Pressure data processing method and related equipment thereof

Abstract

The embodiment of the invention provides a pressure data processing method which comprises the steps that measurement basic data are obtained, and the measurement basic data are data generated in the blood pressure measurement process of a user through a pressure sensor; determining a plurality of pulse wave minimum value points on the basis of the measurement basic data, wherein the pulse wave minimum value points are points at which pressure data in the measurement basic data is changed from descending to ascending; cubic spline difference algorithm processing is carried out based on the two pulse wave minimum value points and natural boundary conditions, and an interpolation curve is obtained; and taking the interpolation curve as a baseline, and carrying out baseline filtering on the measurement basic data to obtain pulse wave data. Compared with the common linear interpolation, the continuous smoothness of the base line at the end point, which is obtained based on the scheme, has good coherence and smoothness, avoids the jump at the end point, has better implementability, and in addition, the scheme needs fewer computing resources, and is convenient to realize in an embedded platform.

Description

Technical Field

[0001] The present application belongs to the field of data processing, and in particular, relates to a pressure data processing method and related equipment. Background Art

[0002] Blood pressure measurement is the process of using a sphygmomanometer to wrap a cuff around the upper arm or wrist and start the measurement at the heart level to obtain the systolic and diastolic blood pressure values. The pulse wave is generated by the heartbeat, which propagates along the artery and reflects the pressure changes during the heart's contraction and relaxation. By capturing and analyzing the pulse wave signal, we can indirectly understand the working state of the heart, including the heart's contractility, heart rate, heart rhythm and other information. This is of great significance for evaluating heart function and diagnosing cardiovascular diseases.

[0003] In the blood pressure measurement process, the effective pulse wave signal is superimposed on the constantly changing pressure signal generated by a cuff in the signal captured by the pressure sensor. Whether the deflation or pressurization blood pressure measurement method is used, the subsequent algorithm processing needs to extract the pure pulse wave from this composite signal. One of the key steps in this extraction process is baseline removal, which is crucial for accurately measuring the amplitude of the pulse wave, which in turn affects subsequent operations such as fitting the blood pressure envelope. Baseline removal occupies a core position in the blood pressure calculation process: if the baseline is not completely removed, it will cause the pulse wave amplitude to fluctuate; if it is removed excessively, it may cause amplitude attenuation and result in loss of the actual signal. Summary of the invention

[0004] The purpose of the present invention is to provide a pressure data processing method, aiming to solve the problem that the existing data processing process is relatively complicated. The pressure data processing method provided in the first aspect of the embodiment of the present application includes:

[0005] Acquiring basic measurement data, where the basic measurement data is data generated during the process of measuring the blood pressure of a user using a pressure sensor;

[0006] Determine a plurality of pulse wave minimum value points based on the measurement basic data, wherein the pulse wave minimum value points are points where pressure data in the measurement basic data changes from decreasing to increasing;

[0007] Performing cubic spline difference algorithm processing based on the two pulse wave minimum points and natural boundary conditions to obtain an interpolation curve;

[0008] The interpolation curve is used as a baseline, and baseline filtering is performed on the measurement basic data to obtain pulse wave data.

[0009] According to the pressure data processing method provided in the first aspect of the embodiment of the present application, optionally, the basic measurement data is data generated by the user using a pressure sensor blood pressure monitor during the blood pressure reduction process.

[0010] According to the pressure data processing method provided in the first aspect of the embodiment of the present application, optionally, after determining a plurality of pulse wave minimum value points based on the measurement basic data, the method further comprises:

[0011] Determining whether two adjacent pulse wave minimum value points meet preset requirements;

[0012] If the relationship between the two adjacent pulse wave minimum value points meets the preset requirements, the two adjacent pulse wave minimum value points are determined to be the minimum value points of the effective pulse wave;

[0013] The interpolation curve is obtained by performing a cubic spline difference algorithm based on the two pulse wave minimum points and the natural boundary conditions, including:

[0014] Based on the minimum points of two adjacent effective pulse waves and natural boundary conditions, a cubic spline difference algorithm is used to obtain an interpolation curve.

