPG signal in the latest time period and the set blood pressure mutation recognition model, proceed to:

[0085] Step S2300: When the blood pressure mutation recognition result is a blood pressure mutation, output a prompt to the wearer indicating that the blood pressure mutation recognition result is a blood pressure mutation.

[0086] In this embodiment, when the blood pressure mutation recognition result is a blood pressure mutation, the wearable device can output a prompt to the wearer that the blood pressure mutation recognition result is a blood pressure mutation, so as to inform the wearer of the blood pressure mutation.

[0087] In an optional embodiment, in step S2300, when the blood pressure mutation recognition result is a blood pressure mutation, outputting a prompt to the wearer that the blood pressure mutation recognition result is a blood pressure mutation includes at least one of the following:

[0088] Item 1: When the blood pressure mutation recognition result is a blood pressure mutation, controlling the output device to prompt that the blood pressure mutation recognition result is a blood pressure mutation.

[0089] Wherein, the output module includes at least one of a vibration output device and an audio output device.

[0090] Specifically, when the output module includes a vibration output device, if the blood pressure mutation recognition result is a blood pressure mutation, the vibration output device can be controlled to output a prompt to the wearer through vibration that the blood pressure mutation recognition result is a blood pressure mutation.

[0091] When the output module includes an audio output device, if the blood pressure mutation recognition result is a blood pressure mutation, the audio output device can be controlled to output a prompt to the wearer through voice and / or a buzzer that the blood pressure mutation recognition result is a blood pressure mutation.

[0092] Item 2: When the blood pressure mutation recognition result is a blood pressure mutation, controlling a terminal device that is communicatively connected to the wearable device to prompt that the blood pressure mutation recognition result is a blood pressure mutation through a target application.

[0093] Specifically, if the result of the blood pressure mutation recognition is a blood pressure mutation, the wearable device can send a control instruction through the terminal device with which the wearable device has established a communication connection, and the control instruction is used to control the terminal device to prompt that the result of the blood pressure mutation recognition is a blood pressure mutation. The terminal device receives the control instruction and outputs a voice prompt and / or text prompt to the wearer through the target application running that the result of the blood pressure mutation recognition is a blood pressure mutation.

[0094] According to this embodiment, only the PPG signal can be used to make a relatively accurate prediction of blood pressure mutations. The user only needs to wear the wearable device naturally, which can make full use of the user's large amount of free time and continuously and imperceptibly monitor blood pressure, greatly improving user-friendliness. In addition, after the blood pressure monitoring function is turned on, the wearable device can continuously and imperceptibly collect PPG signals, and by setting a blood pressure recognition model to recognize the PPG signal of the latest time period, the blood pressure mutation recognition result within the latest time period can be obtained. That is, by monitoring the blood pressure mutation in a short period of time, more comprehensive protection can be provided for the user's health, and danger warnings can be issued in the early stage of the disease to reduce sudden injuries.

[0095] In one embodiment, after executing the above step S2100 and the blood pressure monitoring function is in the turned-on state, the PPG signal of the wearer is continuously collected by the PPG sensor of the wearable device, the blood pressure monitoring method of the embodiment of the present disclosure further includes: writing the PPG signal continuously collected by the PPG sensor into a storage module; reading the latest N consecutive frames of PPG signal from the storage module as the PPG signal within the latest time period; wherein N is a positive integer; and deleting other PPG signals stored in the storage module except for the latest continuous M frames of PPG signal every set time period; wherein M is a positive integer, and M is greater than N.

[0096] Among them, other PPG signals except the latest continuous M-frame PPG signals in the storage module can be understood as expired PPG signals.

[0097] The set time period may be set according to actual scenarios and actual needs, and this embodiment does not limit this.

[0098] In specific implementation, the PPG sensor can write the continuously collected PPG signals into the storage module of the wearable device. If the user manually ends the blood pressure test, the data collection and writing process is stopped. The wearable device can process the PPG signals stored in the storage module in two aspects:

[0099] On the one hand, the wearable device can find the latest N consecutive frames of PPG signals in the storage module as the PPG signals in the latest time period, and package the PPG signals in the latest time period. Then, based on the packaged PPG signals in the latest time period and the set blood pressure mutation recognition model, the wearer's blood pressure mutation recognition result in the latest time period is obtained.

[0100] On the other hand, the wearable device can actively release expired PPG signals in the storage module every set time period, retain only the latest continuous M-frame PPG signals in the storage module, and release and discard other PPG signals except the latest continuous M-frame PPG signals.

