A device for controlling blood pressure

Abstract

The present invention provides a method and device for controlling blood pressure, the method comprising: S1: establishing or retrieving a first model of pulse wave transmission time and blood pressure; S2: acquiring the user's blood pressure data and health parameter information, and establishing a second model of health parameter information and blood pressure; S3: continuously monitoring the pulse wave transmission time, if the pulse wave transmission time is collected within T1 time, then entering step S4; if the pulse wave transmission time is not collected within T1 time, then entering step S5; S4: obtaining blood pressure data in real time through the first model, and outputting it to step S6; S5: continuously monitoring the health parameter information, and obtaining blood pressure data in real time through the second model; and outputting it to step S6; S6: analyzing the output blood pressure data and judging whether the blood pressure data is within a safe range, if so, returning to step S3, if not, performing electrical stimulation treatment. The present invention can improve the accuracy of blood pressure monitoring and provide treatment in a timely manner.

Description

Technical Field

[0001] The invention relates to a device for controlling blood pressure, belonging to the technical field of health monitoring. Background Art

[0002] Blood pressure is one of the important physiological parameters of the human body. It can reflect the functional status of the human heart and blood vessels. It is an important basis for clinical diagnosis of diseases and observation of medical effects.

[0003] At present, the blood pressure measurement used in clinical practice mainly includes office blood pressure, dynamic blood pressure and home self-measurement of blood pressure. Both office blood pressure and dynamic blood pressure need to be performed in the hospital. The former uses a traditional mercury sphygmomanometer or an automatic sphygmomanometer, which requires professional medical staff to operate or requires relatively large professional equipment. The dynamic sphygmomanometer used in the latter is portable, but it is large in size and must be wrapped around the patient. The measurement is still measured by cuff pressurization, which is not comfortable and has a great impact on the user's normal life. In addition, due to power consumption, hygiene and other reasons, the continuous use time is usually no more than 24 hours. Home self-measurement of blood pressure is mainly achieved through electronic cuffs or wristband sphygmomanometers. The product price is relatively reasonable and the accuracy is also high, but the measurement still requires manual active operation, and it is impossible to perform real-time dynamic monitoring of blood pressure. Moreover, these blood pressure detection methods cannot be adjusted in real time according to the actual situation of the user, nor can they actively intervene in time according to the user's blood pressure situation, and cannot meet the user's usage needs.

[0004] In view of this, it is indeed necessary to provide a device for controlling blood pressure to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to provide a method and device for controlling blood pressure, which can achieve stable monitoring of blood pressure in a complex environment and perform timely intervention treatment.

[0006] To achieve the above-mentioned purpose, the present invention provides a device for controlling blood pressure, comprising a wearable structure and a pulse wave sensing module, a health parameter acquisition module, an electrical stimulation module and a control module arranged on the wearable structure, wherein the pulse wave sensing module is used to acquire the pulse wave signal of the user in real time and transmit the pulse wave signal to the control module, the health parameter acquisition module is used to acquire the health parameters of the user in real time and transmit the health parameters to the control module, the electrical stimulation module is used to apply electrical stimulation to the user's limbs, the control module receives and analyzes the pulse wave signal and the health parameters, and controls the electrical stimulation module to start or stop through the above-mentioned method for controlling blood pressure; the step of the control module controlling the electrical stimulation module to start or stop based on the pulse wave signal and the health parameters comprises: S1: establishing or retrieving the pulse wave conduction time The first model of the user's time and blood pressure is as follows: S2: obtaining the user's blood pressure data and health parameter information, and establishing a second model of the user's health parameter information and blood pressure; S3: continuously monitoring the user's pulse wave conduction time, if the user's pulse wave conduction time is collected within T1 time, then proceed to step S4; if the user's pulse wave conduction time is not collected within T1 time, then proceed to step S5; S4: converting the pulse wave conduction time into blood pressure data in real time through the first model, and outputting the blood pressure data to step S6; S5: continuously monitoring the user's health parameter information, and converting the health parameter information into blood pressure data in real time through the second model; outputting the blood pressure data to step S6; S6: analyzing the output blood pressure data and determining whether the blood pressure data is within a safe range, if so, returning to step S3, if not, performing electrical stimulation treatment on the user.

