Rapid measurement methods, devices, equipment and media for ambulatory blood pressure monitoring

Abstract

This invention discloses a rapid measurement method, device, equipment, and medium for dynamic blood pressure monitoring. The method includes acquiring pulse wave data from two consecutive measurements by collecting oscillating wave signals. The pulse wave data from the two consecutive measurements includes the current pulse wave data and the pulse wave data from the previous measurement. Based on the pulse wave data from the two consecutive measurements, it is determined whether the cuff deflation conditions are met. The cuff deflation conditions include: the time interval between the two consecutive measurements, the heart rate difference between the two consecutive measurements, the maximum pulse wave similarity between the two consecutive measurements, and whether the fitted curve of the two consecutive measurements meets the preset conditions. If the cuff deflation conditions are met, the cuff is deflated, and the blood pressure value is output based on the currently measured pulse wave data. This invention can reduce the acquisition time and avoid emotional interference to the user caused by long acquisition times.

Description

Technical Field

[0001] This invention relates to the field of blood pressure monitoring, and more particularly to rapid measurement methods, devices, equipment, and media for ambulatory blood pressure monitoring. Background Technology

[0002] Blood pressure is an important physiological parameter that reflects the functional status of the heart and blood vessels. It is a crucial basis for clinical diagnosis, monitoring treatment effectiveness, and prognosis. Ambulatory blood pressure monitoring (ABPM) is a technique that uses an ambulatory blood pressure recorder to continuously monitor blood pressure for 24 hours without interfering with the patient's daily activities. The recorder tracks and records blood pressure at set time intervals.

[0003] The oscillometric method, also known as the oscillation method, is a widely used blood pressure measurement technique in various clinical monitors and electronic blood pressure monitors. Its principle is as follows: during the inflation and deflation of a cuff, as the cuff pressure decreases, a pressure oscillation wave (also called a pulse wave) appears within the cuff. The amplitude of the oscillation wave is extracted, and systolic and diastolic blood pressure are obtained through techniques such as curve fitting.

[0004] In oscillometric blood pressure measurement using curve fitting, acquiring numerous pulse waves at different pressures is necessary to ensure the fitted curve closely approximates actual blood pressure changes. This results in prolonged acquisition time, causing user discomfort and potentially leading to anxiety and other emotional interference, ultimately resulting in inaccurate blood pressure measurements. In scenarios requiring continuous or multiple measurements of the same user, such as ambulatory blood pressure monitoring, repeated measurements exacerbate user discomfort. Therefore, for continuous or multiple blood pressure measurements, a rapid detection method is needed that minimizes detection time while maintaining accuracy, thereby reducing user discomfort. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a rapid measurement method, device, equipment, and medium for dynamic blood pressure monitoring, which can reduce data acquisition time and avoid emotional interference to users caused by long acquisition times.

[0006] A first aspect of the present invention provides a rapid measurement method for dynamic blood pressure monitoring, comprising: acquiring pulse wave data from two adjacent measurements by collecting oscillating wave signals, wherein the pulse wave data from the two adjacent measurements includes the pulse wave data of the current measurement and the pulse wave data of the previous measurement; determining whether the cuff deflation conditions are met based on the pulse wave data from the two adjacent measurements, wherein the cuff deflation conditions include: the time interval between the two adjacent measurements, the heart rate difference between the two adjacent measurements, the maximum pulse wave similarity between the two adjacent measurements, and whether the fitted curve of the two adjacent measurements meets the preset conditions; if the cuff deflation conditions are met, controlling the cuff to deflate, and outputting a blood pressure value based on the pulse wave data.

[0007] In an optional implementation, determining whether the cuff deflation condition is met based on the pulse wave data from two consecutive measurements includes:

[0008] If the time interval between two adjacent tests meets the time threshold and the heart rate difference between two adjacent tests is less than the first threshold, then the similarity of the maximum pulse wave between the two adjacent tests is determined. If the maximum pulse wave between the two adjacent tests is similar, then the Gaussian fitting curve between the two adjacent tests is checked to see if it meets the preset conditions. If it meets the preset conditions, then the pulse wave data measured at the moment meets the cuff deflation conditions.

