Data correction method, data correction device, electronic device and readable storage medium

Abstract

The present application discloses a data correction method, a data correction device, an electronic device and a readable storage medium, which belongs to the technical field of electronic devices. The data correction method comprises: when a user wears the electronic device and the user is in a first posture, obtaining a first posture parameter of the first posture and a first blood pressure value of the user; when the user wears the electronic device and the user is in a second posture, obtaining a second posture parameter of the second posture and a second blood pressure value of the user; determining a hydrostatic pressure difference according to the first posture parameter and the second posture parameter; determining a correction matrix according to the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, wherein the correction matrix is ​​used to correct a target algorithm, and the target algorithm is used to measure blood pressure.

Description

Technical Field

[0001] The present application belongs to the technical field of electronic equipment, and specifically relates to a data correction method, a data correction device, an electronic device and a readable storage medium. Background Art

[0002] At present, blood pressure measurement can be achieved using wearable devices based on photoelectric technology. The size of the measuring device using photoelectric technology is greatly reduced, making non-contact, all-weather monitoring possible.

[0003] However, the use of photoelectric technology in related technologies requires converting many photoelectric characteristics related to blood pressure (for example, pulse transit time (PTT), pulse arrival time (PAT), etc.) in time and space into blood pressure values. This process has many individual differences (for example, the height, shortness, fatness, and thinness of the human body) and limitations of theoretical estimation algorithms, which will lead to inaccurate blood pressure measurement. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a data correction method, a data correction device, an electronic device and a readable storage medium, which can solve the problem of inaccurate blood pressure value measurement in the related art.

[0005] In a first aspect, an embodiment of the present application provides a data correction method, the data correction method comprising:

[0006] When a user wears the electronic device and the user is in a first posture, obtaining a first posture parameter of the first posture and a first blood pressure value of the user;

[0007] When the user wears the electronic device and the user is in a second posture, obtaining a second posture parameter of the second posture and a second blood pressure value of the user;

[0008] determining a hydrostatic pressure difference based on the first attitude parameter and the second attitude parameter;

[0009] A correction matrix is ​​determined according to the hydrostatic pressure difference, the first blood pressure value, and the second blood pressure value, wherein the correction matrix is ​​used to correct a target algorithm, and the target algorithm is used to measure blood pressure.

[0010] In a second aspect, an embodiment of the present application provides a data correction device, the data correction device comprising:

[0011] A first acquisition module, configured to acquire, when a user wears the electronic device and the user is in a first posture, a first posture parameter of the first posture and a first blood pressure value of the user;

[0012] A second acquisition module, used for acquiring a second posture parameter of the second posture and a second blood pressure value of the user when the user wears the electronic device and the user is in a second posture;

[0013] A first determination module, configured to determine a hydrostatic pressure difference according to a first posture parameter and a second posture parameter;

[0014] The second determination module is used to determine a correction matrix according to the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, wherein the correction matrix is ​​used to correct the target algorithm, and the target algorithm is used to measure blood pressure.

[0015] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the method of the first aspect are implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method of the first aspect are implemented.

[0017] In a fifth aspect, an embodiment of the present application provides a chip, the chip including a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the method of the first aspect.

[0018] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method of the first aspect.

[0019] In an embodiment of the present application, when a user wears an electronic device, the electronic device measures the blood pressure of the user in different postures, thereby obtaining blood pressure values ​​in different postures, and during the measurement process, the posture parameters of the user in different postures are accurately obtained through the accelerometer and gyroscope of the electronic device. Specifically, when the user is in a first posture, the first posture parameter of the first posture and the first blood pressure value of the user are obtained, and when the user is in a second posture, the second posture parameter of the second posture and the second blood pressure value of the user are obtained. Then, based on the first posture parameter and the second posture parameter, the hydrostatic pressure difference is determined. Finally, based on the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, a correction matrix for correcting a target algorithm is determined, wherein the target algorithm is used to measure blood pressure, and wherein the first blood pressure value and the second blood pressure value are obtained by the electronic device through the target algorithm. In the embodiment of the present application, since the hydrostatic pressure difference and the actual blood pressure value are affected by individual differences and theoretical limitations, and the absolute value of the hydrostatic pressure difference is known, the known hydrostatic pressure difference is used to infer the influence of individual differences and theoretical limitations in the implementation of the present application, and a correction matrix for correcting the target algorithm is obtained, so that the target algorithm for blood pressure measurement can be calibrated to avoid measurement errors caused by the passage of time or individual differences, thereby improving the accuracy of blood pressure measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is a flow chart of a data correction method according to an embodiment of the present application;