[0015] According to the pressure data processing method provided in the first aspect of the embodiment of the present application, optionally, determining whether the relationship between the minimum value points of two adjacent pulse waves meets the preset requirements includes:

[0016] Determining whether the pressure difference between the two adjacent pulse wave minimum value points meets the preset requirements;

[0017] Determine whether the time difference between the two adjacent pulse wave minimum value points meets the preset requirements.

[0018] According to the pressure data processing method provided in the first aspect of the embodiment of the present application, optionally, the method is implemented on an embedded device platform.

[0019] According to the pressure data processing method provided in the first aspect of the embodiment of the present application, optionally, the processing using a cubic spline difference algorithm based on the two pulse wave minimum points and the natural boundary conditions to obtain an interpolation curve, using the interpolation curve as a baseline, performing baseline filtering on the measured basic data, and obtaining the pulse wave data includes:

[0020] Processing each adjacent pulse wave minimum point and natural boundary condition with a cubic spline difference algorithm to obtain an interpolation curve corresponding to each sampling segment;

[0021] The measured basic data is baseline filtered based on the difference curves corresponding to each sampling segment to obtain pulse wave data.

[0022] According to the pressure data processing method provided in the first aspect of the embodiment of the present application, optionally, determining a plurality of pulse wave minimum value points based on the measured basic data includes:

[0023] A sliding window method is used to determine a plurality of pulse wave minimum value points in the measurement basic data.

[0024] A second aspect of an embodiment of the present application provides a pressure data processing device, including:

[0025] An acquisition unit, used to acquire basic measurement data, where the basic measurement data is data generated during the blood pressure measurement of a user using a pressure sensor;

[0026] a determining unit, configured to determine a plurality of pulse wave minimum value points based on the measurement basic data, wherein the pulse wave minimum value points are points where pressure data in the measurement basic data changes from decreasing to increasing;

[0027] A processing unit, used for performing a cubic spline difference algorithm based on the two pulse wave minimum value points and the natural boundary conditions to obtain an interpolation curve;

[0028] The filtering unit is used to use the interpolation curve as a baseline to perform baseline filtering on the measurement basic data to obtain pulse wave data.

[0029] Based on the pressure data processing device provided in the second aspect of the embodiment of the present application, optionally, the basic measurement data is data generated by the user using a pressure sensor blood pressure monitor during the blood pressure reduction process.

[0030] Based on the pressure data processing device provided in the second aspect of the embodiment of the present application, optionally, the determining unit is further used to:

[0031] Determining whether two adjacent pulse wave minimum value points meet preset requirements;

[0032] If the relationship between the two adjacent pulse wave minimum value points meets the preset requirements, the two adjacent pulse wave minimum value points are determined to be the minimum value points of the effective pulse wave.

[0033] The processing unit is specifically used for: performing cubic spline difference algorithm processing based on the minimum value points of two adjacent effective pulse waves and natural boundary conditions to obtain an interpolation curve.

[0034] Based on the pressure data processing device provided in the second aspect of the embodiment of the present application, optionally, the determining unit is further used to:

[0035] Determining whether the pressure difference between the two adjacent pulse wave minimum value points meets the preset requirements;

[0036] Determine whether the time difference between the two adjacent pulse wave minimum value points meets the preset requirements.

[0037] According to the pressure data processing device provided in the second aspect of the embodiment of the present application, optionally, the device is an embedded device.

[0038] According to the pressure data processing device provided in the second aspect of the embodiment of the present application, optionally,

[0039] The processing unit is specifically used to: perform cubic spline difference algorithm processing on each adjacent pulse wave minimum value point and natural boundary condition to obtain an interpolation curve corresponding to each sampling segment;

[0040] The filtering unit is specifically used for performing baseline filtering on the measurement basic data based on the difference curves corresponding to each sampling segment to obtain pulse wave data.