[0009] In one optional implementation, the pulse wave data includes pulse wave pressure and amplitude datasets; the step of verifying whether the Gaussian fitting curves of two adjacent detections meet preset conditions if the maximum pulse waves of two adjacent detections are similar further includes:

[0010] The Gaussian fitting curve of the current measurement is calculated based on the pulse wave data, and the 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.

[0011] In one optional implementation, the cross-validation based on pulse wave data to determine the similarity between the Gaussian fitted curve and the previously measured Gaussian fitted curve includes:

[0012] Substitute the pressure values ​​corresponding to all current 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 previous pulse waves into the Gaussian function of the current measurement to obtain the second amplitude value of the pulse wave.

[0013] The first absolute value is obtained by subtracting the first amplitude value from the corresponding amplitude value measured on the previous side, and the second absolute value is obtained by subtracting the second amplitude value from the corresponding amplitude value measured at the current time.

[0014] If both the first absolute value and the second absolute value are less than the third threshold, it indicates that the Gaussian fitting curve is similar in fit to the Gaussian fitting curve of the previous measurement, and the pulse wave data of the current measurement meets the cuff deflation conditions.

[0015] In an optional implementation, determining whether the cuff deflation condition is met based on the pulse wave data from two consecutive measurements includes:

[0016] The heart rate difference is obtained by subtracting the current heart rate value from the previous heart rate value and taking the absolute value of the difference. The heart rate difference is then compared with a first threshold. If the heart rate difference is less than the first threshold, the current heart rate value is considered valid. The time interval between the current measurement and the previous measurement meets a time threshold.

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

[0018] Calculate the ratio coefficient between the current maximum pulse wave and the previous maximum pulse wave. If the ratio coefficient is not greater than the second threshold, it indicates that the current effective maximum amplitude pulse wave has appeared.

[0019] Compare the waveforms of the current effective maximum amplitude pulse wave with the maximum pulse wave measured on the previous side. If the waveforms are similar, verify whether the Gaussian fitting curves of the two adjacent detections meet the preset conditions.

[0020] In an optional implementation, the step of determining whether the cuff deflation condition is met based on the pulse wave data of the two adjacent measurements further includes: determining the maximum measured pulse wave amplitude value and updating the maximum measured pulse wave amplitude value to the 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] The acquisition module is used to acquire oscillating wave signals and obtain pulse wave data from two consecutive measurements. The pulse wave data from two consecutive measurements includes the pulse wave data of the current measurement and the pulse wave data of the previous measurement.

[0023] The processing module is used to determine whether the cuff deflation conditions are met based on the pulse wave data of the two adjacent measurements. The cuff deflation conditions include: the time interval between the two adjacent measurements, the heart rate difference between the two adjacent measurements, the maximum pulse wave similarity between the two adjacent measurements, and whether the fitted curves of the two adjacent measurements meet the preset conditions.

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

[0025] A third aspect of the present invention provides 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 invokes the program instructions to perform a rapid measurement method for dynamic blood pressure monitoring as described in the first aspect 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 the computer program, when executed by a computer, performs a rapid measurement method for dynamic blood pressure monitoring as described in the first aspect of the present invention.

[0028] During blood pressure measurement, this invention continuously compares relevant parameters between the current and previous measurements. If certain conditions are met, the two measurements are considered to indicate that the blood pressure changes of the same individual are not significant. The blood pressure measurement result can be directly calculated based on the acquired parameters, thus achieving rapid blood pressure measurement, reducing data collection time, and avoiding emotional interference to the user caused by long collection times. Attached Figure Description

[0029] Figure 1 A schematic diagram of blood pressure measurement using pulse wave curve fitting.

[0030] Figure 2 This is a flowchart illustrating a rapid measurement method for dynamic blood pressure monitoring according to an embodiment of the present invention.

