Rapid measurement method, device and equipment for ambulatory blood pressure monitoring and medium

Abstract

The invention discloses a rapid measurement method, device and equipment for ambulatory blood pressure monitoring and a medium. The method comprises the steps that oscillatory wave signals are collected, pulse wave data of two adjacent times of measurement are obtained, and the pulse wave data of the two adjacent times of measurement comprise the currently measured pulse wave data and the pulse wave data of the previous time of measurement; judging whether a cuff deflation condition is met or not according to the pulse wave data of the two adjacent times of measurement, wherein the cuff deflation condition comprises a time interval of the two adjacent times of detection, a heart rate difference value of the two adjacent times of detection, the maximum pulse wave similarity of the two adjacent times of detection and whether a fitting curve of the two adjacent times of detection meets a preset condition or not; if the cuff deflation condition is met, the cuff is controlled to deflate, and the blood pressure value is output according to the currently measured pulse wave data. According to the invention, the collection time can be reduced, and emotion interference to the user due to long collection time is avoided.

Description

Technical Field

[0001] The present invention relates to the field of blood pressure monitoring, and in particular to a rapid measurement method, device, equipment and medium for dynamic blood pressure monitoring. Background Art

[0002] Blood pressure is an important physiological parameter of the human body. It can reflect the functional status of the human heart and blood vessels. It is an important basis for clinical diagnosis of diseases, observation of treatment effects, and prognosis judgment. Dynamic blood pressure monitoring is a technology that uses a dynamic blood pressure recorder to monitor blood pressure for 24 hours without affecting the patient's daily activities. The recorder tracks, measures and records blood pressure at set time intervals.

[0003] The oscillometric method, also known as the oscillation method, is a blood pressure measurement technology widely used in various clinical monitors and electronic sphygmomanometers. The principle of measuring blood pressure is as follows: when using a cuff to inflate and deflate blood pressure, as the cuff pressure decreases, a pressure oscillation wave (also called a pulse wave) will appear in the cuff. After the amplitude of the oscillation wave is extracted, the systolic and diastolic pressures are obtained through curve fitting and other techniques.

[0004] In the process of measuring blood pressure by curve fitting using the oscillometric method, in order to make the fitted curve closer to the actual blood pressure changes, it is necessary to collect more pulse waves under different pressures, which leads to a long collection time, making the user feel uncomfortable, and may cause emotional interference such as tension, which in turn leads to inaccurate blood pressure measurement. In scenarios such as dynamic blood pressure monitoring where continuous or multiple measurements of the same user are required, multiple measurements will cause the user's discomfort to increase. Therefore, in the scenario of continuous or multiple blood pressure measurements, a rapid detection method is needed to minimize the user's discomfort by shortening the detection time as much as possible while ensuring accuracy. Summary of the invention

[0005] In response to the above technical problems, the present invention provides a rapid measurement method, device, equipment and medium for dynamic blood pressure monitoring, which can reduce the collection time and avoid emotional interference to users due to long collection time.

[0006] In a first aspect, the present invention provides a rapid measurement method for dynamic blood pressure monitoring, comprising: collecting an oscillation wave signal to obtain pulse wave data of two adjacent measurements, the pulse wave data of two adjacent measurements including the pulse wave data of a current measurement and the pulse wave data of a previous measurement; judging whether a cuff deflation condition is met based on the pulse wave data of the two adjacent measurements, the cuff deflation condition comprising: the time interval between two adjacent detections, the heart rate difference between two adjacent detections, the maximum pulse wave similarity between two adjacent detections, and whether a fitting curve of two adjacent detections meets a preset condition; if the cuff deflation condition is met, controlling the cuff to deflate, and outputting a blood pressure value based on the pulse wave data.

[0007] In an optional implementation, judging whether the cuff deflation condition is met according to the pulse wave data of the two adjacent measurements includes:

[0008] If the time interval between two adjacent detections meets the time threshold and if the heart rate difference between two adjacent detections is less than the first threshold, the maximum pulse wave similarity of the two adjacent detections is determined. If the maximum pulse waves of the two adjacent detections are similar, it is checked whether the Gaussian fitting curves of the two adjacent detections meet the preset conditions. If they meet the preset conditions, the currently measured pulse wave data meets the cuff deflation conditions.