[0021] Figure 2 It is one of the schematic diagrams of human blood pressure measurement in the embodiment of the present application;

[0022] Figure 3 This is the second schematic diagram of human blood pressure measurement in the embodiment of the present application;

[0023] Figure 4 is a flow chart of a blood pressure measurement method according to an embodiment of the present application;

[0024] Figure 5 is a schematic block diagram of a data correction device according to an embodiment of the present application;

[0025] Figure 6 It is one of the schematic block diagrams of the electronic device according to the embodiment of the present application;

[0026] Figure 7 This is the second schematic block diagram of the electronic device according to the embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0028] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0029] The data correction method, data correction device, electronic device and readable storage medium provided in the embodiments of the present application are described in detail below with reference to the accompanying drawings through specific embodiments and their application scenarios.

[0030] The present application embodiment provides a data correction method, such as Figure 1 As shown, the data correction method includes:

[0031] Step 102, when the user wears the electronic device and the user is in a first posture, obtaining a first posture parameter of the first posture and a first blood pressure value of the user;

[0032] Step 104, when the user wears the electronic device and the user is in a second posture, obtaining a second posture parameter of the second posture and a second blood pressure value of the user;

[0033] Step 106, determining the hydrostatic pressure difference according to the first posture parameter and the second posture parameter;

[0034] Step 108, determining a correction matrix according to the hydrostatic pressure difference, the first blood pressure value, and the second blood pressure value, wherein the correction matrix is ​​used to correct the target algorithm, and the target algorithm is used to measure the blood pressure.

[0035] In this embodiment, when the user wears the electronic device, the electronic device measures the blood pressure of the user in different postures, thereby obtaining the blood pressure values ​​in different postures, and during the measurement process, the posture parameters of the user in different postures (such as the measurement height of the user's blood pressure measurement position) are accurately obtained through the accelerometer and gyroscope of the electronic device. Specifically, when the user is in a first posture, the first posture parameter of the first posture and the first blood pressure value of the user are obtained, and when the user is in a second posture, the second posture parameter of the second posture and the second blood pressure value of the user are obtained.

[0036] Then, the hydrostatic pressure difference is determined according to the first posture parameter and the second posture parameter. For example, the actual blood pressure value P in a certain posture is P = P b +ρgh, where P b is the blood pressure value of this posture (that is, the blood pressure value measured by the electronic device in this posture), ρ is the water density, g is the gravity coefficient, and h is the measurement height.

[0037] It should be noted that the measured height h can be the relative height between the measured position and the heart position, or the absolute height of the measured position on the human body. In addition, when the user is in a non-inertial state, the gravity coefficient g needs to be corrected according to the component of the acceleration of the measured position of the user in the gravity direction to ensure the accuracy of the final hydrostatic pressure difference.

[0038] like Figure 2 and Figure 3 As shown, the actual blood pressure value of the user in two different postures is P1=P b +ρgh1, actual blood pressure value P2=P b +ρgh2. It is assumed here that in a short period of time, the measured blood pressure value P b There will be no drastic changes or the observed changes can be eliminated by multiple averaging. Therefore, the theoretical blood pressure error in two different postures is the hydrostatic pressure difference, that is, pgh1-pgh2.

[0039] Finally, a correction matrix for correcting a target algorithm is determined based on the hydrostatic pressure difference, the first blood pressure value, and the second blood pressure value, wherein the target algorithm is used to measure blood pressure, and wherein the first blood pressure value and the second blood pressure value are obtained by the electronic device through the target algorithm.