[0007] As a further improvement of the present invention, the health parameter information includes a constant parameter of the user and at least one time-varying parameter collected by a health parameter collection module.

[0008] As a further improvement of the present invention, the constant parameters are set to m, ranging from L1 to L m Indicates that the time-varying parameters are set to n, with S1(t)~S n (t) represents, where m and n are integers, and m≥1, n≥1. The blood pressure data converted according to the second model is

[0009] ,

[0010] Among them, P 21 is the calculated value of diastolic pressure, P 22 is the calculated value of systolic blood pressure, is the second model matrix, G 11 ~G 1（M+N） and G 21 ~G 2（M+N）are the coefficient parameters calculated according to the neural network algorithm.

[0011] As a further improvement of the present invention, the coefficient parameters in the second model are automatically optimized after reaching a predetermined time t1 and / or a predetermined condition, or are passively optimized after being triggered by a user.

[0012] As a further improvement of the present invention, the method for optimizing the coefficient parameters includes training a network using the blood pressure data obtained by the first model and the blood pressure data obtained by the second model to optimize the coefficient parameters of the second model; and / or training a network using the blood pressure data directly acquired and the blood pressure data obtained by the second model to optimize the coefficient parameters of the second model.

[0013] As a further improvement of the present invention, the electrical stimulation therapy gears are set to multiple levels according to the degree of abnormality of the blood pressure data, and the electrical stimulation intensity and / or electrical stimulation frequency and / or electrical stimulation time and / or the number of repeated electrical stimulations of the multiple levels are different.

[0014] As a further improvement of the present invention, the gear of the electrical stimulation therapy is optimized according to the user's usage and / or after reaching a predetermined time t2.

[0015] As a further improvement of the present invention, the health parameter acquisition module includes a heart rate sensor or a blood oxygen sensor; or, the health parameter acquisition module includes a combination of a heart rate sensor, a blood oxygen sensor, a temperature sensor, a motion sensor, a blood lipid sensor and a skin resistance sensor.

[0016] As a further improvement of the present invention, the device also includes a feedback module, which is communicatively connected with the pulse wave sensing module, the health parameter acquisition module and the control module to monitor the user's blood pressure changes in real time and feed back the blood pressure changes to the control module. The control module adjusts the electrical stimulation intensity and / or electrical stimulation frequency and / or electrical stimulation time and / or number of repetitions of the electrical stimulation module according to the feedback information of the feedback module.

[0017] As a further improvement of the present invention, the device further includes a communication module, and the communication module sends the second model to a server to implement backup of the second model.

[0018] As a further improvement of the present invention, the device further includes a storage module, and the storage module is configured to store constant parameters of multiple users and a second model corresponding to each user.

[0019] The beneficial effect of the present invention is that compared with the prior art, a device for controlling blood pressure of the present invention uses the user's health information parameters to monitor blood pressure in real time when the user's pulse wave signal cannot be monitored, thereby ensuring that blood pressure data can be stably obtained in a complex environment, and timely intervene in the user's blood pressure abnormality to prevent it from deteriorating, forming a closed loop of blood pressure monitoring and blood pressure intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The present invention is a flow chart of a method for controlling blood pressure of a device for controlling blood pressure.

[0021] Figure 2 It is a structural block diagram of a device for controlling blood pressure according to the present invention.

[0022] Figure 3 It is the logic block diagram for establishing and optimizing the second model. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] It should be noted here that in order to avoid obscuring the present invention due to unnecessary details, only structures and / or processing steps closely related to the scheme of the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0025] In addition, it should be noted that the terms "comprises", "includes" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or apparatus that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or apparatus.

[0026] Pulse Wave Transit Time (PWTT) is the time it takes for a blood pressure wave to travel along the blood vessel wall. This time is composed of the time from the beginning of the heart contraction to the opening of the aortic valve and then to the pulsation of blood in the aorta, and the time it takes to be transmitted through the blood vessels to the peripheral parts. The PWTT parameter can be obtained from the ECG and pulse wave at the wrist. Currently, a large number of clinical trials have shown that the pulse wave transmission time is negatively correlated with blood pressure. When the blood pressure is relatively high, the arterial wall becomes tense and the transmission speed of the pulse wave becomes faster. When the blood pressure is relatively low, the arterial wall becomes relaxed and the transmission speed of the pulse wave slows down. Therefore, the relationship between the pulse wave transmission time and blood pressure can be used to monitor changes in blood pressure and blood pressure values ​​within a certain error range. However, the pulse wave transmission time itself has high requirements for the measurement environment, and there may be a situation where no data can be monitored, and it is impossible to monitor the user's blood pressure in real time in a complex environment.