[0041] According to the pressure data processing device provided by the second aspect of the embodiment of the present application, optionally, the determining unit is specifically used for:

[0042] A sliding window method is used to determine a plurality of pulse wave minimum value points in the measurement basic data.

[0043] A third aspect of the embodiment of the present application provides a pressure data processing device, including:

[0044] CPU, memory, input and output interfaces, wired or wireless network interfaces, and power supply;

[0045] The memory is a short-term storage memory or a persistent storage memory;

[0046] The central processing unit is configured to communicate with the memory and execute instruction operations in the memory on the device to perform the method described in any one of the first aspects of the embodiments of the present application.

[0047] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, enable the computer to execute a method as described in any one of the first aspects of the embodiment of the present application.

[0048] A fifth aspect of the embodiments of the present application provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute a method as described in any one of the first aspects of the embodiments of the present application.

[0049] It can be seen from the above technical scheme that the embodiment of the present application has the following advantages: the embodiment of the present application provides a pressure data processing method, including: obtaining measurement basic data, the measurement basic data is the data generated in the process of measuring the blood pressure of the user using a pressure sensor; determining multiple pulse wave minimum points based on the measurement basic data, the pulse wave minimum point is the point where the pressure data in the measurement basic data changes from falling to rising; performing cubic spline difference algorithm processing based on the two pulse wave minimum points and natural boundary conditions to obtain an interpolation curve; using the interpolation curve as a baseline, performing baseline filtering on the measurement basic data to obtain pulse wave data. The baseline obtained based on this scheme is continuously smooth at the endpoints, which has good coherence and smoothness compared to ordinary linear interpolation, avoids jumps at the endpoints, and has better feasibility. In addition, this scheme requires fewer computing resources and is easy to implement in embedded platforms. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without creative work. It is understood that the drawings provided in this section are only used to better understand the present solution and do not constitute a limitation of the present application.

[0051] Figure 1 A schematic flow chart of an embodiment of the pressure data processing method provided in this application.

[0052] Figure 2 This is another flowchart diagram of an embodiment of the pressure data processing method provided in the present application.

[0053] Figure 3 A schematic diagram of an overall flow chart of an embodiment of the pressure data processing method provided in this application.

[0054] Figure 4 A schematic diagram of the pulse wave minimum point determination process provided in this application.

[0055] Figure 5 A schematic diagram of the processing of the cubic spline interpolation algorithm provided in this application.

[0056] Figure 6 A schematic diagram of the superposition of the original signal waveform and the difference curve provided in this application.

[0057] Figure 7 A schematic diagram of a pulse wave signal waveform after filtering provided by the present application.

[0058] Figure 8 A structural schematic diagram of an embodiment of the pressure data processing device provided in this application.

[0059] Fig. 9 This is another structural schematic diagram of an embodiment of the pressure data processing device provided in this application. DETAILED DESCRIPTION

[0060] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application are clearly and completely described below. Obviously, the described embodiments are only embodiments of a part of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should belong to the scope of protection of the present application. At the same time, for the sake of clarity and simplicity, the description of well-known functions and structures is omitted in the following description.

[0061] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0062] Blood pressure measurement is the process of using a sphygmomanometer to wrap a cuff around the upper arm or wrist and start the measurement at the heart level to obtain the systolic and diastolic blood pressure values. The pulse wave is generated by the heartbeat, which propagates along the artery and reflects the pressure changes during the heart's contraction and relaxation. By capturing and analyzing the pulse wave signal, we can indirectly understand the working state of the heart, including the heart's contractility, heart rate, heart rhythm and other information. This is of great significance for evaluating heart function and diagnosing cardiovascular diseases.

[0063] In the process of blood pressure measurement, the effective pulse wave signal is superimposed on a constantly changing pressure signal in the signal captured by the pressure sensor. Whether the deflation or pressurization blood pressure measurement method is used, the subsequent algorithm processing needs to extract the pure pulse wave from this composite signal. One of the key steps in this extraction process is baseline removal, which is crucial for accurately measuring the amplitude of the pulse wave, and thus affects subsequent operations such as fitting the blood pressure envelope. Baseline removal occupies a core position in the blood pressure calculation process: if the baseline is not removed thoroughly, it will cause the pulse wave amplitude to fluctuate; if it is removed excessively, it may cause amplitude attenuation and result in loss of the actual signal.