[0040] In the embodiment of the present application, since the hydrostatic pressure difference and the actual blood pressure value are affected by individual differences and theoretical limitations, and the absolute value of the hydrostatic pressure difference is known, the known hydrostatic pressure difference is used to infer the influence of individual differences and theoretical limitations in the implementation of the present application, and a correction matrix for correcting the target algorithm is obtained, so that the target algorithm for blood pressure measurement can be calibrated to avoid measurement errors caused by the passage of time or individual differences, thereby improving the accuracy of blood pressure measurement.

[0041] Furthermore, compared to the existing method that requires the use of a blood pressure monitor for calibration, the embodiment of the present application does not require the human body to maintain a specific posture when measuring blood pressure. Blood pressure measurement is used for subsequent calibration without any intervention from the user, thereby improving the practicality of electronic equipment in measuring blood pressure.

[0042] It should be noted that the embodiments of the present application do not consider specific blood pressure measurement methods. Common methods of combining electrocardiogram (ECG) with photoplethysmograph (PPG), ballisto cardiogram (BCG) with PPG, or PPG morphology blood pressure measurement are all applicable.

[0043] In one embodiment of the present application, obtaining a first blood pressure value of a user includes: obtaining a first pulse signal of the user; and obtaining a first blood pressure value based on the first pulse signal and a target algorithm; obtaining a second blood pressure value of the user includes: obtaining a second pulse signal of the user; and obtaining a second blood pressure value based on the second pulse signal and a target algorithm.

[0044] In this embodiment, the electronic device can obtain the user's blood pressure value based on photoelectric technology, using pulse signals (eg, PTT, PAT and other features) and a target algorithm.

[0045] In the embodiments of the present application, on the one hand, blood pressure measurement through photoelectric technology can greatly reduce the size of electronic devices with blood pressure measurement function, thereby realizing continuous monitoring and contactless all-weather monitoring; on the other hand, the target algorithm can be calibrated during the blood pressure measurement process without any intervention from the user.

[0046] In one embodiment of the present application, a correction matrix is ​​determined based on the hydrostatic pressure difference, the first blood pressure value, and the second blood pressure value, including: obtaining the difference between the first blood pressure value and the second blood pressure value; generating an error matrix based on the hydrostatic pressure difference and the difference; and determining a correction matrix based on the error matrix, wherein the correction matrix is ​​an inverse matrix of the error matrix.

[0047] In this embodiment, the difference between the first blood pressure value and the second blood pressure value, that is, the measurement error, is obtained, and then the error matrix is ​​calculated based on the difference and the hydrostatic pressure difference. The error matrix is ​​the error caused by individual differences and theoretical limitations. The inverse matrix of the error matrix (that is, the correction matrix) is calculated, and finally the target algorithm is compensated based on the inverse matrix.

[0048] In the above manner, a correction matrix is ​​obtained based on the hydrostatic pressure difference and the measurement error, which can realize the calibration of the target algorithm for blood pressure measurement and improve the accuracy of blood pressure measurement.

[0049] In one embodiment of the present application, generating an error matrix according to the hydrostatic pressure difference and the difference includes: generating an error matrix according to the hydrostatic pressure difference, the difference and a first formula; wherein the first formula is A=M×T -1 , A is the error matrix, T is the hydrostatic pressure difference, and M is the difference.

[0050] In this embodiment, it is assumed that the measurement error (i.e., the difference between the first blood pressure value and the second blood pressure value) is F(x)=A×G(x)+e, where A is a multi-observation error matrix of modeling error or individual difference, e is observation noise, F(x) is an error observation, and G(x) is an error-free observation. Assuming e is neutral noise, the error matrix A can be obtained by continuously obtaining F1-F2, F2-F3, F3-F4, etc. and obtaining its optimal estimate through the least squares method.

[0051] That is, F1-F2=A×(G1-G2), F2-F3=A×(G2-G3), F3-F4=A×(G3-G4)... Among them, F1-F2, F2-F3, F3-F4..., are the measurement errors of the blood pressure values ​​of N blood pressure measurements, and G1-G2, G2-G3, G3-G4..., are the hydrostatic pressure differences of N blood pressure measurements.