[0027] See also Figure 1 to Figure 2 As shown, the present invention provides a device 100 for controlling blood pressure, including a wearable structure and a pulse wave sensor module 10, a health parameter acquisition module 20, an electrical stimulation module 40 and a control module 30 arranged on the wearable structure. The pulse wave sensor module 10 is used to collect the user's pulse wave signal in real time and transmit the pulse wave signal to the control module 30. The health parameter acquisition module 20 is used to collect the user's health parameters in real time and transmit the health parameters to the control module 30. The electrical stimulation module 40 is used to apply electrical stimulation to the user's limbs. The control module 30 receives and analyzes the pulse wave signal and the health parameters, and controls the electrical stimulation module 40 to start or stop through the above-mentioned method for controlling blood pressure. The device can monitor the changes in blood pressure in real time under complex environments, and when abnormal blood pressure is detected, timely intervene in treatment to prevent it from deteriorating, and stop treatment in time after the blood pressure is detected to be normal. The steps of the control module 30 controlling the electrical stimulation module 40 to start or stop based on the pulse wave signal and the health parameters include:

[0028] S1: Establish or retrieve the first model of pulse wave transmission time and blood pressure;

[0029] S2: Obtain the user's blood pressure data and health parameter information, and establish a second model of the user's health parameter information and blood pressure;

[0030] S3: continuously monitoring the pulse wave transmission time of the user. If the pulse wave transmission time of the user is collected within T1, the process proceeds to step S4; if the pulse wave transmission time of the user is not collected within T1, the process proceeds to step S5;

[0031] S4: converting the pulse wave transmission time into blood pressure data in real time through the first model, and outputting the blood pressure data to step S6;

[0032] S5: continuously monitor the user's health parameter information, and convert the health parameter information into blood pressure data in real time through the second model; output the blood pressure data to step S6;

[0033] S6: Analyze the output blood pressure data and determine whether the blood pressure data is within a safe range. If so, return to step S3; if not, perform electrical stimulation therapy on the user.

[0034] When the device 100 cannot detect the user's pulse wave signal, it can use the user's health information parameters to monitor blood pressure in real time, thereby ensuring that blood pressure data can be stably obtained in complex environments, and timely intervene in the user's blood pressure abnormalities to prevent them from worsening, forming a closed loop of blood pressure monitoring and blood pressure intervention.

[0035] In order to clearly describe the device for controlling blood pressure of the present invention, the following description will be described in detail using the device 100 for controlling blood pressure as a wearable watch as an example, but the invention should not be limited thereto.

[0036] In one embodiment, a wearable watch includes a wristband and a housing coupled to the wristband. A pulse wave sensing module 10, a health parameter acquisition module 20, an electrical stimulation module 40 and a control module 30 are built into the housing, wherein the pulse wave sensing module 10, the health parameter acquisition module 20 and the electrical stimulation module 40 are arranged on the inner surface of the housing contacting the user's body surface. The pulse wave sensing module 10 is used to collect the user's pulse wave signal in real time, and transmit the pulse wave signal to the control module 30. The control module 30 calculates the blood pressure data through the first model and monitors the user's blood pressure changes in real time. The health parameter acquisition module 20 is used to collect the user's health parameters in real time, and transmit the health parameters to the control module 30. When the user's pulse wave signal cannot be monitored, the control module 30 calculates the blood pressure data through the second model using the above health parameters to continuously and stably monitor the user's blood pressure changes. The electrical stimulation module 40 is used to apply electrical stimulation to the user's limbs. When the user's blood pressure is abnormal, the control module 30 controls the electrical stimulation module 40 to start, so as to perform intervention treatment in time. When the user's blood pressure is detected to be back to normal, the control module 30 controls the electrical stimulation module 40 to stop. Of course, in other embodiments, the pulse wave sensing module 10, the health parameter acquisition module 20, the electrical stimulation module 40 and the control module 30 can also be arranged on the wristband, or partially arranged on the wristband and partially arranged on the housing, and the present invention is not limited to this.

