Blood pressure measurement method, system and equipment by oscillography and storage medium

Abstract

The invention relates to an oscillography blood pressure measurement method, system and device and a storage medium, and the method comprises the steps: controlling a cuff to be inflated to a first preset pressure, judging whether a user state accords with a measurement condition or not based on a collected first pressure signal and a first limb dynamic signal of a user, and if yes, judging whether the user state accords with the measurement condition; if yes, controlling the cuff to inflate to a second preset pressure and then executing deflation measurement; in the deflation measurement process, a second pressure signal and a second limb dynamic signal of the user are synchronously collected, a burst artifact time period is determined based on the second limb dynamic signal, the second pressure signal of the burst artifact time period is preprocessed based on a dynamic gating strategy, the obtained preprocessed pressure signal is converted into an envelope curve, and the envelope curve is subjected to deflation measurement; calculating a blood pressure value; compared with the prior art, according to the technical scheme, through state admission judgment before measurement and dynamic processing of sudden artifacts in measurement, non-resting state interference is avoided, the pressure signal purity can be improved, and then the accuracy and reliability of blood pressure measurement are improved.

Description

Technical Field

[0001] This application relates to the technical field of blood pressure measurement, and more particularly to an oscillometric blood pressure measurement method, system, device, and storage medium. Background Technology

[0002] As a core physiological indicator for assessing cardiovascular health, blood pressure is directly related to the early diagnosis of hypertension, the adjustment of treatment plans, and the effectiveness of daily health management. It plays an irreplaceable role in both clinical diagnosis and treatment and family health monitoring.

[0003] Currently, most electronic blood pressure monitors widely used in home and clinical settings employ the oscillometric measurement principle. This method involves collecting cuff pressure oscillation waves caused by arterial pulsation during cuff deflation and using the envelope characteristics of the oscillation waves to estimate systolic and diastolic blood pressure. It has the advantages of being easy to operate and non-invasive.

[0004] However, traditional oscillometric blood pressure measurement technology has two inherent drawbacks: First, it is blind to the measurement state: the device starts inflation measurement immediately after startup, and cannot identify whether the user is in a resting state. If the user is in a state of stress or muscle tension due to the white coat hypertension effect, the measured value will be significantly higher than the true baseline value, leading to misdiagnosis. Second, it is vulnerable to motion artifacts: the cuff pressure oscillation wave signal is extremely weak and is easily interfered with by arm movement, coughing, talking, etc. Existing back-end digital filtering or AI repair technology has limited effect when the artifact energy is strong, and it is easy to introduce signal distortion, which seriously affects the accuracy and reliability of the measurement. Summary of the Invention

[0005] This application provides an oscillometric blood pressure measurement method, system, device, and storage medium. By judging the state before measurement and dynamically processing sudden artifacts during measurement, it avoids interference from non-resting states, improves the purity of the pressure signal, and thus improves the accuracy and reliability of blood pressure measurement.

[0006] In a first aspect, this application provides an oscillometric blood pressure measurement method applicable to an oscillometric blood pressure measurement system including a cuff. The method includes: controlling the cuff to inflate to a first preset pressure; acquiring a user's first pressure signal and a first limb dynamic signal; determining whether the user's state meets the measurement conditions based on the first pressure signal and the first limb dynamic signal; if so, controlling the cuff to inflate to a second preset pressure and then performing deflation measurement; during the deflation measurement, simultaneously acquiring the user's second pressure signal and second limb dynamic signal; determining the sudden artifact period based on the second limb dynamic signal; preprocessing the second pressure signal during the sudden artifact period based on a dynamic gating strategy to obtain a preprocessed pressure signal; converting the preprocessed pressure signal into an envelope curve; and calculating the blood pressure value based on the envelope curve.

[0007] In one possible implementation, determining whether the user's state meets the measurement conditions based on the first pressure signal and the first limb dynamic signal specifically includes: performing multi-dimensional feature extraction on the first pressure signal and the first limb dynamic signal to obtain multi-dimensional state features; determining whether the multi-dimensional state features are within a preset multi-dimensional state feature range; if so, determining that the user's state meets the measurement conditions.