[0031] Figure 3 This is a schematic diagram of a rapid measurement device for dynamic blood pressure monitoring according to an embodiment of the present invention. Detailed Implementation

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

[0033] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0034] Figure 1This diagram illustrates blood pressure measurement using pulse wave curve fitting. During blood pressure measurement, the pulse wave is extracted as the cuff pressure decreases, obtaining the corresponding data of pulse wave amplitude and cuff pressure. A curve is then fitted to the pressure and amplitude data. The pressure corresponding to the highest point on the curve is the mean blood pressure; the pressure corresponding to a certain percentage decrease to the left of the mean blood pressure is the systolic pressure; and the pressure corresponding to a certain percentage decrease to the right of the mean blood pressure is the diastolic pressure. Measuring blood pressure using pulse wave curve fitting is an existing technique and will not be elaborated upon here.

[0035] like Figure 1 As shown, to obtain more accurate diastolic blood pressure information, after acquiring the highest amplitude pulse wave, multiple smaller amplitude pulse waves need to be acquired, which will increase the acquisition time, especially when using a step-down deflation method. In scenarios such as ambulatory blood pressure monitoring that require continuous or multiple measurements on the same user, the blood pressure of the same individual may not change significantly within a short period of time, which makes rapid blood pressure measurement possible.

[0036] In the process of blood pressure measurement, this invention continuously compares the relevant parameters of the current measurement with those of the previous measurement. If certain conditions are met, the two measurements are considered to be consistent with the measurement of blood pressure changes of the same individual with little variation. The blood pressure measurement result is directly calculated based on the acquired parameters, thereby achieving rapid detection of blood pressure.

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

[0038] S100: Acquire oscillating wave signals to obtain pulse wave data from two consecutive measurements. The pulse wave data includes pulse wave pressure and amplitude datasets.

[0039] S200: Determine whether the cuff deflation conditions are met based on the pulse wave data of the two adjacent measurements. The cuff deflation conditions include: the time interval between the two adjacent measurements, the heart rate difference between the two adjacent measurements, the maximum pulse wave similarity between the two adjacent measurements, and whether the fitted curves of the two adjacent measurements meet the preset conditions.

[0040] S300: If the cuff deflation conditions are met, control the cuff to deflate and output the blood pressure value based on the pulse wave data.

[0041] Analyzing the acquired oscillating wave signals to obtain pulse waves is a prior art technique and will not be elaborated upon here. In some embodiments, after acquiring a pulse wave, it is determined whether the current monitoring meets the condition for complete deflation. If the condition is met, the cuff is fully deflated, the acquisition ends, and the final blood pressure measurement result is output; if the condition is not met, it is further determined whether the measurement can be terminated under normal measurement logic. If the measurement can be terminated under normal measurement logic, the cuff is fully deflated, the acquisition ends, and the result is output; otherwise, the oscillating wave signal is acquired to obtain the next pulse wave, and this process is repeated until the acquisition ends.

[0042] Specifically, this can be determined by checking whether the monitored pulse wave data meets the cuff deflation conditions. First, determine the maximum measured pulse wave amplitude value, and update the maximum measured pulse wave amplitude value to the current maximum measured pulse wave amplitude value.

[0043] After acquiring a pulse wave, it is determined whether the amplitude value of the current pulse wave 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 amplitude value of the current pulse wave is greater than or equal to the maximum pulse wave amplitude value, the currently monitored pulse wave data is updated with the information of the maximum pulse wave.

[0044] Among them, the pulse wave data is an oscillating wave signal at 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 judged.

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

[0046] Then, the time interval between two adjacent measurements, heart rate, maximum pulse similarity, and Gaussian fitting curve fitting similarity are judged sequentially. If the time interval between two adjacent measurements meets the time threshold and the heart rate difference between two adjacent measurements is less than the first threshold, the maximum pulse wave similarity between the two adjacent measurements is judged. If the maximum pulse waves between two adjacent measurements are similar, the Gaussian fitting curve between the two adjacent measurements is checked to see if it meets the preset conditions. If it meets the preset conditions, the currently measured pulse wave data meets the cuff deflation conditions.