[0052] Let the new matrix generated by F1-F2, F2-F3, F3-F4, ... be M, and the new matrix generated by G1-G2, G2-G3, G3-G4, ... be T, then the measurement error M = A×T.

[0053] Furthermore, A = M × T -1 , thus obtaining the inverse matrix A of A -1 =(M×T -1 ) -1 , that is, the correction matrix, realizes the reverse deduction of the theoretical limit error. Finally, the measurement error F is calibrated, that is, the calibration of the target algorithm is realized, where the calibrated measurement error F c =(M×T -1 ) -1 F. In addition, it should be noted that, assuming that the error matrix A is nonlinear, linearization can be achieved through Taylor expansion.

[0054] The embodiment of the present application combines the characteristic that the absolute value of the hydrostatic pressure difference is known, and by comparing the difference in blood pressure values ​​obtained by continuous measurement in different postures, it is possible to reversely infer the impact of individual differences and theoretical limitations, and then calibrate the target algorithm for blood pressure measurement.

[0055] In one embodiment of the present application, the first posture includes N first sub-postures, and the second posture includes N second sub-postures, where N is a positive integer; obtaining the first posture parameter of the first posture and the first blood pressure value of the user includes: obtaining the N first sub-posture parameters corresponding to the N first sub-postures and the N first sub-blood pressure values ​​of the user; obtaining the second posture parameter of the second posture and the second blood pressure value of the user includes: obtaining the N second sub-posture parameters corresponding to the N second sub-postures and the N second sub-blood pressure values ​​of the user; determining the hydrostatic pressure difference according to the first posture parameter and the second posture parameter includes: determining the N sub-hydrostatic pressure differences according to the N first sub-posture parameters and the N second sub-posture parameters; determining the correction matrix according to the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, includes: when N is greater than or equal to a preset value, determining the correction matrix according to the N sub-hydrostatic pressure differences, the N first sub-blood pressure values, and the N second sub-blood pressure values.

[0056] In this embodiment, the first posture includes N first sub-postures, and the second posture includes N second sub-postures. When obtaining posture parameters and blood pressure values, specifically, N first sub-posture parameters corresponding to the N first sub-postures and N first sub-blood pressure values ​​of the user are obtained, and N second sub-posture parameters corresponding to the N second sub-postures and N second sub-blood pressure values ​​of the user are obtained. Then, according to the N first sub-posture parameters and the N second sub-posture parameters, N sub-hydrostatic pressure differences are determined respectively. When N is greater than or equal to the preset value, it indicates that there are enough calibration data, and then the correction matrix is ​​calculated according to the N sub-hydrostatic pressure differences, the N first sub-blood pressure values, and the N second sub-blood pressure values.

[0057] Through the above method, after collecting enough calibration data, the correction matrix is ​​calculated, so that the correction matrix is ​​more accurate, and the accuracy of the final calibrated target algorithm is improved.

[0058] In addition, when N is less than a preset value, it indicates that the collected calibration data is not sufficient, and a prompt message is output, which is used to prompt the user to be in the third posture, thereby reminding the user to change the posture in time.

[0059] The present application embodiment provides a blood pressure measurement method applied to a wearable device, such as Figure 4 As shown, the blood pressure measurement method includes:

[0060] Step 402, measuring blood pressure using a wearable device to obtain a blood pressure value;

[0061] Step 404, while measuring, determine the posture of the measurement position through an accelerometer or other device of the wearable device, and calculate the height and instantaneous acceleration of the measurement position;

[0062] Step 406, calculating the difference between the two measured blood pressure values, and calculating the hydrostatic pressure difference using the height difference between the two measured positions and the instantaneous acceleration;

[0063] Step 408, recording the difference between the blood pressure values ​​and the hydrostatic pressure difference as calibration data;

[0064] Step 410, determining whether sufficient calibration data has been collected, if it is determined that sufficient calibration data has been collected, proceeding to step 412, otherwise returning to step 402;

[0065] Step 412, performing optimal estimation using the calibration data to generate an error matrix;

[0066] Step 414, inverting the error matrix to calibrate the original target algorithm for blood pressure measurement and generate a new target algorithm;

[0067] Step 416: The wearable device measures blood pressure and obtains the blood pressure value using the new target algorithm.