[0101] Reference Figure 3 , the latest PPG signal collected by the PPG sensor is PPG signal 1. The latest N consecutive frames of PPG signals include PPG signal 1, PPG signal 2, PPG signal 3, PPG signal 4, PPG signal 5, PPG signal 6, PPG signal 7 and PPG signal 8. The latest M consecutive frames of PPG signals include PPG signal 1, PPG signal 2, PPG signal 3, PPG signal 4, PPG signal 5, PPG signal 6, PPG signal 7, PPG signal 8, PPG signal 9 and PPG signal 10, that is, M is 10, N is 8, and M>N. The expired PPG signal includes PPG signal 1.

[0102] The wearable device can use the latest continuous 8 frames of PPG signals, namely PPG signal 1, PPG signal 2, PPG signal 3, PPG signal 4, PPG signal 5, PPG signal 6, PPG signal 7 and PPG signal 8, as the PPG signals in the latest time period, and package the PPG signals in the latest time period.

[0103] The wearable device can also continue to store 10 consecutive frames of PPG signals, namely PPG signal 1, PPG signal 2, PPG signal 3, PPG signal 4, PPG signal 5, PPG signal 6, PPG signal 7, PPG signal 8, PPG signal 9, and PPG signal 10, in the storage module, which is equivalent to retaining but not packaging the two frames of PPG signals, PPG signal 9 and PPG signal 10, and storing them in the storage module as a cache, so as to use them as alternative PPG signals for blood pressure mutation identification when problems occur in the above 8 consecutive frames of PPG signals. The wearable device can also actively release PPG signal 11 from the storage module.

[0104] According to the above-mentioned method of managing the PPG signal stored in the storage module, it is possible to ensure that the wearable device is in a healthy state so as to operate for a long time.

[0105] <Example>

[0106] An example of a blood pressure monitoring method is shown below. In this example, the blood pressure monitoring method further includes:

[0107] Step 401, start the blood pressure monitoring function of the wearable device.

[0108] Step 402: When the blood pressure monitoring function of the wearable device is turned on, the PPG signal of the wearer is continuously collected through the PPG sensor of the wearable device and written into the storage module of the wearable device.

[0109] Step 403, the signal management module of the wearable device is responsible for processing the PPG signals stored in the storage module. On the one hand, the signal management module reads the latest N consecutive frames of PPG signals from the storage module and packages them as the PPG signals in the latest time period. On the other hand, the signal management module is responsible for releasing the expired signals in the storage module, retaining only the latest M consecutive frames of PPG signals in the storage module, and releasing and discarding the remaining PPG signals, M>N.

[0110] In step 404, the feature extraction network of the neural network prediction module of the wearable device extracts features from the PPG signal within the latest time period, the first-order derivative PPG signal of the PPG signal, and the second-stage PPG signal of the PPG signal to obtain time series feature information; and the prediction module of the neural network prediction module predicts blood pressure mutations on the time series feature information to obtain the blood pressure mutation recognition result of the wearer within the latest time period.

[0111] Exemplarily, the blood pressure mutation recognition results at different times are shown in the following Table 1, wherein the blood pressure mutation recognition result is "1", indicating that there is a blood pressure mutation, and the blood pressure mutation recognition result is "0", indicating that there is no blood pressure mutation.

[0112] Table 1 Blood pressure mutation recognition results

[0113] date time Sudden changes in blood pressure 2024.1.1 7:00 0 2024.1.1 7:20 1 …… …… …… 2024.12.31 14:30 0 2024.12.31 14:40 0

[0114] Step 405: When the blood pressure mutation recognition result is a blood pressure mutation, the wearable device controls the vibration output device to output a prompt to the wearer that the blood pressure mutation recognition result is a blood pressure mutation, and / or controls the terminal device connected to the wearable device for communication to prompt that the blood pressure mutation recognition result is a blood pressure mutation through the target application.

[0115] According to this example, compared with the existing technology, the blood pressure monitoring method provided by it transforms the blood pressure prediction task from the traditional numerical prediction (regression task) to the change trend prediction (classification task), which has the following two advantages: First, by increasing the monitoring of blood pressure mutations in a short period of time, it can provide more comprehensive protection for the user's health, and can provide danger warnings in the early stage of the disease to reduce sudden injuries. Second, this method can make more accurate predictions of blood pressure mutations using only PPG signals, requiring users to wear wearable devices naturally, while the existing accurate blood pressure measurement requires the use of PPG signals and other signals such as ECG signals and PCG signals. Users need to remain still in a certain posture and cannot do other things during this period. This method makes full use of the user's large amount of free time and continuously and imperceptibly monitors blood pressure, greatly improving user-friendliness.