[0064] Currently, baseline removal techniques include median filtering, wavelet transform, high-pass filtering, band-pass filtering and other methods, each of which has its own unique advantages and limitations. In view of this situation, this application aims to propose an innovative baseline filtering algorithm to specifically solve the problem of baseline removal in the blood pressure measurement process to ensure the accurate extraction of pulse wave signals.

[0065] To solve the above problems, the first aspect of the present application provides a pressure data processing method, see Figure 1 , an embodiment of the pressure data processing method provided in the present application includes: step 101-step 104.

[0066] 101. Obtain basic measurement data.

[0067] Obtain basic measurement data, which is the original data generated during the process of measuring the user's blood pressure using a pressure sensor. In the actual implementation process, a cuff can be used to collect and detect data from the user. The purpose of this process is to simultaneously complete the blood pressure detection of the user and the pulse wave detection of the user, thereby obtaining more comprehensive user body data. The specific basic measurement data is a curve composed of pressure data and time data generated during the user's blood pressure measurement. During the measurement process, it may be in a stable pressure increase process or pressure decrease process, that is, the pressure provided by the external blood pressure measurement device, in addition to the pressure generated by the pulse wave. The two parameters are superimposed on each other to form the basic measurement data. In the actual implementation process, the basic measurement data can be obtained through the data port of the blood pressure measurement device, which is not limited here.

[0068] 102. Determine a plurality of pulse wave minimum value points based on the measurement basic data.

[0069] Based on the measurement basic data, multiple pulse wave minimum points are determined, and the pulse wave minimum point is the point where the pressure data in the measurement basic data changes from decreasing to increasing; the number of pulse wave minimum points should be greater than or equal to two, so as to facilitate the processing of subsequent steps. Specifically, the pulse wave minimum point is the bottom of the pulse wave. There will be one pulse wave minimum point in a pulse cycle, and the pulse wave minimum point can be determined as the point where only the pressure provided by the external blood pressure measurement device exists, or the pressure provided by the pulse itself is small, which is the value of the baseline at this point. Therefore, this point can be used to determine the baseline. In the actual implementation process, the pulse wave minimum point can be determined by using the extreme point recognition method and other methods for identification, which will not be elaborated here.

[0070] 103. Based on two pulse wave minimum points and natural boundary conditions, a cubic spline difference algorithm is used to obtain an interpolation curve.

[0071] Specifically, after determining the two pulse wave minimum points, the cubic spline interpolation algorithm is used to process the two pulse wave minimum points using the natural boundary conditions (the second-order derivative of the endpoint is 0) to obtain the difference curve. The equation of the cubic spline interpolation function is:

[0072] y=ax 3 +bx 2 +cx+d

[0073] a, b, c, d are the coefficients that need to be calculated, and the two endpoints and natural boundary conditions are all the conditions for calculating the coefficients. After integration, the corresponding matrix can be obtained, and then the corresponding equation coefficients can be obtained using the matrix conditions. In the actual implementation process, the pulse wave minimum point used should be the nearest pulse wave minimum point, or the adjacent pulse wave minimum point, and in the case of multiple pulse wave minimum points, multiple cubic spline interpolation processes should be performed to obtain a difference curve that is closer to the baseline. The cubic spline interpolation algorithm is a commonly used numerical analysis method, which can fit a smooth continuous function curve through a given set of scattered data. The baseline changes during blood pressure measurement are generally smooth, so the difference curve obtained by this scheme is largely consistent with the changes in the baseline.

[0074] 104. Using the interpolation curve as a baseline, baseline filtering is performed on the measurement basic data to obtain pulse wave data.