[0037] Specifically, the pulse wave sensing module 10 collects the user's radial artery main peak value (H1), radial artery main peak time (T1), brachial artery main peak value (H2) and brachial artery main peak time (T2), and takes the radial artery main peak value (H1) and the brachial artery main peak value (H2) as reference points to compare the time difference between the corresponding radial artery main peak time (T1) and the brachial artery main peak time (T2), and the difference is taken as the pulse wave transmission time (PWTT), PWTT = , the first model matrix is: , the calculated value of diastolic pressure P11= *PWTT3+ *PWTT2+ *PWTT+ , the calculated value of systolic blood pressure P12= *PWTT3+ *PWTT2+ *PWTT+ Among them, A11~A14 and A21~A24 in the first model are coefficient parameters calculated by the neural network algorithm and the polynomial fitting algorithm.

[0038] The first model can be pre-stored in the storage module 70 of the watch. When monitoring blood pressure, the control module 30 retrieves the first model from the storage module 70, and then converts the pulse wave transmission time of the user monitored in real time by the pulse wave sensor module 10 into blood pressure data in real time through the first model, thereby achieving the purpose of real-time monitoring of the user's blood pressure. Alternatively, the first model can be established by itself. The user measures the user's accurate real-time blood pressure data through a separate dynamic blood pressure monitoring device (dynamic blood pressure monitoring device is independent of the wearable device), and then inputs the blood pressure data into the watch. At the same time, the pulse wave sensor module 10 in the watch monitors the pulse wave transmission time. The control module 30 puts the above data in the same coordinate system and establishes a first model between the pulse wave transmission time and blood pressure through mathematical modeling methods such as polynomial fitting method. Afterwards, the pulse wave transmission time of the user monitored in real time by the pulse wave sensor module 10 in the watch can be converted into blood pressure data in real time through the first model.

[0039] The pulse wave transmission time (PWTT) itself has relatively high requirements for the measurement environment, and there may be situations where no data can be monitored. In this case, the user's blood pressure cannot be monitored in time, and it is even more impossible to intervene in abnormal blood pressure in time. In this case, the present invention forms a second model by associating the user's health parameters with the blood pressure data, and derives the user's real-time blood pressure through the second model, which is a supplementary method for measuring blood pressure by the pulse wave transmission time (PWTT), ensuring that blood pressure information (blood pressure change trend) can be stably obtained in complex environments, ensuring that timely intervention can be made in abnormal blood pressure of the user to prevent it from deteriorating.

[0040] Since the second model is associated with the user's health parameter information, it is not a standard model and needs to be established when the wearable device is used for the first time. Therefore, the second model is also an independent and valid model for each individual user.

[0041] See also Figure 3 As shown, the health parameter information includes the user's constant parameter and at least one time-varying parameter collected by the health parameter collection module 20. There are m constant parameters, represented by L1~Lm, and n time-varying parameters, represented by S1(t)~Sn(t), where m and n are integers, and m≥1, n≥1. The blood pressure data converted according to the second model is

[0042] ,

[0043] That is, the calculated value of diastolic pressure P 21 =L1G 11 + +L M G 1M +S1(t)G1(M+1) + +S N (t)G 1(M+N) , the calculated value of systolic blood pressure P 22 =L1G 21 + +L M G 2M +S1(t)G 2(M+1) + +S N (t)G 2(M+N) .in, is the second model matrix, G 11 ~G 1（M+N） and G 21 ~G 2（M+N） are the coefficient parameters calculated according to the neural network algorithm.

[0044] The control module 30 will compare and analyze the data of the dynamic blood pressure monitoring device within a period of time with the data of the corresponding health parameter acquisition module 20, and finally establish a model between the user's health information parameter changes and the user's blood pressure trend, that is, the second model.