[0068] In this embodiment, the process of correcting the blood pressure value does not require any intervention from the user and is fully automated. Moreover, the hydrostatic pressure difference of the accelerated correction can correct each measurement result, so that the user does not need to place the arm on the chest to measure the blood pressure to improve the accuracy, which facilitates the user's blood pressure measurement operation.

[0069] The data correction method provided in the embodiment of the present application can be executed by a data correction device. In the embodiment of the present application, the data correction device provided in the embodiment of the present application is described by taking the data correction method executed by the data correction device as an example.

[0070] The present application embodiment provides a data correction device, such as Figure 5 As shown, the data correction device 500 includes:

[0071] A first acquisition module 502, configured to acquire a first posture parameter of the first posture and a first blood pressure value of the user when the user wears the electronic device and the user is in a first posture;

[0072] A second acquisition module 504, configured to acquire a second posture parameter of the second posture and a second blood pressure value of the user when the user wears the electronic device and the user is in a second posture;

[0073] A first determination module 506, configured to determine a hydrostatic pressure difference according to a first posture parameter and a second posture parameter;

[0074] The second determination module 508 is used to determine a correction matrix according to the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, wherein the correction matrix is ​​used to correct the target algorithm, and the target algorithm is used to measure blood pressure.

[0075] In this embodiment, when the user wears the electronic device, the electronic device measures the blood pressure of the user in different postures, thereby obtaining the blood pressure values ​​in different postures, and during the measurement process, the posture parameters of the user in different postures are accurately obtained through the accelerometer and gyroscope of the electronic device. Specifically, when the user is in a first posture, the first posture parameter of the first posture and the first blood pressure value of the user are obtained, and when the user is in a second posture, the second posture parameter of the second posture and the second blood pressure value of the user are obtained.

[0076] Then, the hydrostatic pressure difference is determined according to the first posture parameter and the second posture parameter. Finally, a correction matrix for correcting a target algorithm is determined according to the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, wherein the target algorithm is used to measure blood pressure, wherein the first blood pressure value and the second blood pressure value are obtained by the electronic device through the target algorithm.

[0077] In the embodiment of the present application, since the hydrostatic pressure difference and the actual blood pressure value are affected by individual differences and theoretical limitations, and the absolute value of the hydrostatic pressure difference is known, the known hydrostatic pressure difference is used to infer the influence of individual differences and theoretical limitations in the implementation of the present application, and a correction matrix for correcting the target algorithm is obtained, so that the target algorithm for blood pressure measurement can be calibrated to avoid measurement errors caused by the passage of time or individual differences, thereby improving the accuracy of blood pressure measurement.

[0078] In one embodiment of the present application, the first acquisition module is specifically used to acquire a first pulse signal of a user, and obtain a first blood pressure value based on the first pulse signal and a target algorithm; the second acquisition module is specifically used to acquire a second pulse signal of the user, and obtain a second blood pressure value based on the second pulse signal and a target algorithm.

[0079] In one embodiment of the present application, the data correction device 500 also includes: a third acquisition module, used to obtain the difference between the first blood pressure value and the second blood pressure value, and to generate an error matrix based on the hydrostatic pressure difference and the difference; a second determination module, specifically used to determine a correction matrix based on the error matrix, wherein the correction matrix is ​​an inverse matrix of the error matrix.

[0080] In one embodiment of the present application, the third acquisition module is specifically used to generate an error matrix according to the hydrostatic pressure difference, the difference and the first formula; wherein the first formula is A=M×T -1 , A is the error matrix, T is the hydrostatic pressure difference, and M is the difference.