[0009] In an optional embodiment, the pulse wave data includes a pulse wave pressure and amplitude data set; if the maximum pulse waves of two adjacent detections are similar, then checking whether the Gaussian fitting curves of the two adjacent detections meet a preset condition also includes:

[0010] A Gaussian fitting curve of a current measurement is calculated according to the pulse wave data, and a fitting similarity between the Gaussian fitting curve and a Gaussian fitting curve of a previous measurement is determined based on cross-validation of the pulse wave data.

[0011] In an optional implementation, the cross-validation based on pulse wave data determines the fitting similarity between the Gaussian fitting curve and the Gaussian fitting curve of the previous measurement, including:

[0012] Substitute the pressure values ​​corresponding to all the currently measured pulse waves into the Gaussian function of the previous measurement to obtain the first amplitude value of the pulse wave, and substitute the pressure values ​​corresponding to all the previously measured pulse waves into the Gaussian function of the current measurement to obtain the second amplitude value of the pulse wave;

[0013] Subtracting the first amplitude value from the corresponding amplitude value measured on the previous side to obtain a first absolute value, and subtracting the second amplitude value from the corresponding amplitude value measured currently to obtain a second absolute value;

[0014] If the first absolute value and the second absolute value are both smaller than the third threshold, it indicates that the Gaussian fitting curve has a similar fitting degree to the Gaussian fitting curve of the previous measurement, and the currently measured pulse wave data meets the cuff deflation condition.

[0015] In an optional implementation, judging whether the cuff deflation condition is met according to the pulse wave data of the two adjacent measurements includes:

[0016] The heart rate difference is obtained by subtracting the current heart rate value measured from the heart rate value measured last time and taking the absolute value of the difference, and the heart rate difference is compared with a first threshold; if the heart rate difference is less than the first threshold, the current heart rate value is judged to be valid; wherein the time interval between the current measurement and the last measurement meets the time threshold.

[0017] In an optional implementation, judging whether the cuff deflation condition is met based on the pulse wave data of the two adjacent measurements further includes:

[0018] Calculating a ratio coefficient between the current maximum pulse wave measured and the previous maximum pulse wave measured, if the ratio coefficient is not greater than a second threshold, it indicates that the effective maximum amplitude pulse wave currently measured has appeared;

[0019] Compare the waveform similarity between the effective maximum amplitude pulse wave currently measured and the maximum pulse wave measured on the previous side. If the waveforms are similar, check whether the Gaussian fitting curves of two adjacent tests meet the preset conditions.

[0020] In an optional implementation, judging whether the cuff deflation condition is met based on the pulse wave data of the two adjacent measurements further includes: determining a maximum pulse wave amplitude value measured, and updating the maximum pulse wave amplitude value to a currently measured maximum pulse wave amplitude value.

[0021] A second aspect of the present invention provides a rapid measurement device for dynamic blood pressure monitoring, comprising:

[0022] An acquisition module, used for acquiring an oscillation wave signal to obtain pulse wave data of two consecutive measurements, wherein the pulse wave data of two consecutive measurements include the pulse wave data of the current measurement and the pulse wave data of the previous measurement;

[0023] A processing module, used for judging whether the cuff deflation condition is met according to the pulse wave data of two adjacent measurements, wherein the cuff deflation condition includes: the time interval between two adjacent detections, the heart rate difference between two adjacent detections, the maximum pulse wave similarity between two adjacent detections, and whether the fitting curves of two adjacent detections meet the preset conditions;

[0024] The control module is used to control the cuff to deflate if the cuff deflation condition is met, and output the blood pressure value according to the pulse wave data.

[0025] According to a third aspect of the present invention, there is provided an electronic device, comprising:

[0026] At least one processor; and at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the rapid measurement method for dynamic blood pressure monitoring as described in the first aspect of the embodiment of the present invention.

[0027] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a computer, the computer program executes the rapid measurement method for dynamic blood pressure monitoring as described in the first aspect of the embodiment of the present invention.