[0045] In one embodiment, when the user gets the watch, the user's personal constant parameters are first input into the user information of the watch. For example, the constant parameters are the user's age, gender, height, weight, etc. Then the user's accurate real-time blood pressure data is measured by the dynamic blood pressure monitoring device, and then the blood pressure data is input into the watch. At the same time, the health parameter acquisition module 20 in the watch collects the user's time-varying parameters at the same time. For example, the control module 30 will select a period of time, such as the blood pressure data monitored by the dynamic blood pressure monitoring device from 5:10:00:00 to 5:20:00:00 and the relevant health information parameters collected by the health parameter acquisition module 20. The control module 30 uses the neural network algorithm to train the coefficient parameters of the second model based on the above data, and establishes a second model between the health parameter information and the blood pressure. After the second model is established, if the pulse wave sensing module 10 does not collect the pulse wave transmission time within the T1 time, the user's time-varying parameters monitored in real time by the health parameter acquisition module 20 in the watch can be converted into blood pressure data in real time through the second model to continuously and stably monitor the blood pressure. Preferably, the T1 time can be 10 seconds, that is, when the pulse wave sensor module 10 collects the measurement value within 10 seconds, steps S4 and S6 are entered. If the pulse wave sensor module 10 collects the measurement value within 10 seconds, step S5 will be activated, and step S6 will be entered from S5.

[0046] In another embodiment, the blood pressure data obtained by the pulse wave sensing module 10 through the first model and the health parameter acquisition module 20 can collect the user's time-varying parameters and the input user's constant parameters at the same time, and establish a second model between the health parameter information and blood pressure through a neural network algorithm.

[0047] In some embodiments, the health parameter acquisition module 20 includes any one of a heart rate sensor or a blood oxygen sensor. In this case, the time-varying parameter may be heart rate or blood oxygen. In other embodiments, the health parameter acquisition module 20 may also include a combination of a heart rate sensor, a blood oxygen sensor, a temperature sensor, a motion sensor, a blood fat sensor, and a skin resistance sensor. In this case, the time-varying parameter may be a combination of heart rate, blood oxygen, temperature, motion, blood fat, and skin resistance.

[0048] After the specific time-varying parameters are selected, the control module 30 constructs a second model matrix according to the number and type of the time-varying parameters and the constant parameters. When calculating the blood pressure change, the data of the selected time-varying parameters need to be input simultaneously.

[0049] Furthermore, the coefficient parameters in the second model are automatically optimized after reaching a predetermined time t1 and / or a predetermined condition, or are passively optimized after being triggered by the user. That is, the user can trigger the upgrade module on the watch as needed to optimize the coefficient parameters in the second model matrix. Alternatively, when a predetermined time t1 and / or a predetermined condition is set, when the second model in the watch reaches the predetermined time t1 and / or the predetermined condition, the coefficient parameters in the second model can be automatically optimized.

[0050] The method for optimizing the coefficient parameters includes training a network using the blood pressure data obtained by the first model and the blood pressure data obtained by the second model to optimize the coefficient parameters of the second model. Alternatively, the blood pressure data directly obtained by the dynamic blood pressure monitoring device and the blood pressure data obtained by the second model are used to train the network to optimize the coefficient parameters of the second model. Alternatively, the above two optimization methods can be combined to optimize the coefficient parameters of the second model.

[0051] Furthermore, the watch also includes a storage module 70, which is configured to store constant parameters of multiple users and second models related to multiple users. When multiple users use the watch in turn, the constant parameters of the user and the second model related to the constant parameters can be retrieved from the user information, so that the second model does not need to be repeatedly established.

[0052] Optionally, the device further comprises a communication module 60, which sends the second model to the server to implement backup of the second model. When the user changes the wearable device, the second model can be downloaded from the server to avoid repeatedly establishing the second model.

[0053] When the wearable device detects that the user's blood pressure is abnormal, for example, the current blood pressure parameter exceeds 20% of the average blood pressure over the past three days, the control module 30 controls the electrical stimulation module 40 to perform electrical stimulation treatment on the user, thereby timely intervening in the abnormal blood pressure. Preferably, when the wearable device is a watch, the median nerve of the user is electrically stimulated through the contact surface of the watch and the user, which can be simply understood as applying current, voltage, and frequency stimulation to an "acupoint".