[0081] In one embodiment of the present application, the first posture includes N first sub-postures, and the second posture includes N second sub-postures, where N is a positive integer; the first acquisition module is specifically used to obtain N first sub-posture parameters corresponding to the N first sub-postures and N first sub-blood pressure values ​​of the user; the second acquisition module is specifically used to obtain N second sub-posture parameters corresponding to the N second sub-postures and N second sub-blood pressure values ​​of the user; the first determination module is specifically used to determine N sub-hydrostatic pressure differences based on the N first sub-posture parameters and the N second sub-posture parameters; the second determination module is specifically used to determine the correction matrix based on the N sub-hydrostatic pressure differences, the N first sub-blood pressure values, and the N second sub-blood pressure values ​​when N is greater than or equal to a preset value.

[0082] The data correction device 500 in the embodiment of the present application can be an electronic device, or a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or other devices other than a terminal. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), an augmented reality (augmented reality, AR) / virtual reality (virtual reality, VR) device, a robot, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and can also be a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0083] The data correction device 500 in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0084] The data correction device 500 provided in the embodiment of the present application can achieve Figure 1 To avoid repetition, the various processes implemented in the data correction method embodiment are not described here.

[0085] Alternatively, if Figure 6As shown, an embodiment of the present application also provides an electronic device 600, including a processor 602 and a memory 604, wherein the memory 604 stores programs or instructions that can be executed on the processor 602, and when the program or instructions are executed by the processor 602, the various steps of the above-mentioned data correction method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, they are not described here.

[0086] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0087] Figure 7 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of the present application.

[0088] The electronic device 700 includes but is not limited to components such as a radio frequency unit 702 , a network module 704 , an audio output unit 706 , an input unit 708 , a sensor 710 , a display unit 712 , a user input unit 714 , an interface unit 716 , a memory 718 , and a processor 720 .

[0089] Those skilled in the art will appreciate that the electronic device 700 may also include a power source (such as a battery) for supplying power to each component, and the power source may be logically connected to the processor 720 through a power management system, thereby implementing functions such as managing charging, discharging, and power consumption management through the power management system. Figure 7 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be described in detail here.

[0090] Among them, the processor 720 is used to obtain a first posture parameter of a first posture and a first blood pressure value of the user when the user is wearing the electronic device and the user is in a first posture, and to obtain a second posture parameter of a second posture and a second blood pressure value of the user when the user is wearing the electronic device and the user is in a second posture, determine the hydrostatic pressure difference according to the first posture parameter and the second posture parameter, and determine a correction matrix according to the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, wherein the correction matrix is ​​used to correct the target algorithm, and the target algorithm is used to measure blood pressure.

[0091] In this embodiment, when the user wears the electronic device, the electronic device measures the blood pressure of the user in different postures, thereby obtaining the blood pressure values ​​in different postures, and during the measurement process, the posture parameters of the user in different postures are accurately obtained through the accelerometer and gyroscope of the electronic device. Specifically, when the user is in a first posture, the first posture parameter of the first posture and the first blood pressure value of the user are obtained, and when the user is in a second posture, the second posture parameter of the second posture and the second blood pressure value of the user are obtained.

[0092] Then, the hydrostatic pressure difference is determined according to the first posture parameter and the second posture parameter. Finally, a correction matrix for correcting a target algorithm is determined according to the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, wherein the target algorithm is used to measure blood pressure, wherein the first blood pressure value and the second blood pressure value are obtained by the electronic device through the target algorithm.

[0093] In the embodiment of the present application, since the hydrostatic pressure difference and the actual blood pressure value are affected by individual differences and theoretical limitations, and the absolute value of the hydrostatic pressure difference is known, the known hydrostatic pressure difference is used to infer the influence of individual differences and theoretical limitations in the implementation of the present application, and a correction matrix for correcting the target algorithm is obtained, so that the target algorithm for blood pressure measurement can be calibrated to avoid measurement errors caused by the passage of time or individual differences, thereby improving the accuracy of blood pressure measurement.

[0094] In one embodiment of the present application, the processor 720 is specifically used to obtain a first pulse signal of the user, and obtain a first blood pressure value based on the first pulse signal and a target algorithm, and to obtain a second pulse signal of the user, and obtain a second blood pressure value based on the second pulse signal and a target algorithm.