[0075] Specifically, the interpolation curve is used as a baseline, and the measured basic data is baseline filtered to obtain pulse wave data. That is, the values ​​of the measured basic data and the corresponding points of the interpolation curve are differentiated, and the corresponding pulse wave signal after removing the baseline can be obtained. In the actual implementation process, cubic spline interpolation can be performed on each adjacent point to obtain multiple difference curves, and the multiple results are differentiated from the measured basic data, thereby improving the accuracy of the obtained pulse wave data.

[0076] It can be seen from the above technical scheme that the embodiment of the present application has the following advantages: the embodiment of the present application provides a pressure data processing method, including: obtaining measurement basic data, the measurement basic data is the data generated in the process of measuring the blood pressure of the user using a pressure sensor; determining multiple pulse wave minimum points based on the measurement basic data, the pulse wave minimum point is the point where the pressure data in the measurement basic data changes from falling to rising; performing cubic spline difference algorithm processing based on two adjacent pulse wave minimum points and natural boundary conditions to obtain an interpolation curve; using the interpolation curve as a baseline, performing baseline filtering on the measurement basic data to obtain pulse wave data. The baseline obtained based on this scheme is continuously smooth at the endpoint, which has good coherence and smoothness compared to ordinary linear interpolation, avoids jumps at the endpoint, and has better feasibility. In addition, this scheme requires fewer computing resources and is easy to implement in an embedded platform.

[0077] To facilitate the use of this method in actual implementation, this application also provides a more detailed embodiment that can be optionally implemented, please refer to Figure 2 Another embodiment of the pressure data processing method provided in the present application includes: steps 201 to 206.

[0078] The overall process of this program can be referred to Figure 3 , which includes four steps, namely, finding the pulse wave minimum point in the measurement basic data, performing cubic spline interpolation on adjacent pulse wave minimum points, interpolating the measurement basic data and the interpolation curve, and obtaining the pulse wave signal after filtering the baseline.

[0079] 201. Obtain basic measurement data.

[0080] 202. Determine a plurality of pulse wave minimum value points based on the measurement basic data.

[0081] The specific steps 201 to 202 are the same as those mentioned above. Figure 1 Steps 101 to 102 in the corresponding embodiment are similar and will not be described in detail here.

[0082] In the actual implementation process, the sliding window method can be used to determine multiple pulse wave minimum points in the measurement basic data. The sliding window method is a signal processing technology that slides on the signal by setting a window of fixed length and searches for the signal minimum in each window. It can effectively extract key features in the measurement basic data.

[0083] In the process of determining the measurement basic data to determine multiple pulse wave minimum points, it should be noted that the validity of the minimum point data should be confirmed, and a reasonable minimum value should be found before performing cubic spline interpolation, otherwise the obtained equation will be difficult to meet the requirements, and the obtained baseline will change too fast or too slow (small minimum interval or large interval). Determine whether two adjacent pulse wave minimum points meet the preset requirements; if the relationship between the two adjacent pulse wave minimum points meets the preset requirements, the two adjacent pulse wave minimum points are determined to be the minimum points of the effective pulse wave; the setting of the preset requirements can be determined by the pressure difference and duration difference described in the following steps 203 and 204.

[0084] 203. Determine whether the pressure difference between the two adjacent pulse wave minimum value points meets a preset requirement.

[0085] Specifically, the pressure difference is used as a reference for verification. Under the current environment of stable blood pressure reduction, the pressure corresponding to the previous pulse wave minimum point should be lower than the pressure corresponding to the next pulse wave minimum point, which is consistent with the change of mechanical pressure.

[0086] 204. Determine whether the time difference between the two adjacent pulse wave minimum value points meets a preset requirement.