[0028] During the blood pressure measurement process, the present invention continuously compares the relevant parameters of the current measurement and the previous measurement. If the conditions are met, the two measurements are considered to be measurements of the same individual with little change in blood pressure. The blood pressure measurement result can be directly calculated based on the acquired parameters, thereby realizing rapid detection of blood pressure measurement, reducing the acquisition time, and avoiding emotional interference to users due to long acquisition time. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Schematic diagram of measuring blood pressure by pulse wave curve fitting.

[0030] Figure 2 The figure is a flow chart of a rapid measurement method for dynamic blood pressure monitoring in an embodiment of the present invention.

[0031] Figure 3 Schematic diagram of a module of a rapid measurement device for dynamic blood pressure monitoring in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0033] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0034] Figure 1The figure is a schematic diagram of measuring blood pressure by pulse wave curve fitting. When measuring blood pressure, the pulse wave when the cuff pressure drops is extracted to obtain the corresponding data of the pulse wave amplitude and the cuff pressure. The pressure and amplitude data are curve fitted, and the pressure corresponding to the highest point on the curve is the average pressure. The pressure corresponding to the position where the average pressure on the left side of the curve drops a certain ratio is the systolic pressure. The pressure corresponding to the position where the average pressure on the right side of the curve drops a certain ratio is the diastolic pressure. Measuring blood pressure by curve fitting using pulse waves is a prior art and will not be described in detail here.

[0035] like Figure 1 As shown in the figure, in order to obtain more accurate diastolic pressure information, after collecting the pulse wave with the highest amplitude, it is necessary to collect multiple pulse waves with smaller amplitudes, which will lead to a longer collection time, especially when using the step-by-step deflation method. In scenarios such as dynamic blood pressure monitoring that require continuous or multiple measurements of the same user, the blood pressure of the same individual does not change much in a short period of time, which makes it possible to quickly measure blood pressure.

[0036] During the blood pressure measurement process, the present invention continuously compares the relevant parameters of the current measurement and the previous measurement. If certain conditions are met, it is considered that the two measurements are consistent with measurements of the same individual with little change in blood pressure; the blood pressure measurement result is directly calculated based on the acquired parameters, thereby realizing rapid detection of blood pressure measurement.

[0037] See also Figure 2 The present invention provides a rapid measurement method for dynamic blood pressure monitoring, comprising the following steps.

[0038] S100: Collecting oscillation wave signals to obtain pulse wave data of two consecutive measurements. The pulse wave data includes a pulse wave pressure and amplitude data set.

[0039] S200: Determine whether the cuff deflation condition is met based on the pulse wave data of the two adjacent measurements, the cuff deflation condition includes: the time interval between two adjacent detections, the heart rate difference between two adjacent detections, the maximum pulse wave similarity between two adjacent detections, and whether the fitting curves of two adjacent detections meet the preset conditions.

[0040] S300: If the cuff deflation condition is met, the cuff is controlled to deflate, and a blood pressure value is output according to the pulse wave data.

[0041] Acquiring a pulse wave by analyzing the collected oscillation wave signal is a prior art and will not be described in detail here. In some embodiments, each time a pulse wave is acquired, it is determined whether the current monitoring meets all deflation conditions. If all deflation conditions are met, the cuff is fully deflated, the acquisition is terminated, and the final blood pressure measurement result is output; if all deflation conditions are not met, it is further determined whether it can be terminated under normal measurement logic. If it can be terminated according to normal measurement logic, the cuff is also fully deflated, the acquisition is terminated and the result is output; otherwise, the oscillation wave signal is continued to be acquired to obtain the next pulse wave, and the process is repeated until the acquisition is completed.

[0042] Specifically, it can be determined whether the monitored pulse wave data meets the cuff deflation condition. First, the maximum pulse wave amplitude value measured is determined, and the maximum pulse wave amplitude value is updated to the current maximum pulse wave amplitude value measured.

[0043] After acquiring a pulse wave, determine whether the current pulse wave amplitude value is greater than or equal to the maximum pulse wave amplitude value. At the beginning of each measurement, the maximum pulse wave amplitude value is initialized to 0. If the current pulse wave amplitude value is greater than or equal to the maximum pulse wave amplitude value, the currently monitored pulse wave data is updated to the information of the maximum pulse wave.