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

[0048] Subtract the previous measurement time from the current measurement time to obtain the time interval between the two measurements. Check if this time interval is less than the first threshold TH_TIME. If the time interval is less than the first threshold, the time interval condition is considered met; otherwise, the time interval condition is not met. Then, compare the heart rate. Obtaining the heart rate through the pulse wave interval during blood pressure measurement is existing technology and will not be elaborated here. Calculate the difference between the current and previous heart rates and take the absolute value as the heart rate difference value. Compare this heart rate difference value with the second threshold TH_HR. If the heart rate difference value is less than the second threshold, the heart rate difference condition is considered met; otherwise, the heart rate difference condition is not met. If neither the time interval condition nor the heart rate difference condition is met, or only one of them is met, the judgment process ends, and the next pulse wave acquisition begins, until both the time interval condition and the heart rate difference condition are met. Finally, determine whether the maximum pulse wave measured in the current measurement is similar to the maximum pulse wave measured in the previous measurement.

[0049] Then, the ratio coefficient between the current maximum pulse wave and the previous maximum pulse wave is calculated. If the ratio coefficient is not greater than the second threshold, the waveform similarity between the current effective maximum amplitude pulse wave and the previous maximum pulse wave is compared. If the waveforms are similar, the Gaussian fitting curves of two adjacent detections are checked to see if they meet the preset conditions.

[0050] For example, we compare the similarity of the maximum pulse waves from two blood pressure measurements. In the similarity matching test, we use a correlation coefficient calculation method. To prevent the influence of amplitude factors, 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. 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 dissimilar, and the subsequent correlation coefficient calculation is not performed. If the amplitude ratio coefficient is less than or equal to the second threshold TH_MAX_AMP_RATIO, the correlation coefficient is then calculated.

[0052] Specifically, the correlation coefficient between the currently measured maximum pulse wave data and the previously measured maximum pulse wave data is calculated to determine waveform similarity. The result is then compared with a fixed threshold (e.g., a third threshold). If the result is less than the third threshold, it indicates that the two maximum pulse waves are not similar, and the judgment process ends, proceeding to the acquisition of the next pulse wave; otherwise, it indicates that the two maximum pulse waves are similar. The correlation coefficient is calculated from the pulse wave data, which is existing technology and will not be elaborated further.

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

[0054] It should be understood that Gaussian fitting is a fitting method that approximates a set of data points using a Gaussian function. The shape of the pulse wave envelope in the oscillometric method used for blood pressure measurement resembles a Gaussian curve; therefore, Gaussian fitting is commonly used in curve fitting for blood pressure measurement. For example... Figure 1 As shown in the figure, the curve is obtained by fitting the pulse wave pressure and amplitude dataset using 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 curve's half-width. The essence of Gaussian fitting is to find parameters a, b, and c that minimize the final fitting error. Finding these three parameters to perform Gaussian fitting is a current technique and will not be elaborated upon here.

[0056] After Gaussian fitting of the pulse wave pressure and amplitude dataset, the adjusted R-squared (ARS) is calculated using the following formula:

[0057] Where n is the number of pulse waves used for fitting, and R0 2 The coefficient of determination (R-square) is defined as: Among them, y i The pulse wave amplitude value for fitting, y predict The amplitude y is calculated using Gaussian fitting. mean This represents the average amplitude of the pulse waves used for fitting. The correction determination coefficient (ARS) values ​​mostly range from 0 to 1, with values ​​closer to 1 indicating a better fit.

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

[0060] After the adjusted coefficient meets the requirements, check the Gaussian parameters of the two measurements to see if the differences in 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 in the three Gaussian parameters all meet the threshold range, the judgment process continues; otherwise, output information indicating that the curves are not similar.