[0087] Specifically, determine whether the time difference between the two adjacent pulse wave minimum points meets the preset requirements. The time distance should meet the heart rate change situation, that is, the general heart rate range is 30 to 200 (times / minute). If all the requirements are met, then this point is the minimum point. If not, a prompt can be issued to the user to remind the user to re-measure. The specific process of determining the pulse wave minimum point can be referred to in this application Figure 4 , this application Figure 4 That is a schematic diagram of the pulse wave minimum point determination process. It can be understood that in the actual implementation process, there is no timing restriction between step 203 and step 204. In the actual implementation process, the execution order can be adjusted according to any requirements, and the pulse wave minimum value identification method can be further refined. The specifics are not limited here.

[0088] 205. Performing a cubic spline difference algorithm on each adjacent pulse wave minimum value point and natural boundary condition to obtain an interpolation curve corresponding to each sampling segment.

[0089] Specifically, the cubic spline interpolation algorithm is used to process each adjacent pulse wave minimum point and natural boundary condition to obtain an interpolation curve corresponding to each sampling segment. The processing process of the cubic spline interpolation algorithm can be referred to Figure 5 , for each pulse wave minimum point that has been identified, cubic spline interpolation is performed. The equation of the cubic spline interpolation function is:

[0090] y=ax 3 +bx 2 +cx+d

[0091] a, b, c, d are the coefficients that need to be calculated. Figure 5 The dotted line in the middle is the minimum value that has been found when all the conditional endpoint values ​​of the coefficients are sought. After combining with other conditions, the corresponding matrix can be obtained. Then the matrix conditions can be used to obtain the corresponding equation coefficients. Cubic spline interpolation is a mature method and will not be introduced in detail here.

[0092] 206. Perform baseline filtering on the measurement basic data based on the difference curves corresponding to each sampling segment to obtain pulse wave data.

[0093] Specifically, the process before filtering can refer to the attached Figure 6 , Figure 6 The original signal waveform is shown in . This process is a process of reducing pressure. The pulse wave is superimposed on the original signal. S44 represents the pulse wave superimposed on the original signal. It can be seen that the baseline of the pulse wave is also decreasing with the change of the pressure signal. In the later algorithm, the amplitude of the pulse wave is needed to be extracted, so this decreasing baseline needs to be removed. S40, that is, each asterisk is the minimum point of the pulse wave found in the original data, and it is also the starting point of each pulse wave. There are many valid pulse waves in the original signal, so multiple minimum points can be found. By using cubic spline interpolation for each two adjacent minimum points, the cubic equation between two adjacent points can be obtained, that is, the difference curve, and then the value corresponding to any point in this interval, that is, S41, can be obtained. Figure 6 The vertical axis S42 represents the pressure value in hundredths of millimeters of mercury, and the horizontal axis S43 represents the time information.

[0094] After the cubic spline interpolation equation is obtained, the value of the corresponding point is obtained. The original signal and the value of the corresponding point are differentiated to obtain the corresponding pulse wave signal after removing the baseline. For details, please refer to Figure 7 , Figure 7 S50 is the effective pulse wave signal waveform.

[0095] It can be understood that the solution of removing baseline by cubic spline interpolation provided in this solution can be applied not only to the processing of pulse wave signals, but also to the processing of other similar types of signals. For example, the photoplethysmography (PPG) measurement process can also use the cubic spline interpolation using minimum values ​​provided by this solution to remove the baseline. The specific method here can be determined according to the actual situation and is not limited here.

[0096] The solution provided in this application can be applied to a variety of measuring devices, such as blood pressure monitors or wearable devices, etc., and the specifics are not limited here.

[0097] It can be seen from the above technical scheme that the embodiment of the present application has the following advantages: the embodiment of the present application provides a pressure data processing method, including: obtaining measurement basic data, the measurement basic data is the data generated in the process of measuring the blood pressure of the user using a pressure sensor; determining multiple pulse wave minimum points based on the measurement basic data, the pulse wave minimum point is the point where the pressure data in the measurement basic data changes from falling to rising; performing cubic spline difference algorithm processing based on two adjacent pulse wave minimum points and natural boundary conditions to obtain an interpolation curve; using the interpolation curve as a baseline, performing baseline filtering on the measurement basic data to obtain pulse wave data. The baseline obtained based on this scheme is continuously smooth at the endpoint, which has good coherence and smoothness compared to ordinary linear interpolation, avoids jumps at the endpoint, and has better feasibility. In addition, this scheme requires fewer computing resources and is easy to implement in an embedded platform.