[0054] Furthermore, the gear of the electrical stimulation treatment is provided with multiple levels according to the abnormal degree of the blood pressure data, and the electrical stimulation intensity and / or the electrical stimulation frequency and / or the electrical stimulation time and / or the number of repeated electrical stimulations of the multiple levels are different. Specifically, based on the accurate real-time blood pressure parameters of the user measured by the dynamic blood pressure monitoring device, and according to the preset algorithm, the blood pressure parameters or blood pressure change trends of the user are divided into multiple blood pressure abnormality levels. And personalized median nerve electrical stimulation parameters are assigned to each of the divided blood pressure abnormality levels. For example, the blood pressure range of a normal and healthy adult should be 90-130 mmHg systolic pressure. The accurate real-time blood pressure parameters of the user are analyzed by the preset algorithm, and the ideal systolic pressure of the user is 100-135 mmHg. If the systolic pressure reaches 135-145 mmHg, it is a first-level blood pressure abnormality, and the level of electrical stimulation of the median nerve by the electrical stimulation module 40 is A. If the systolic pressure reaches 145-153 mmHg, it is a second-level blood pressure abnormality, and the level of electrical stimulation of the median nerve by the electrical stimulation module 40 is B. If the systolic blood pressure reaches 154-163 mmHg, it is a third-level blood pressure abnormality. At this time, the level of electrical stimulation performed by the electrical stimulation module 40 on the median nerve is C.

[0055] Furthermore, the user's history of hypertension can also be input into the user information of the watch. When the user is diagnosed with hypertension, the control unit will determine the stimulation level of electrical stimulation that should be given to the user based on the blood pressure range that exceeds the normal range according to the severity of the hypertension, the duration of hypertension, the medication taken, etc.

[0056] Furthermore, the gear of the electrical stimulation therapy is optimized according to the user's usage and / or after reaching a predetermined time t2 to improve the effect of the electrical stimulation therapy. For example, when the user feedback intensity is not enough or a certain time has passed since the last optimization, the electrical stimulation gear parameters will be reset.

[0057] Further, the device also includes a feedback module 50, which is connected to the pulse wave sensor module 10, the health parameter acquisition module 20 and the control module 30 in communication to monitor the user's blood pressure data in real time, and feed back the blood pressure data to the control module 30, and the control module 30 automatically adjusts the electrical stimulation intensity and / or the electrical stimulation frequency and / or the electrical stimulation time and / or the number of repetitions of the electrical stimulation module 40 according to the feedback information of the feedback module 50. For example, when the watch is performing B-level electrical stimulation, the blood pressure data of the user is re-measured through the pulse wave sensor module 10 or the health parameter acquisition module 20, and when the blood pressure is monitored to be reduced to the first level of abnormal blood pressure interval, the information is fed back to the control module 30 through the feedback module 50, and the control module 30 thereby reduces the level of the electrical stimulation module 40 from B level to A level. When the blood pressure data of the user is re-measured through the pulse wave sensor module 10 or the health parameter acquisition module 20 sensor module, when it is found that the blood pressure has not changed, the information is fed back to the control module 30 through the feedback module 50, and the control module 30 thereby increases the level of the electrical stimulation module 40 from B level to C level. Alternatively, the control module 30 can adjust at least one of the intensity, frequency, time and number of repetitions in level B to suit the user's body. Through the feedback module 50, blood pressure data can be fed back to the control module 30 in a timely manner according to the user's own situation, so as to make timely electrical stimulation adjustments.

[0058] Optionally, the gear, intensity, frequency, time and number of repetitions of the electrical stimulation therapy can also be adjusted manually. For example, a watch is provided with several buttons, through which the electrical stimulation therapy scheme can be manually adjusted. The present invention is not limited to this.

[0059] To summarize, the method and device for controlling blood pressure of the present invention can monitor blood pressure in real time using the user's health information parameters when the user's pulse wave signal cannot be monitored, thereby ensuring that blood pressure data can be stably obtained in a complex environment, and timely intervening in the user's abnormal blood pressure to prevent it from deteriorating, thereby forming a closed loop of blood pressure monitoring and blood pressure intervention.