[0044] The pulse wave data is an oscillation wave signal of a fixed distance before and after the position of the maximum pulse wave amplitude. If the current pulse wave amplitude value is less than the maximum pulse wave amplitude value, the pulse wave amplitude value is determined.

[0045] For example, the judgment condition is: the maximum pulse wave amplitude value is greater than the threshold value TH_AMP; the ratio of the current pulse wave amplitude value to the maximum pulse wave amplitude value is less than the threshold value TH_RATIO. If neither condition is met, or only one of them is met, the judgment process ends and the next pulse wave acquisition is started.

[0046] Then, the time interval, heart rate, maximum pulse similarity, and fitting similarity of the Gaussian fitting curve between two adjacent tests are judged in turn. If the time interval between two adjacent tests meets the time threshold and if the heart rate difference between the two adjacent tests is less than the first threshold, the maximum pulse wave similarity between the two adjacent tests is judged. If the maximum pulse waves of the two adjacent tests are similar, whether the Gaussian fitting curves of the two adjacent tests meet the preset conditions is checked. If the preset conditions are met, the currently measured pulse wave data meets the cuff deflation conditions.

[0047] For example, when comparing the heart rate difference between two adjacent detections, the current heart rate value measured is subtracted from the heart rate value of the previous measurement and the absolute value of the difference is taken to obtain the heart rate difference, and the heart rate difference is compared with a first threshold; if the heart rate difference is less than the first threshold, the current heart rate value is judged to be valid; wherein the time interval between the current measurement and the previous measurement meets the time threshold to determine that the pulse wave of the same individual is being measured.

[0048] Subtract the time point of the previous measurement from the time point of the current measurement to obtain the time interval between the two measurements, and check whether the time interval is less than the first threshold TH_TIME. If the time interval is less than the first threshold, it is considered that the time interval condition is met; otherwise, the time interval condition is not met. Then the heart rate is compared. It is a prior art to obtain the heart rate through the pulse wave interval when measuring blood pressure, which will not be repeated here. The heart rate of the current measurement is subtracted from the heart rate of the previous measurement and the absolute value is taken as the heart rate difference, and the heart rate difference is compared to see whether it is less than the second threshold TH_HR. If the heart rate difference is less than the second threshold, it is considered that the heart rate difference condition is met; otherwise, the heart rate difference condition is not met. If both the time interval condition and the heart rate difference condition are not met, or only one of them is met, the judgment process is terminated, and the next pulse wave is acquired until both the time interval condition and the heart rate difference condition are met, and it is judged whether the maximum pulse wave of the current measurement is similar to the maximum pulse wave of the previous measurement.

[0049] Then calculate the ratio coefficient of the current maximum pulse wave measured and the maximum pulse wave measured last time. If the ratio coefficient is not greater than the second threshold value, compare the waveform similarity between the current effective maximum amplitude pulse wave and the maximum pulse wave measured on the previous side. If the waveforms are similar, check whether the Gaussian fitting curves of the two adjacent detections meet the preset conditions.

[0050] For example, the maximum pulse waves of two blood pressure measurements are compared to see if they are similar. In the test of similarity matching, the method of calculating the correlation coefficient is adopted. In order to prevent the influence of the amplitude factor, an amplitude judgment mechanism is added before calculating the correlation coefficient.

[0051] Specifically, before calculating the correlation coefficient of the maximum pulse wave data, the amplitudes of the two maximum pulse waves are first compared, and the larger pulse wave amplitude is divided by the smaller pulse wave amplitude to obtain a ratio coefficient. If the ratio coefficient is greater than the second threshold TH_MAX_AMP_RATIO, the two pulse wave data are considered to be dissimilar, and the subsequent calculation of the correlation coefficient is not performed. If the amplitude ratio coefficient is less than or equal to the second threshold TH_MAX_AMP_RATIO, the calculation of the correlation coefficient is further performed.