[0008] In one possible implementation, the step of extracting multidimensional features from the first pressure signal and the first limb dynamic signal to obtain multidimensional state features specifically includes: calculating the limb position angle based on the first limb dynamic signal and using the limb position angle as a position angle feature; performing spectral analysis on the first limb dynamic signal to calculate the energy ratio of a first energy in a first target frequency band and a second energy in a second target frequency band, and using the energy ratio as a muscle tension feature; calculating the real-time synthetic modulus of the first limb dynamic signal, calculating the variance of the real-time synthetic modulus within a preset time window, and using the variance as a physical stability feature; extracting a beat interval sequence from the first pressure signal, calculating a short-term heart rate variability index based on the beat interval sequence, and using the short-term heart rate variability index as an autonomic nervous system state feature; and integrating the position angle feature, the muscle tension feature, the physical stability feature, and the autonomic nervous system state feature to obtain multidimensional state features.

[0009] In one possible implementation, determining the sudden artifact period based on the second limb dynamic signal specifically includes: calculating the signal change rate of the second limb dynamic signal collected at the current moment in real time; setting a dynamic change rate threshold based on the second pressure signal collected at the current moment; comparing the signal change rate with the dynamic change rate threshold; and if the signal change rate is greater than the dynamic change rate threshold, determining the current moment as the sudden artifact period.

[0010] In one possible implementation, the preprocessing of the second pressure signal during the sudden artifact period based on the dynamic gating strategy to obtain the preprocessed pressure signal specifically includes: acquiring the acquisition time corresponding to each acquired second pressure signal; removing second pressure signals whose acquisition time falls within the sudden artifact period; and using all the remaining second pressure signals as the preprocessed pressure signal; or, when it is determined that the current time is the sudden artifact period, controlling the cuff to pause deflation to maintain constant pressure until the current time is not the sudden artifact period, and then resuming the deflation measurement process; acquiring the target second pressure signal when the current time is not the sudden artifact period, and using the target second pressure signal as the preprocessed pressure signal.

[0011] In one possible implementation, converting the preprocessed pressure signal into an envelope curve specifically includes: integrating the preprocessed pressure signal into a pressure signal sequence according to the acquisition time; determining whether the number of signals in the pressure signal sequence is the theoretical number of signals; if so, directly reconstructing the pressure signal sequence into an envelope curve; if the number of signals is not the theoretical number of signals, using a monotonic interpolation algorithm to interpolate the pressure signal sequence to obtain an interpolated pressure signal sequence, and reconstructing the interpolated pressure signal sequence into an envelope curve.

[0012] In one possible implementation, calculating the blood pressure value based on the envelope curve specifically includes: determining the maximum amplitude point on the envelope curve and taking the pressure value corresponding to the maximum amplitude point as the mean pressure; obtaining preset systolic pressure characteristic ratio and diastolic pressure characteristic ratio, and calculating the systolic pressure and diastolic pressure based on the mean pressure, the systolic pressure characteristic ratio and the diastolic pressure characteristic ratio.

[0013] Secondly, this application provides an oscillometric blood pressure measurement system, comprising: an airway control module, a sensing module, and a main control module; wherein, the airway control module includes a cuff; the main control module is connected to the airway control module and the sensing module respectively, and is configured to perform the oscillometric blood pressure measurement method as described in any of the above claims.

[0014] Thirdly, embodiments of this application also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0015] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the above-described method.

[0016] This application provides an oscillometric blood pressure measurement method, system, device, and storage medium, which has the following advantages compared with the prior art:

[0017] This method involves controlling the cuff to inflate to a first preset pressure, acquiring the user's first pressure signal and first limb dynamic signal, determining whether the user's state meets the measurement conditions based on the first pressure signal and the first limb dynamic signal, and if so, controlling the cuff to inflate to a second preset pressure and then performing deflation measurement; during the deflation measurement, simultaneously acquiring the user's second pressure signal and second limb dynamic signal, determining the sudden artifact period based on the second limb dynamic signal, preprocessing the second pressure signal during the sudden artifact period based on a dynamic gating strategy to obtain a preprocessed pressure signal; converting the preprocessed pressure signal into an envelope curve, and calculating blood pressure based on the envelope curve. Compared with existing technical solutions, the technical solution of this application establishes coupling between the cuff and the user's limb by inflating the cuff before measurement. It combines the collected first pressure signal and the first limb dynamic signal to determine whether the user is in a suitable measurement state. Formal measurement is only initiated when the state is qualified, effectively avoiding measurement deviations caused by stress, muscle tension, etc. During the deflation measurement process, two types of signals are collected simultaneously and sudden artifact periods are accurately identified. The pressure signal that is disturbed is preprocessed through a dynamic gating strategy to ensure the purity of the pressure signal used for calculation. Finally, the blood pressure value is calculated through a high-quality envelope curve, which comprehensively improves the accuracy, reliability and robustness of blood pressure measurement results. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] One or more embodiments are illustrated by way of example with reference numerals in the accompanying drawings. These illustrations do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are denoted as similar elements. Unless otherwise stated, the figures in the drawings are not to be limited by scale.