[0061] After the Gaussian fitting parameters meet the requirements, perform cross-validation 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, substitute the pulse wave pressure and amplitude dataset of the current measurement into the Gaussian function obtained from the previous measurement to check if the difference is within the threshold range; at the same time, substitute the pulse wave pressure and amplitude dataset of the previous measurement 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 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 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] Take the difference between the first amplitude value and the corresponding amplitude value of the previous measurement to obtain the first absolute value, and take the difference between the second amplitude value and the corresponding amplitude value of the current measurement 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 this 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 made 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, 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. Sequentially perform the above comparison on all the pulse wave pressure and amplitude data sets of the current measurement. 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 pulse wave pressure and amplitude data set of the current measurement and the Gaussian function of the previous measurement passes, otherwise it is considered not to pass.

[0068] The method for verifying the pulse wave pressure and amplitude data set of the previous measurement 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 pulse wave of the previous measurement, 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 pulse wave of the previous measurement 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 this 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 fitted curves are dissimilar, the judgment process ends and the next pulse wave is acquired. Otherwise, it is considered to meet the fast acquisition logic, and the output shows that the full deflation condition is met. At this point, the cuff deflation valve can be controlled to open fully deflate the cuff, and the acquisition ends. A suitable fitting algorithm is selected based on the acquired data to calculate the blood pressure, and the final blood pressure value is output.

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

[0074] This invention determines whether the information obtained from the current measurement meets the requirements for blood pressure calculation by comparing the time interval and heart rate difference between the current and previous measurements, the maximum pulse wave fitting similarity, and the Gaussian fitting similarity between the pulse wave pressure and amplitude datasets. If the requirements are met, it is not necessary to collect all pulse wave information; all air can be released directly, and the blood pressure value can be calculated using the current information, thus completing a rapid blood pressure measurement.

[0075] Please see 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 oscillation wave signals to obtain pulse wave data from two adjacent measurements. The pulse wave data from two adjacent measurements includes 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 the two adjacent measurements. The cuff deflation conditions include: the time interval between the two adjacent measurements, the heart rate difference between the two adjacent measurements, the maximum pulse wave similarity between the two adjacent measurements, and whether the fitted curve of the two adjacent measurements meets the preset conditions.

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

[0079] For a description of the rapid measurement device for ambulatory blood pressure monitoring, please refer to the rapid measurement method for ambulatory 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 communicatively connected to the processor, wherein the memory stores program instructions executable by the processor, and the processor can execute the above-described rapid measurement method for dynamic blood pressure monitoring by invoking the program instructions.

[0082] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described rapid measurement method for dynamic blood pressure monitoring.

[0083] It is understood that computer-readable storage media can include: any entity or device capable of carrying computer programs, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media, etc. Computer programs include computer program code. Computer program code can be in the form of source code, object code, executable files, or certain intermediate forms, etc. Computer-readable storage media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), and software distribution media, etc.

[0084] In some embodiments of the present invention, the device may include a controller, which is a microcontroller chip integrating a processor, memory, 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 (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0085] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing a particular logical function or process, and the scope of the preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as will be understood by those skilled in the art to which embodiments of the invention pertain.