[0095] In one embodiment of the present application, the processor 720 is specifically used to obtain the difference between the first blood pressure value and the second blood pressure value, generate an error matrix based on the hydrostatic pressure difference and the difference, and determine a correction matrix based on the error matrix, wherein the correction matrix is ​​the inverse matrix of the error matrix.

[0096] In one embodiment of the present application, the processor 720 is specifically configured to generate an error matrix according to the hydrostatic pressure difference, the difference value and the first formula; wherein the first formula is A=M×T -1 , A is the error matrix, T is the hydrostatic pressure difference, and M is the difference.

[0097] In one embodiment of the present application, the first posture includes N first sub-postures, and the second posture includes N second sub-postures, where N is a positive integer; the processor 720 is specifically used to obtain N first sub-posture parameters corresponding to the N first sub-postures and N first sub-blood pressure values ​​of the user, obtain N second sub-posture parameters corresponding to the N second sub-postures and N second sub-blood pressure values ​​of the user, determine N sub-hydrostatic pressure differences according to the N first sub-posture parameters and the N second sub-posture parameters, and when N is greater than or equal to a preset value, determine a correction matrix according to the N sub-hydrostatic pressure differences, the N first sub-blood pressure values, and the N second sub-blood pressure values.

[0098] It should be understood that in the embodiment of the present application, the input unit 708 may include a graphics processor (Graphics Processing Unit, GPU) 7082 and a microphone 7084, and the graphics processor 7082 processes the image data of the static picture or video obtained by the image capture device (such as a camera) in the video capture mode or the image capture mode. The display unit 712 may include a display panel 7122, and the display panel 7122 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 714 includes at least one of a touch panel 7142 and other input devices 7144. The touch panel 7142 is also called a touch screen. The touch panel 7142 may include two parts: a touch detection device and a touch controller. Other input devices 7144 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0099] The memory 718 can be used to store software programs and various data. The memory 718 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, an application program or instruction required for at least one function (such as a sound playback function, an image playback function, etc.), etc. In addition, the memory 718 may include a volatile memory or a non-volatile memory, or the memory 718 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM) and a direct memory bus random access memory (DRRAM). The memory 718 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0100] The processor 720 may include one or more processing units; optionally, the processor 720 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and application programs, and the modem processor mainly processes wireless communication signals, such as a baseband processor. It is understandable that the modem processor may not be integrated into the processor 720.

[0101] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned data correction method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0102] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0103] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned data correction method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0104] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0105] An embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the above-mentioned data correction method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0106] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0107] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of each embodiment of the present application.

[0108] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A data correction method, characterized in that: include: When a user wears the electronic device and the user is in a first posture, obtaining a first posture parameter of the first posture and a first blood pressure value of the user; When a user wears the electronic device and the user is in a second posture, obtaining a second posture parameter of the second posture and a second blood pressure value of the user; determining a hydrostatic pressure difference based on the first posture parameter and the second posture parameter; Determine a correction matrix according to the hydrostatic pressure difference, the first blood pressure value and the second blood pressure value, wherein the correction matrix is ​​used to correct a target algorithm, the target algorithm is used to measure blood pressure, wherein the first blood pressure value and the second blood pressure value are obtained by the target algorithm; The step of determining a correction matrix according to the hydrostatic pressure difference, the first blood pressure value, and the second blood pressure value comprises: Obtaining a difference between the first blood pressure value and the second blood pressure value; generating an error matrix according to the hydrostatic pressure difference and the difference; Determine the correction matrix according to the error matrix, wherein the correction matrix is ​​an inverse matrix of the error matrix; The first posture includes N first sub-postures, and the second posture includes N second sub-postures, where N is a positive integer; and obtaining the first posture parameter of the first posture and the first blood pressure value of the user includes: Obtaining N first sub-posture parameters corresponding to the N first sub-postures and N first sub-blood pressure values ​​of the user; The obtaining of the second posture parameter of the second posture and the second blood pressure value of the user includes: Obtaining N second sub-posture parameters corresponding to the N second sub-postures and N second sub-blood pressure values ​​of the user; The determining the hydrostatic pressure difference according to the first posture parameter and the second posture parameter comprises: Determining N sub-hydrostatic pressure differences according to the N first sub-attitude parameters and the N second sub-attitude parameters; The step of determining a correction matrix according to the hydrostatic pressure difference, the first blood pressure value, and the second blood pressure value comprises: When N is greater than or equal to a preset value, a correction matrix is ​​determined according to the N sub-hydrostatic pressure differences, the N first sub-blood pressure values, and the N second sub-blood pressure values.