[0116] <Device Example>

[0117] Figure 5 is a schematic diagram of the structure of a blood pressure monitoring device according to an embodiment. Figure 5 As shown, the blood pressure monitoring device 500 includes a collection module 510 , a recognition module 520 and an output module 530 .

[0118] The collection module 510 is used to continuously collect the wearer's PPG signal through the PPG sensor of the wearable device when the blood pressure monitoring function is turned on;

[0119] The identification module 520 is used to obtain the blood pressure mutation identification result of the wearer in the latest time period according to the PPG signal in the latest time period and the set blood pressure mutation identification model;

[0120] The output module 530 is used to output a prompt to the wearer that the blood pressure mutation recognition result is a blood pressure mutation when the blood pressure mutation recognition result is a blood pressure mutation.

[0121] In one embodiment, the identification module 520 is specifically used to obtain the first-order derivative PPG signal of the PPG signal in the latest time period; obtain the second-order derivative PPG signal of the PPG signal in the latest time period; and obtain the blood pressure mutation recognition result of the wearer in the latest time period based on the PPG signal in the latest time period, the first-order derivative PPG signal, the second-order derivative PPG signal and the set blood pressure mutation recognition model.

[0122] In one embodiment, the identification module 520 is specifically used to extract features of the PPG signal, the first-order derivative PPG signal and the second-order derivative PPG signal in the latest time period through the feature extraction network in the set blood pressure mutation identification model to obtain time series feature information; and predict the blood pressure mutation based on the time series feature information through the prediction network in the set blood pressure mutation identification model to obtain the blood pressure mutation identification result of the wearer in the latest time period.

[0123] In one embodiment, the apparatus 500 further includes a writing module and a reading module (neither of which are shown in the figure).

[0124] A writing module, used for writing the PPG signal continuously collected by the PPG sensor into a storage module;

[0125] A reading module, used for reading the latest N consecutive frames of PPG signals from the storage module as the PPG signal in the latest time period;

[0126] Wherein, N is a positive integer.

[0127] In one embodiment, the apparatus 500 further includes a deletion module (not shown in the figure).

[0128] A deleting module, used for deleting other PPG signals stored in the storage module except for the latest M consecutive frames of PPG signals at every set time period;

[0129] Wherein, M is a positive integer, and M is greater than N.

[0130] In one embodiment, the device 500 further includes a receiving module and an opening module (not shown in the figure).

[0131] A receiving module, used for receiving an input operation on the wearable device;

[0132] The activation module is used to activate the blood pressure monitoring function in response to the input operation.

[0133] In one embodiment, the output module 530 is specifically used to control the output device to prompt that the blood pressure mutation recognition result is a blood pressure mutation when the blood pressure mutation recognition result is a blood pressure mutation; and to control the terminal device connected to the wearable device for communication to prompt that the blood pressure mutation recognition result is a blood pressure mutation through a target application when the blood pressure mutation recognition result is a blood pressure mutation.

[0134] According to this embodiment, only the PPG signal can be used to make a relatively accurate prediction of blood pressure mutations. The user only needs to wear the wearable device naturally, which can make full use of the user's large amount of free time and continuously and imperceptibly monitor blood pressure, greatly improving user-friendliness. In addition, after the blood pressure monitoring function is turned on, the wearable device can continuously and imperceptibly collect PPG signals, and by setting a blood pressure recognition model to recognize the PPG signal of the latest time period, the blood pressure mutation recognition result within the latest time period can be obtained. That is, by monitoring the blood pressure mutation in a short period of time, more comprehensive protection can be provided for the user's health, and danger warnings can be issued in the early stage of the disease to reduce sudden injuries.

[0135] <Equipment Embodiment>

[0136] Figure 6 FIG. 1 is a schematic diagram of the hardware structure of a wearable device according to an embodiment. Figure 6 As shown, the wearable device 600 includes a PPG sensor 610 , and the wearable device 600 also includes a processor 620 and a memory 630 .

[0137] The memory 630 may be used to store executable computer instructions.

[0138] The processor 620 can be used to execute the blood pressure monitoring method described in the method embodiment of the present disclosure under the control of the executable computer instructions.

[0139] The wearable device 600 may be Figure 1 The wearable device 1000 shown may also be a device with other hardware structures, which is not limited here. In another embodiment, the wearable device 600 may include the above blood pressure monitoring device 500.

[0140] In one embodiment, each module of the above blood pressure monitoring device 500 can be implemented by the processor 620 running computer instructions stored in the memory 630 .