[0052] Specifically, the correlation coefficient between the current maximum pulse wave data and the previous maximum pulse wave data is calculated to determine the waveform similarity, and the result is compared with a fixed threshold (such as a third threshold). If the result is less than the third threshold, it means that the two maximum pulse waves are not similar, and the judgment process ends and the next pulse wave acquisition is entered; otherwise, it means that the two maximum pulse waves are similar. The correlation coefficient is calculated by pulse wave data, which belongs to the prior art and will not be repeated.

[0053] Furthermore, when verifying whether the Gaussian fitting curves of two adjacent detections meet the preset conditions, the Gaussian fitting curve of the current measurement is calculated according to the pulse wave data of the current measurement, and the fitting similarity between the Gaussian fitting curve and the Gaussian fitting curve of the previous measurement is determined; that is, the fitting similarities of the Gaussian fitting curves of the two measurements are compared by the parameters obtained after fitting. Specifically, the fitting similarity between the Gaussian fitting curve and the Gaussian fitting curve of the previous measurement is determined based on the cross-validation of the pulse wave data.

[0054] It should be understood that Gaussian fitting is a fitting method that approximates a data point set through a Gaussian function. The shape of the pulse wave envelope in the oscillometric method used in blood pressure measurement is similar to a Gaussian curve, so Gaussian fitting is often used in curve fitting for blood pressure measurement. Figure 1 As shown, the curve in the figure is obtained by fitting the pulse wave pressure and amplitude data set through a Gaussian function.

[0055] The first-order Gaussian function is expressed as Where a represents the height of the curve, b represents the center position of the curve on the x-axis, and c represents the half-width information of the curve. The essence of Gaussian fitting is to find the parameters a, b and c so that the final fitting error is minimized. It is a prior art to complete Gaussian fitting by finding these three parameters, which will not be repeated here.

[0056] After the Gaussian fitting of the pulse wave pressure and amplitude data set is completed, the adjusted R-square (ARS) is calculated, and the formula is:

[0057] Among them, n is the number of pulse waves used for fitting, R 2 is the coefficient of determination (R-square), defined as: Among them, y i is the pulse wave amplitude for fitting, y predict is the amplitude calculated by Gaussian fitting, y mean is the average value of the pulse wave amplitude used for fitting. The values ​​of the correction determination coefficient ARS are mostly distributed between 0 and 1. The closer it is to 1, the better the fitting effect.

[0058] Therefore, after performing Gaussian fitting on the pulse wave pressure and amplitude dataset, three parameters of the Gaussian fitting and one parameter for evaluating the fitting effect can be obtained, for a total of four parameters. Then, through these four parameters and the cross-validation of the pulse wave pressure and amplitude dataset with the Gaussian curve, it is determined whether the two Gaussian fitting curves are similar.

[0059] Exemplarily, Gaussian fitting is performed on the currently measured pulse wave pressure and amplitude dataset to obtain the corresponding Gaussian function parameters a0, b0, and c0 (where the label 0 represents the current measurement, 1 represents the previous measurement, and the following are all represented in this way), and the adjusted coefficient of determination ARS0 is calculated. Next, the adjusted coefficient of determination ARS0 of the current measurement and the adjusted coefficient ARS1 of the previous measurement are respectively compared with the adjusted coefficient threshold TH_ARS. If both ARS0 > TH_ARS and ARS1 > TH_ARS are satisfied, the judgment process continues; otherwise, information indicating that the curves are not similar is output.

[0060] After the adjusted coefficient meets the requirements, the Gaussian parameters of the two measurements are examined to see if the differences of the three Gaussian parameters are all within the threshold range, that is, whether the three conditions |a0–a1|<TH_GAUSSIAN_A, |b0–b1|<TH_GAUSSIAN_B, and |c0–c1|<TH_GAUSSIAN_C are satisfied. If the differences of the three Gaussian parameters all meet the threshold range, the judgment process continues; otherwise, information indicating that the curves are not similar is output.