2. The data correction method according to claim 1, characterized in that: The obtaining of the first blood pressure value of the user comprises: Acquiring a first pulse signal of the user; Obtaining the first blood pressure value according to the first pulse signal and the target algorithm; The obtaining of the second blood pressure value of the user comprises: Acquiring a second pulse signal of the user; The second blood pressure value is obtained according to the second pulse signal and the target algorithm.

3. The data correction method according to claim 1, characterized in that: The step of generating an error matrix according to the hydrostatic pressure difference and the difference value comprises: generating the error matrix according to the hydrostatic pressure difference, the difference value and a first formula; Among them, the first formula is A=M×T -1 , A is the error matrix, T is the hydrostatic pressure difference, and M is the difference.

4. A data correction device, characterized in that: include: A first acquisition module, configured to acquire, when a user wears the electronic device and the user is in a first posture, a first posture parameter of the first posture and a first blood pressure value of the user; A second acquisition module, configured to acquire, when a user wears the electronic device and the user is in a second posture, a second posture parameter of the second posture and a second blood pressure value of the user; A first determination module, configured to determine a hydrostatic pressure difference according to the first posture parameter and the second posture parameter; a second determination module, configured to determine a correction matrix according to the hydrostatic pressure difference, the first blood pressure value, and the second blood pressure value, wherein the correction matrix is ​​used to correct a target algorithm, the target algorithm is used to measure blood pressure, and wherein the first blood pressure value and the second blood pressure value are obtained by the target algorithm; a third acquisition module, configured to acquire a difference between the first blood pressure value and the second blood pressure value, and generate an error matrix according to the hydrostatic pressure difference and the difference; The second determination module is specifically configured to determine the correction matrix according to the error matrix, wherein the correction matrix is ​​an inverse matrix of the error matrix; The first posture includes N first sub-postures, and the second posture includes N second sub-postures, where N is a positive integer; The first acquisition module is specifically used to acquire N first sub-posture parameters corresponding to the N first sub-postures and N first sub-blood pressure values ​​of the user; The second acquisition module is specifically used to acquire N second sub-posture parameters corresponding to the N second sub-postures and N second sub-blood pressure values ​​of the user; The first determination module is specifically configured to determine N sub-hydrostatic pressure differences according to the N first sub-posture parameters and the N second sub-posture parameters; The second determination module is specifically used to determine a correction matrix according to the N sub-hydrostatic pressure differences, the N first sub-blood pressure values, and the N second sub-blood pressure values ​​when N is greater than or equal to a preset value.

5. The data correction device according to claim 4, characterized in that: The first acquisition module is specifically used to acquire a first pulse signal of the user, and obtain the first blood pressure value according to the first pulse signal and the target algorithm; The second acquisition module is specifically used to acquire the second pulse signal of the user, and obtain the second blood pressure value according to the second pulse signal and the target algorithm.

6. The data correction device according to claim 4, characterized in that: The third acquisition module is specifically used to generate the error matrix according to the hydrostatic pressure difference, the difference and the first formula; Among them, the first formula is A=M×T -1 , A is the error matrix, T is the hydrostatic pressure difference, and M is the difference.

7. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a program that can be run on the processor, and when the program is executed by the processor, the steps of the data correction method according to any one of claims 1 to 3 are implemented.

8. A readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps of the data correction method according to any one of claims 1 to 3 are implemented.

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