[0098] The above content describes the pressure data processing method provided by the present application. To support the implementation of the above embodiment, the present application also provides a pressure data processing device. Figure 8 , an embodiment of the pressure data processing device provided by the present application includes:

[0099] An acquisition unit 801 is used to acquire basic measurement data, where the basic measurement data is data generated during the blood pressure measurement of a user using a pressure sensor;

[0100] A determination unit 802 is used to determine a plurality of pulse wave minimum value points based on the measurement basic data, wherein the pulse wave minimum value points are points where the pressure data in the measurement basic data changes from decreasing to increasing;

[0101] The processing unit 803 is used to perform a cubic spline difference algorithm based on the two pulse wave minimum value points and the natural boundary conditions to obtain an interpolation curve;

[0102] The filtering unit 804 is used to use the interpolation curve as a baseline to perform baseline filtering on the measurement basic data to obtain pulse wave data.

[0103] In this embodiment, the process executed by each unit in the pressure data processing device is the same as the above Figure 1 The method flow described in the corresponding embodiment is similar and will not be repeated here.

[0104] Optionally, the basic measurement data is data generated by a user using a pressure sensor blood pressure monitor during a blood pressure reduction process.

[0105] Optionally, the determining unit is further configured to:

[0106] Determining whether two adjacent pulse wave minimum value points meet preset requirements;

[0107] If the relationship between the two adjacent pulse wave minimum value points meets the preset requirements, the two adjacent pulse wave minimum value points are determined to be the minimum value points of the effective pulse wave.

[0108] The processing unit is specifically used for: performing cubic spline difference algorithm processing based on the minimum value points of two adjacent effective pulse waves and natural boundary conditions to obtain an interpolation curve.

[0109] Optionally, the determining unit is further configured to:

[0110] Determining whether the pressure difference between the two adjacent pulse wave minimum value points meets the preset requirements;

[0111] Determine whether the time difference between the two adjacent pulse wave minimum value points meets the preset requirements.

[0112] Optionally, the device is an embedded device.

[0113] Optionally, the processing unit is specifically used to: perform cubic spline difference algorithm processing on each adjacent pulse wave minimum value point and natural boundary condition to obtain an interpolation curve corresponding to each sampling segment;

[0114] The filtering unit is specifically used for performing baseline filtering on the measurement basic data based on the difference curves corresponding to each sampling segment to obtain pulse wave data.

[0115] Optionally, the determining unit is specifically configured to:

[0116] A sliding window method is used to determine a plurality of pulse wave minimum value points in the measurement basic data.

[0117] Fig. 9It is a structural diagram of a pressure data processing device provided in an embodiment of the present application. The pressure data processing device 900 may include one or more central processing units (CPU) 901 and a memory 905. The memory 905 stores one or more application programs or data.

[0118] In this embodiment, the specific functional module division in the central processing unit 901 can be the same as the above Figure 8 The functional module division method of each unit described in is similar and will not be repeated here.

[0119] The memory 905 may be a volatile storage or a persistent storage. The program stored in the memory 905 may include one or more modules, each of which may include a series of instruction operations in the pressure data processing device. Furthermore, the central processor 901 may be configured to communicate with the memory 905 and execute a series of instruction operations in the memory 905 on the server 900.

[0120] The server 900 may further include one or more power supplies 902 , one or more wired or wireless network interfaces 903 , one or more input / output interfaces 904 , and the like.

[0121] The CPU 901 can execute the aforementioned Figure 1 The operations performed by the pressure data processing method in the illustrated embodiment will not be described in detail here.

[0122] The embodiment of the present application also provides a computer storage medium, which is used to store computer software instructions used for the above-mentioned pressure data processing method, including a program designed for executing the pressure data processing method.