[0061] After the Gaussian fitting parameters meet the requirements, cross-validation is performed on the pulse wave pressure and amplitude datasets of the two measurements in combination with the Gaussian fitting curve to see if they meet the requirements. That is, the pulse wave pressure and amplitude dataset of the current measurement is substituted into the Gaussian function obtained from the previous measurement to check if the difference is within the threshold range; at the same time, the pulse wave pressure and amplitude dataset of the previous measurement is substituted into the Gaussian function obtained from the current measurement to check if the difference is within the threshold range.

[0062] In some embodiments, the pressure values corresponding to all the currently measured pulse waves can be substituted into the Gaussian function of the previous measurement to obtain the first amplitude value of the pulse wave, and the pressure values corresponding to all the pulse waves of the previous measurement can be substituted into the Gaussian function of the current measurement to obtain the second amplitude value of the pulse wave.

[0063] The difference between the first amplitude value and the corresponding amplitude value of the previous measurement is used to obtain the first absolute value, and the difference between the second amplitude value and the corresponding amplitude value of the current measurement is used to obtain the second absolute value. If both the first absolute value and the second absolute value are less than the third threshold, it indicates that the fitting degree similarity between the Gaussian fitting curve and the Gaussian fitting curve of the previous measurement is similar, and the currently measured pulse wave data meets the cuff deflation condition.

[0064] Exemplarily, substitute the pressure value corresponding to the currently measured pulse wave into the Gaussian function of the previous measurement, calculate an amplitude value based on the Gaussian function, take the first absolute value after taking the difference between the calculated amplitude value and the measured pulse wave amplitude value, and compare whether the first absolute value is less than the third threshold.

[0065] Specifically, sequentially traverse the pulse wave pressure and amplitude data set obtained from the current measurement, expressed as: (x1, y1), (x2, y2), …, (xn, yn), where x is the abscissa representing the pressure value corresponding to the pulse wave, y is the ordinate representing the pulse wave amplitude value, and the numbers 1 to n represent the pulse wave serial numbers, with a total of n pulse waves. For each pulse wave, without loss of generality, it is represented by i, that is, (xi, yi), and the following comparison is performed to check whether the requirements are met:

[0066] |yi – f(xi|a1 b1 c1)| < TH_ACROSS_AMP;

[0067] Among them, yi represents the amplitude of the currently measured pulse wave, and f(xi|a1 b1 c1) represents the value obtained by substituting xi into the Gaussian function with a1, b1, and c1 as parameters, that is, substituting the pressure value corresponding to the currently measured pulse wave into the Gaussian function obtained from the previous measurement to calculate an amplitude value. Perform the above comparison on all the pulse wave pressure and amplitude data sets obtained from the current measurement in sequence. If all the data sets meet the condition that the absolute value of the difference is less than the threshold after verification, it is considered that the verification of the current pulse wave pressure and amplitude data set and the Gaussian function of the previous measurement passes, otherwise it is considered not to pass.

[0068] The method for verifying the previous measured pulse wave pressure and amplitude data set with the Gaussian function of the current measurement is similar, and the verification formula is:

[0069] |yi – f(xi|a0 b0 c0)| < TH_ACROSS_AMP; where yi represents the amplitude of the previously measured pulse wave, and f(xi|a0 b0 c0) represents the value obtained by substituting xi into the Gaussian function with a0, b0, and c0 as parameters.

[0070] Substitute the pressure value corresponding to the previously measured pulse wave into the Gaussian function of the current measurement, calculate an amplitude value based on the Gaussian function, take the second absolute value after taking the difference between the calculated amplitude value and the measured pulse wave amplitude value, and compare whether the second absolute value is less than the third threshold.

[0071] If the cross-verification of the two measurements passes, that is, both the first absolute value and the second absolute value are less than the third threshold, it is considered that the Gaussian curves of the two measurements are similar; if neither of the two verifications passes, or only one verification passes, it is considered that the Gaussian curves are not similar.

[0072] If the Gaussian fitting curves are not similar, the judgment process ends and the next pulse wave acquisition is entered. Otherwise, it is considered to meet the fast acquisition logic and the output meets all deflation conditions. At this time, the deflation valve of the cuff can be controlled to open and deflate completely, ending the acquisition. The appropriate fitting algorithm is selected based on the acquired data to calculate the blood pressure and output the final blood pressure value.