[0086] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0087] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A rapid measurement method for ambulatory blood pressure monitoring, characterized in that, include: The oscillating wave signal is collected to obtain pulse wave data from two consecutive measurements. The pulse wave data from two consecutive measurements includes the pulse wave data from the current measurement and the pulse wave data from the previous measurement. The determination of whether the cuff deflation conditions are met is based on the pulse wave data of two adjacent measurements. The cuff deflation conditions include: the time interval between two adjacent measurements, the heart rate difference between two adjacent measurements, the maximum pulse wave similarity between two adjacent measurements, and whether the fitted curves of two adjacent measurements meet the preset conditions. If the conditions for cuff deflation are met, the cuff will be deflated, and the blood pressure value will be output based on the currently measured pulse wave data. The step of determining whether the cuff deflation conditions are met based on the pulse wave data from two consecutive measurements includes: If the time interval between two adjacent tests meets the time threshold and the heart rate difference between two adjacent tests is less than the first threshold, then the similarity of the maximum pulse wave between the two adjacent tests is determined. If the maximum pulse wave between the two adjacent tests is similar, then the Gaussian fitting curve between the two adjacent tests is checked to see if it meets the preset conditions. If it meets the preset conditions, then the pulse wave data measured at the moment meets the cuff deflation conditions. The pulse wave data includes pulse wave pressure and amplitude datasets; the step of verifying whether the Gaussian fitting curves of two adjacent detections meet preset conditions if the maximum pulse waves of two adjacent detections are similar also includes: The Gaussian fitting curve of the current measurement is calculated based on the pulse wave data, and the 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. The step of determining whether the cuff deflation conditions are met based on the pulse wave data from two consecutive measurements includes: The heart rate difference is obtained by subtracting the current heart rate value from the previous heart rate value and taking the absolute value of the difference. The heart rate difference is then compared with a first threshold. If the heart rate difference is less than the first threshold, the current heart rate value is considered valid. The time interval between the current measurement and the previous measurement meets a time threshold. The step of determining whether the cuff deflation conditions are met based on the pulse wave data from two consecutive measurements also includes: Calculate the ratio coefficient between the current maximum pulse wave and the previous maximum pulse wave. If the ratio coefficient is not greater than the second threshold, it indicates that the current effective maximum amplitude pulse wave has appeared. Compare the waveform similarity between the current effective maximum amplitude pulse wave and the previous maximum pulse wave. If the waveforms are similar, verify whether the Gaussian fitting curves of two adjacent detections meet the preset conditions.

2. The rapid measurement method for dynamic blood pressure monitoring according to claim 1, characterized in that, The cross-validation based on pulse wave data to determine the similarity between the Gaussian fitted curve and the previously measured Gaussian fitted curve includes: Substitute the pressure values ​​corresponding to all current 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 previous pulse waves into the Gaussian function of the current measurement to obtain the second amplitude value of the pulse wave. The first absolute value is obtained by subtracting the first amplitude value from the corresponding amplitude value of the previous measurement, and the second absolute value is obtained by subtracting the second amplitude value from the corresponding amplitude value of the current measurement. If both the first absolute value and the second absolute value are less than the third threshold, it indicates that the Gaussian fitting curve is similar to the Gaussian fitting curve of the previous measurement, and the pulse wave data of the current measurement meets the cuff deflation condition.

3. The rapid measurement method for dynamic blood pressure monitoring according to any one of claims 1 to 2, characterized in that, The step of determining whether the cuff deflation condition is met based on the pulse wave data of the two adjacent measurements further includes: determining the maximum measured pulse wave amplitude value and updating the maximum measured pulse wave amplitude value to the currently measured maximum pulse wave amplitude value.

4. A rapid measurement device for ambulatory blood pressure monitoring, used to implement the rapid measurement method for ambulatory blood pressure monitoring as described in claim 1, characterized in that, include: The acquisition module is used to acquire oscillating wave signals and obtain pulse wave data from two consecutive measurements. The pulse wave data from two consecutive measurements includes the pulse wave data of the current measurement and the pulse wave data of the previous measurement. The processing module is used to determine whether the cuff deflation conditions are met based on the pulse wave data of the two adjacent measurements. The cuff deflation conditions include: the time interval between the two adjacent measurements, the heart rate difference between the two adjacent measurements, the maximum pulse wave similarity between the two adjacent measurements, and whether the fitted curves of the two adjacent measurements meet the preset conditions. The control module is used to control the cuff to deflate if the cuff deflation conditions are met, and to output the blood pressure value based on the pulse wave data.

5. 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 invokes the program instructions to perform a rapid measurement method for dynamic blood pressure monitoring as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a computer, performs a rapid measurement method for dynamic blood pressure monitoring as described in any one of claims 1 to 3.

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