[0021] Figure 1 This is a schematic flowchart of an embodiment of the oscillometric blood pressure measurement method provided in this application;

[0022] Figure 2 This is a schematic diagram of an embodiment of an oscillometric blood pressure measurement system provided in this application;

[0023] Figure 3This is a schematic diagram of the airway control module structure of an embodiment of an oscillometric blood pressure measurement system provided in this application;

[0024] Figure 4 This is a schematic diagram of the sensor module structure of an embodiment of the oscillometric blood pressure measurement system provided in this application;

[0025] Figure 5 This is a schematic diagram of the main control module structure of an embodiment of the oscillometric blood pressure measurement system provided in this application;

[0026] Figure 6 This is a schematic diagram of the structure of a computer device provided in this application. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] The following disclosure provides numerous different embodiments or examples for implementing various structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0029] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0030] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0031] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0032] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determined" or "if [described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [described condition or event] is detected," or "in response to detection of [described condition or event]."

[0033] Example 1, see Figure 1 , Figure 1 This is a flowchart illustrating one embodiment of an oscillometric blood pressure measurement method provided in this application, applicable to oscillometric blood pressure measurement systems including cuffs, such as... Figure 1 As shown, the method includes steps 101-103, as detailed below:

[0034] Step 101: Control the cuff to inflate to the first preset pressure, collect the user's first pressure signal and first limb dynamic signal, and determine whether the user's state meets the measurement conditions based on the first pressure signal and the first limb dynamic signal. If so, control the cuff to inflate to the second preset pressure and then perform the deflation measurement.

[0035] In one embodiment, since the oscillometric blood pressure measurement system is equipped with an air pump and a rapid inflation valve, the main control unit of the system controls the valve opening of the air pump and the rapid inflation valve to inflate the cuff until the first preset pressure is reached.

[0036] In one embodiment, the oscillometric blood pressure measurement system is further provided with a sensing module, which can be built into the cuff.

[0037] In one embodiment, the first preset pressure is a low pressure value set before measurement to determine the user's state; preferably, the pressure range of the first preset pressure is 20-30 mmHg, based on which the first preset pressure only needs to fill the gap between the cuff and the arm, without blocking arterial blood flow; but it is sufficient to establish acoustic / vibration coupling between the sensor and the limb.

[0038] In one embodiment, the oscillometric blood pressure measurement system is further provided with a human-computer interaction module, and the human-computer interaction module is provided with a button for triggering blood pressure measurement of the user when pressed by the user.

[0039] In one embodiment, the acquisition of the first pressure signal and the first limb dynamic signal occurs during the measurement state access judgment stage before the formal high-pressure inflation measurement. After the user puts on the cuff and presses the start button, the system does not immediately start the formal measurement, but first controls the air pump to inflate the cuff to the first preset pressure. After the pressure stabilizes, the acquisition process is triggered. The acquisition process continues in this low-pressure state until the preset time window ends.

[0040] In one embodiment, the sensing module includes a pressure sensor and a triaxial accelerometer.

[0041] Specifically, the pressure sensor 2021 is a MEMS piezoresistive sensor, such as the Honeywell ABP series, with a range of 0-40kPa (0-300mmHg) and an accuracy of ±1%; its sampling rate is set to 100Hz.

[0042] Specifically, the triaxial accelerometer 2022 is a low-power triaxial accelerometer, such as ST LIS2DW12 or Bosch BMA400; its range is configured to ±2g, which is sufficient to capture micro-movements of the human body and has high resolution; its sampling rate is configured to 200Hz-500Hz, where the high sampling rate is configured to ensure that the high-frequency characteristics of muscle tremors and instantaneous impact signals can be captured.