[0060] The above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A device for controlling blood pressure, characterized in that: It includes a wearable structure and a pulse wave sensing module, a health parameter acquisition module, an electrical stimulation module and a control module arranged on the wearable structure; The pulse wave sensing module is used to collect the user's pulse wave signal in real time and transmit the pulse wave signal to the control module; The health parameter acquisition module is used to acquire the user's health parameters in real time and transmit the health parameters to the control module; The electrical stimulation module is used to apply electrical stimulation to the user's limbs; The control module receives and analyzes the pulse wave signal and the health parameter, and controls the electrical stimulation module to start or stop based on the pulse wave signal and the health parameter; The step of the control module controlling the start or stop of the electrical stimulation module based on the pulse wave signal and the health parameter comprises: S1: Establish or retrieve the first model of pulse wave transmission time and blood pressure; S2: Obtain the user's blood pressure data and health parameter information, and establish a second model of the user's health parameter information and blood pressure; S3: continuously monitoring the pulse wave transmission time of the user. If the pulse wave transmission time of the user is collected within T1, the process proceeds to step S4; if the pulse wave transmission time of the user is not collected within T1, the process proceeds to step S5; S4: converting the pulse wave transmission time into blood pressure data in real time through the first model, and outputting the blood pressure data to step S6; S5: continuously monitor the user's health parameter information, and convert the health parameter information into blood pressure data in real time through the second model; output the blood pressure data to step S6; S6: Analyze the output blood pressure data and determine whether the blood pressure data is within a safe range. If so, return to step S3; if not, perform electrical stimulation treatment on the user.

2. The device for controlling blood pressure according to claim 1, characterized in that: The health parameter information includes a constant parameter of the user and at least one time-varying parameter collected by a health parameter collection module.

3. The device for controlling blood pressure according to claim 2, characterized in that: The constant parameters are set to m, ranging from L1 to L m Indicates that there are n time-varying parameters, with S1(t)~S n (t) represents, where m and n are integers, and m≥1, n≥1. The blood pressure data converted according to the second model is , where P 21 is the calculated value of diastolic pressure, P 22 is the calculated value of systolic blood pressure, is the second model matrix, G 11 ~G 1（M+N） and G 21 ~G 2（M+N） are the coefficient parameters calculated according to the neural network algorithm.

4. The device for controlling blood pressure according to claim 3, characterized in that: The coefficient parameters in the second model are automatically optimized after reaching a predetermined time t1 and / or a predetermined condition, or are passively optimized after being triggered by a user.

5. The device for controlling blood pressure according to claim 4, characterized in that: The method for optimizing coefficient parameters includes training a network using blood pressure data obtained by the first model and blood pressure data obtained by the second model to optimize the coefficient parameters of the second model; and / or training a network using directly acquired blood pressure data and blood pressure data obtained by the second model to optimize the coefficient parameters of the second model.

6. The device for controlling blood pressure according to claim 1, characterized in that: The electrical stimulation therapy has multiple levels according to the abnormality of the blood pressure data. The electrical stimulation intensity and / or the electrical stimulation frequency and / or the electrical stimulation time and / or the number of repeated electrical stimulations of the multiple levels are different.

7. The device for controlling blood pressure according to claim 6, characterized in that: The gear of the electrical stimulation therapy is optimized according to the user's usage and / or after reaching a predetermined time t2.

8. The device for controlling blood pressure according to claim 1, characterized in that: The health parameter acquisition module includes one of a heart rate sensor or a blood oxygen sensor; or, the health parameter acquisition module includes a combination of a heart rate sensor, a blood oxygen sensor, a temperature sensor, a motion sensor, a blood lipid sensor and a skin resistance sensor.

9. The device for controlling blood pressure according to claim 1, characterized in that: The device also includes a feedback module, which is communicatively connected with the pulse wave sensing module, the health parameter acquisition module and the control module to monitor the user's blood pressure changes in real time and feed back the blood pressure changes to the control module. The control module adjusts the electrical stimulation intensity and / or electrical stimulation frequency and / or electrical stimulation time and / or number of repetitions of the electrical stimulation module according to the feedback information of the feedback module.

10. The device for controlling blood pressure according to claim 1, characterized in that: The device also includes a communication module, which sends the second model to a server to implement backup of the second model.

11. The device for controlling blood pressure according to claim 1, characterized in that: The device also includes a storage module configured to store constant parameters of multiple users and a second model corresponding to each user.

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