[0073] After the current measurement is completed, the information of the previous measurement, including the measurement time point, heart rate, maximum pulse wave information, Gaussian fitting parameters, and pulse wave pressure and amplitude data sets, is updated to the information of the current measurement.

[0074] The present invention determines whether the information obtained by the current measurement meets the blood pressure calculation requirements by comparing the time interval and heart rate difference between the current measurement and the previous measurement, the maximum pulse wave fitting similarity, and the Gaussian fitting similarity of the pulse wave pressure and amplitude data sets. If the requirements for blood pressure calculation are met, it is not necessary to collect all the pulse wave information, and all the air is directly deflated, and the blood pressure value is calculated using the current information to complete the rapid measurement of blood pressure.

[0075] See also Figure 3 The present invention also provides a rapid measurement device for dynamic blood pressure monitoring, comprising:

[0076] The acquisition module 31 is used to acquire the oscillation wave signal to obtain the pulse wave data of two consecutive measurements, wherein the pulse wave data of two consecutive measurements include the pulse wave data of the current measurement and the pulse wave data of the previous measurement.

[0077] The processing module 32 is used to determine whether the cuff deflation conditions are met based on the pulse wave data of two adjacent measurements, and the cuff deflation conditions include: the time interval between two adjacent detections, the heart rate difference between two adjacent detections, the maximum pulse wave similarity between two adjacent detections, and whether the fitting curves of two adjacent detections meet the preset conditions.

[0078] The control module 33 is used to control the cuff to deflate if the cuff deflation condition is met, and output the blood pressure value according to the pulse wave data.

[0079] For the description of the rapid measurement device for dynamic blood pressure monitoring, please refer to the rapid measurement method for dynamic blood pressure monitoring, which will not be repeated here.

[0080] The present invention also provides an electronic device, comprising:

[0081] At least one processor; and at least one memory in communication with the processor, wherein: the memory stores program instructions that can be executed by the processor, and the processor calls the program instructions to execute the above-mentioned rapid measurement method for dynamic blood pressure monitoring.

[0082] The present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the rapid measurement method for dynamic blood pressure monitoring is implemented.

[0083] It can be understood that computer-readable storage media may include: any entity or device capable of carrying a computer program, recording media, USB flash drives, mobile hard disks, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media, etc. A computer program includes computer program code. The computer program code may be in source code form, object code form, executable file, or some intermediate form, etc. A computer-readable storage medium may include: any entity or device capable of carrying a computer program code, recording media, USB flash drives, mobile hard disks, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media, etc.

[0084] In certain embodiments of the present invention, the device may include a controller, which is a single-chip microcomputer chip that integrates a processor, a memory, a communication module, etc. The processor may refer to the processor included in the controller. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc.

[0085] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0086] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0087] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A rapid measurement method for dynamic blood pressure monitoring, characterized in that: include: Collecting the oscillation wave signal to obtain pulse wave data of two consecutive measurements, wherein the pulse wave data of two consecutive measurements include the pulse wave data of the current measurement and the pulse wave data of the previous measurement; Determining whether the cuff deflation condition is met according to the pulse wave data of the two adjacent measurements, wherein the cuff deflation condition includes: the time interval between two adjacent detections, the heart rate difference between two adjacent detections, the maximum pulse wave similarity between two adjacent detections, and whether the fitting curves of two adjacent detections meet the preset conditions; If the cuff deflation conditions are met, the cuff is controlled to deflate and the blood pressure value is output based on the currently measured pulse wave data.

2. The rapid measurement method for dynamic blood pressure monitoring according to claim 1, characterized in that: The determining whether the cuff deflation condition is met according to the pulse wave data of the two consecutive measurements includes: If the time interval between two adjacent detections meets the time threshold and if the heart rate difference between two adjacent detections is less than the first threshold, the maximum pulse wave similarity of the two adjacent detections is determined. If the maximum pulse waves of the two adjacent detections are similar, it is checked whether the Gaussian fitting curves of the two adjacent detections meet the preset conditions. If they meet the preset conditions, the currently measured pulse wave data meets the cuff deflation conditions.