[0043] In one embodiment, when the cuff is inflated to a first preset pressure, a first pressure signal within a preset time window is acquired based on the pressure sensor, and a first limb dynamic signal within the preset time window is acquired based on the triaxial accelerometer.

[0044] Specifically, the sensing module transmits the first pressure signal and the first limb dynamic signal it collects to the main control module.

[0045] Specifically, the first pressure signal is pressure fluctuation data, and the first limb dynamic signal is acceleration data.

[0046] Specifically, the preset time window is 5-10 seconds.

[0047] Preferably, the default preset time window is 5 seconds. If the system detects that the data is in a critically unstable state at the end of 5 seconds, such as excessive signal fluctuation or feature value close to the threshold, the acquisition time will be automatically extended, not exceeding 15 seconds, to ensure that enough effective data can be acquired for subsequent state feature extraction. During the acquisition process, the cuff maintains a constant first preset low pressure to avoid interference from pressure changes on signal acquisition. At the same time, the encapsulation design of the triaxial accelerometer can isolate noise such as cuff fabric friction, ensuring signal purity.

[0048] In one embodiment, when determining whether the user's state meets the measurement conditions based on the first pressure signal and the first limb dynamic signal, multi-dimensional state features are obtained by extracting multi-dimensional features from the first pressure signal and the first limb dynamic signal; it is then determined whether the multi-dimensional state features are within a preset multi-dimensional state feature range, and if so, the user's state is determined to meet the measurement conditions.

[0049] Specifically, the limb position angle is calculated based on the dynamic signal of the first limb, and the limb position angle is used as the position angle feature.

[0050] Specifically, when calculating the limb position angle based on the first limb dynamic signal, the x-axis acceleration component, y-axis acceleration component, and z-axis acceleration component of the first limb dynamic signal are input into the upper arm tilt angle calculation formula to obtain the upper arm tilt angle, and the upper arm tilt angle is used as the position angle feature. The upper arm tilt angle calculation formula is as follows:

[0051]

[0052] In the formula, Q is the upper arm tilt angle, x is the x-axis acceleration component, y is the y-axis acceleration component, and z is the z-axis acceleration component.

[0053] Specifically, the upper arm tilt angle is the pitch angle of the arm relative to the horizontal plane, used to determine whether the arm is at heart height.

[0054] Specifically, spectral analysis is performed on the dynamic signal of the first limb to calculate the energy ratio of the first energy in the first target frequency band and the second energy in the second target frequency band, and the energy ratio is used as a muscle tension feature.

[0055] Preferably, spectral analysis of the first limb dynamic signal refers to analyzing the z-axis acceleration component in the first limb dynamic signal using Fast Fourier Transform; the first target frequency band is 8-12Hz, and the second target frequency band is 0.5-20Hz.

[0056] Specifically, the first energy and the second energy are substituted into a preset ratio calculation formula to obtain the energy percentage. The ratio calculation formula is as follows: R = e / s, where R is the energy percentage, e is the first energy, and s is the second energy.

[0057] Specifically, the real-time synthetic modulus of the first limb dynamic signal is calculated, the variance of the real-time synthetic modulus within a preset time window is calculated, and the variance is used as a physical stability feature.

[0058] Specifically, when calculating the real-time synthetic modulus of the first limb dynamic signal, the x-axis acceleration component, y-axis acceleration component, and z-axis acceleration component of the first limb dynamic signal are first input into the modulus calculation formula to obtain the real-time synthetic modulus at time t. The modulus calculation formula is as follows: In the formula, M(t) is the real-time synthetic modulus at time t, x(t) is the x-axis acceleration component at time t, y(t) is the y-axis acceleration component at time t, and z(t) is the z-axis acceleration component at time t.

[0059] Specifically, when calculating the variance of the real-time synthetic modulus within a preset time window, the mean value of the acceleration signal within the preset time window is first calculated. The real-time synthetic modulus and the mean value of the acceleration signal collected within the preset time window are then input into a preset variance calculation formula to obtain the variance of the real-time synthetic modulus within the preset time window. The variance calculation formula is as follows:

[0060]

[0061] In the formula, V is the variance, and n is the number of sampling points. M is the mean acceleration within the window. j Let be the j-th real-time synthesized modulus.