[0141] <Computer Readable Storage Medium>

[0142] The embodiment of the present disclosure further provides a computer-readable storage medium on which computer instructions are stored. When the computer instructions are executed by a processor, the blood pressure monitoring method provided by the embodiment of the present disclosure is executed.

[0143] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0144] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0145] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0146] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related 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 "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of 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., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0147] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0148] 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 device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0149] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are 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 implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0150] The flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of an instruction, and the module, a program segment or a part of an instruction contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of the boxes in the block diagram and / or the flowchart can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that it is equivalent to implement it by hardware, implement it by software, and implement it by combining software and hardware.

[0151] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the present disclosure is defined by the appended claims.

Claims

1. A blood pressure monitoring method, characterized in that: Applied to a wearable device, the method comprises: When the blood pressure monitoring function is turned on, the PPG signal of the wearer is continuously collected through the PPG sensor of the wearable device; Obtaining a blood pressure mutation recognition result of the wearer in the latest time period according to the PPG signal in the latest time period and the set blood pressure mutation recognition model; When the blood pressure mutation recognition result is a blood pressure mutation, a prompt indicating that the blood pressure mutation recognition result is a blood pressure mutation is output to the wearer.

2. The method according to claim 1, characterized in that: The obtaining, based on the PPG signal in the latest time period and the set blood pressure mutation recognition model, a blood pressure mutation recognition result of the wearer in the latest time period includes: Obtain a first-order derivative PPG signal of the PPG signal in the latest time period; Acquire a second-order derivative PPG signal of the PPG signal in the latest time period; According to the PPG signal, the first-order derivative PPG signal, the second-order derivative PPG signal and the set blood pressure mutation recognition model in the latest time period, the wearer's blood pressure mutation recognition result in the latest time period is obtained.

3. The method according to claim 2, characterized in that The obtaining, according to the PPG signal, the first-order derivative PPG signal, the second-order derivative PPG signal and the set blood pressure mutation recognition model in the latest time period, a blood pressure mutation recognition result of the wearer in the latest time period includes: Performing feature extraction on the PPG signal, the first-order derivative PPG signal and the second-order derivative PPG signal in the latest time period through the feature extraction network in the set blood pressure mutation recognition model to obtain time series feature information; The prediction network in the set blood pressure mutation recognition model is used to predict blood pressure mutation based on the time series feature information to obtain the wearer's blood pressure mutation recognition result within the latest time period.

4. The method according to claim 1, characterized in that When the blood pressure monitoring function is turned on, after continuously collecting the PPG signal of the wearer through the PPG sensor of the wearable device, the method further includes: Writing the PPG signal continuously collected by the PPG sensor into a storage module; Read the latest N consecutive frames of PPG signals from the storage module as the PPG signals in the latest time period; Wherein, N is a positive integer.

5. The method according to claim 4, characterized in that The method further comprises: Deleting the other PPG signals stored in the storage module except the latest M consecutive frames of PPG signals at every set time period; Wherein, M is a positive integer, and M is greater than N.

6. The method according to claim 1, characterized in that The method further comprises: Receiving an input operation on the wearable device; In response to the input operation, the blood pressure monitoring function is turned on.

7. The method according to claim 1, characterized in that When the blood pressure mutation recognition result is a blood pressure mutation, outputting a prompt to the wearer that the blood pressure mutation recognition result is a blood pressure mutation includes: When the blood pressure mutation recognition result is a blood pressure mutation, controlling the output device to prompt that the blood pressure mutation recognition result is a blood pressure mutation; When the blood pressure mutation recognition result is a blood pressure mutation, the terminal device connected to the wearable device for communication is controlled to prompt that the blood pressure mutation recognition result is a blood pressure mutation through a target application.

8. A blood pressure monitoring device, characterized in that: Applied to a wearable device, the device comprises: A collection module, used for continuously collecting the wearer's PPG signal through the PPG sensor of the wearable device when the blood pressure monitoring function is turned on; An identification module, used to obtain an identification result of a wearer's blood pressure mutation within the latest time period according to the PPG signal within the latest time period and a set blood pressure mutation identification model; The output module is used to output a prompt to the wearer that the blood pressure mutation recognition result is a blood pressure mutation when the blood pressure mutation recognition result is a blood pressure mutation.

9. A wearable device, characterized in that: The wearable device includes a PPG sensor, and the wearable device also includes: Memory for storing executable computer instructions; A processor is used to execute the blood pressure monitoring method according to any one of claims 1-7 under the control of the executable computer instructions.

10. A computer-readable storage medium having computer instructions stored thereon, wherein the computer instructions are executed by a processor to execute the blood pressure monitoring method according to any one of claims 1 to 7.

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