[0123] The pressure data processing method can be as described above. Figure 1 or Figure 2 The pressure data processing method described in .

[0124] The present application also provides a computer program product, which includes computer software instructions, which can be loaded by a processor to implement the above Figure 1 Figure 2 The process of any one of the pressure data processing methods.

[0125] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the equivalent transformation of the circuit, the division of the unit, is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0127] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0128] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modification, equivalent substitution or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A pressure data processing method, characterized in that: include: Acquiring basic measurement data, where the basic measurement data is data generated during the process of measuring the blood pressure of a user using a pressure sensor; Determine a plurality of pulse wave minimum value points based on the measurement basic data, wherein the pulse wave minimum value points are points where pressure data in the measurement basic data changes from decreasing to increasing; Performing cubic spline difference algorithm processing based on the two pulse wave minimum points and natural boundary conditions to obtain an interpolation curve; The interpolation curve is used as a baseline, and baseline filtering is performed on the measurement basic data to obtain pulse wave data.

2. The pressure data processing method according to claim 1, characterized in that: The basic measurement data is the data generated by the user using the pressure sensor blood pressure monitor during the blood pressure reduction process.

3. The pressure data processing method according to claim 1, characterized in that: After determining a plurality of pulse wave minimum value points based on the measurement basic data, the method further comprises: Determining whether two adjacent pulse wave minimum value points meet preset requirements; If the relationship between the two adjacent pulse wave minimum value points meets the preset requirements, the two adjacent pulse wave minimum value points are determined to be the minimum value points of the effective pulse wave; The interpolation curve is obtained by performing a cubic spline difference algorithm based on the two pulse wave minimum points and the natural boundary conditions, including: Based on the minimum points of two adjacent effective pulse waves and natural boundary conditions, a cubic spline difference algorithm is used to obtain an interpolation curve.

4. The pressure data processing method according to claim 3, characterized in that: The step of determining whether the relationship between the minimum value points of two adjacent pulse waves meets a preset requirement includes: Determining whether the pressure difference between the two adjacent pulse wave minimum value points meets the preset requirements; Determine whether the time difference between the two adjacent pulse wave minimum value points meets the preset requirements.

5. The pressure data processing method according to claim 1, characterized in that: The method is implemented on an embedded device platform.

6. The pressure data processing method according to claim 1, characterized in that: The method of performing a cubic spline difference algorithm based on the two pulse wave minimum points and the natural boundary conditions to obtain an interpolation curve, using the interpolation curve as a baseline, and performing baseline filtering on the measurement basic data to obtain pulse wave data includes: Processing each adjacent pulse wave minimum point and natural boundary condition with a cubic spline difference algorithm to obtain an interpolation curve corresponding to each sampling segment; The measured basic data is baseline filtered based on the difference curves corresponding to each sampling segment to obtain pulse wave data.

7. The pressure data processing method according to claim 1, characterized in that: The step of determining a plurality of pulse wave minimum value points based on the measurement basic data comprises: A sliding window method is used to determine a plurality of pulse wave minimum value points in the measurement basic data.

8. A pressure data processing device, characterized in that: include: An acquisition unit, used to acquire basic measurement data, where the basic measurement data is data generated during the blood pressure measurement of a user using a pressure sensor; a determining unit, configured to determine a plurality of pulse wave minimum value points based on the measurement basic data, wherein the pulse wave minimum value points are points where pressure data in the measurement basic data changes from decreasing to increasing; A processing unit, used for performing a cubic spline difference algorithm based on the two pulse wave minimum value points and the natural boundary conditions to obtain an interpolation curve; The filtering unit is used to use the interpolation curve as a baseline to perform baseline filtering on the measurement basic data to obtain pulse wave data.

9. A pressure data processing device, characterized in that: include: CPU, memory, input and output interfaces, wired or wireless network interfaces, and power supply; The memory is a short-term storage memory or a persistent storage memory; The central processing unit is configured to communicate with the memory, and execute instructions in the memory on the device to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The method comprises instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 7.

Images