3. The rapid measurement method for dynamic blood pressure monitoring according to claim 2, characterized in that: The pulse wave data includes a pulse wave pressure and amplitude data set; if the maximum pulse waves of two adjacent detections are similar, then checking whether the Gaussian fitting curves of the two adjacent detections meet the preset conditions also includes: A Gaussian fitting curve of a current measurement is calculated according to the pulse wave data, and a fitting similarity between the Gaussian fitting curve and a Gaussian fitting curve of a previous measurement is determined based on cross-validation of the pulse wave data.

4. The rapid measurement method for dynamic blood pressure monitoring according to claim 3, characterized in that: The cross-validation based on the pulse wave data determines the fitting similarity between the Gaussian fitting curve and the Gaussian fitting curve of the previous measurement, including: Substitute the pressure values ​​corresponding to all the currently measured pulse waves into the Gaussian function of the previous measurement to obtain the first amplitude value of the pulse wave, and substitute the pressure values ​​corresponding to all the previously measured pulse waves into the Gaussian function of the current measurement to obtain the second amplitude value of the pulse wave; Subtracting the first amplitude value from the corresponding amplitude value measured on the previous side to obtain a first absolute value, and subtracting the second amplitude value from the corresponding amplitude value measured currently to obtain a second absolute value; If the first absolute value and the second absolute value are both smaller than the third threshold, it indicates that the Gaussian fitting curve has a similar fitting degree to the Gaussian fitting curve of the previous measurement, and the currently measured pulse wave data meets the cuff deflation condition.

5. The rapid measurement method for dynamic blood pressure monitoring according to claim 2, characterized in that: The determining whether the cuff deflation condition is met according to the pulse wave data of the two consecutive measurements includes: The heart rate difference is obtained by subtracting the current heart rate value measured from the heart rate value measured last time and taking the absolute value of the difference, and the heart rate difference is compared with a first threshold; if the heart rate difference is less than the first threshold, the current heart rate value is judged to be valid; wherein the time interval between the current measurement and the last measurement meets the time threshold.

6. The rapid measurement method for dynamic blood pressure monitoring according to claim 2, characterized in that: The step of judging whether the cuff deflation condition is met according to the pulse wave data of two consecutive measurements further includes: Calculating a ratio coefficient between the current maximum pulse wave measured and the previous maximum pulse wave measured, if the ratio coefficient is not greater than a second threshold, it indicates that the effective maximum amplitude pulse wave currently measured has appeared; Compare the waveform similarity between the effective maximum amplitude pulse wave currently measured and the maximum pulse wave measured on the previous side. If the waveforms are similar, check whether the Gaussian fitting curves of two adjacent tests meet the preset conditions.

7. The rapid measurement method for dynamic blood pressure monitoring according to any one of claims 1 to 6, characterized in that: The judging whether the cuff deflation condition is met according to the pulse wave data of the two adjacent measurements further includes: determining a maximum pulse wave amplitude value measured, and updating the maximum pulse wave amplitude value to a currently measured maximum pulse wave amplitude value.

8. A rapid measurement device for dynamic blood pressure monitoring, characterized in that: include: An acquisition module, used for acquiring an oscillation wave signal to obtain pulse wave data of two consecutive measurements, wherein the pulse wave data of two consecutive measurements include the pulse wave data of the current measurement and the pulse wave data of the previous measurement; A processing module, used for judging whether the cuff deflation condition is met according to the pulse wave data of two adjacent measurements, wherein the cuff deflation condition includes: the time interval between two adjacent detections, the heart rate difference between two adjacent detections, the maximum pulse wave similarity between two adjacent detections, and whether the fitting curves of two adjacent detections meet the preset conditions; The control module is used to control the cuff to deflate if the cuff deflation condition is met, and output the blood pressure value according to the pulse wave data.

9. An electronic device, characterized in that: include: at least one processor; And at least one memory communicatively connected to the processor, wherein: the memory stores program instructions executable by the processor, and the processor calls the program instructions to execute the rapid measurement method for dynamic blood pressure monitoring as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a computer, the rapid measurement method for dynamic blood pressure monitoring according to any one of claims 1 to 7 is executed.

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