[0062] Specifically, a beat interval sequence is extracted from the first pressure signal, a short-term heart rate variability index is calculated based on the beat interval sequence, and the short-term heart rate variability index is used as a feature of the autonomic nervous system state.

[0063] Specifically, when extracting the beat interval sequence from the first pressure signal, the peak value of the pulse wave in the first pressure signal is identified by a peak detection algorithm, and the acquisition timestamp (t1, t2, ..., t) corresponding to each pulse wave peak value is recorded. n The time difference between two adjacent effective pulse wave peaks is the single beat interval i. j =t j+1 -t j (j = 1, 2, ..., n-1); arrange all beat intervals in chronological order to form a beat interval sequence I = {i1, i2, ..., i...} n-1 Furthermore, the length of the beat interval sequence is determined by the signal acquisition duration and the user's heart rate.

[0064] Specifically, when calculating the short-term heart rate variability index based on the beat-by-beat interval sequence, the beat-by-beat interval sequence is sequentially substituted into a preset short-term heart rate variability index calculation formula to obtain the short-term heart rate variability index. The short-term heart rate variability index calculation formula is as follows:

[0065]

[0066] In the formula, i j+1 -i j is the difference between the j-th beat interval and the (j+1)-th beat interval, i.e., the difference between two adjacent beat intervals, n is the number of pulse wave peaks, and r is the short-term heart rate variability index.

[0067] Specifically, the body position angle features, muscle tension features, physical stability features, and autonomic nervous system state features are integrated to obtain multidimensional state features.

[0068] In one embodiment, when determining whether the multidimensional state features are within a preset multidimensional state feature range, it is determined whether the absolute value of the body position angle feature is not greater than a preset angle threshold; whether the muscle tension feature is not greater than a preset tension ratio threshold; whether the physical stability feature is not greater than a preset movement threshold; and whether the autonomic nervous system state feature is greater than a preset stress threshold. If the absolute value of the body position angle feature is not greater than the preset angle threshold, the muscle tension feature is not greater than the preset tension ratio threshold, the physical stability feature is not greater than the preset movement threshold, and the autonomic nervous system state feature is greater than the preset stress threshold, then the user state is determined to meet the measurement conditions; otherwise, the user state is determined to not meet the measurement conditions.

[0069] Preferably, the preset angle threshold is 15°; the preset tension ratio threshold is 0.15; and the preset motion threshold is 0.01g. 2 The preset stress threshold is 20ms.

[0070] Specifically, if the absolute value of the body position angle feature is greater than a preset angle threshold, the user's state is determined to be an incorrect body position; if the muscle tension feature is greater than a preset tension ratio threshold, the user's state is determined to be muscle tension; if the physical stability feature is greater than a preset movement threshold, the user's state is determined to be moving; if the autonomic nervous system state feature is not greater than the preset stress threshold, the user's state is determined to be a state of tension / stress.

[0071] Specifically, if it is determined that the user's condition does not meet the measurement conditions, the blood pressure measurement of the user will be blocked, and specific rectification suggestions will be fed back based on the detected user condition, such as asking the user to relax their arm or raise their arm.

[0072] In one embodiment, the system will only trigger the inflation operation of the second preset pressure after the user's status is determined to meet the measurement conditions through multi-dimensional feature judgment during the measurement status admission stage. The inflation process is executed by the micro DC diaphragm pump controlled by the main control module, and the inflation rate is precisely controlled at 15-20 mmHg / s to ensure inflation efficiency while avoiding excessive pressure rise that could cause user discomfort or signal fluctuations.

[0073] Specifically, the second preset pressure is greater than the first preset pressure.

[0074] In one embodiment, when the cuff pressure reaches the second preset pressure, the system immediately switches to the deflation measurement mode, and the controllable precision exhaust valve performs linear deflation, stabilizing the deflation rate at 3-5 mmHg / s. This deflation rate design ensures that sufficient arterial pulsation signals can be captured at each pressure level, while avoiding excessively slow deflation that would lead to excessively long measurement time.

[0075] Step 102: During the deflation measurement, the user's second pressure signal and second limb dynamic signal are collected simultaneously. Based on the second limb dynamic signal, the sudden artifact period is determined. The second pressure signal during the sudden artifact period is preprocessed based on the dynamic gating strategy to obtain the preprocessed pressure signal.

[0076] In one embodiment, the simultaneous acquisition of the second pressure signal and the second limb dynamic signal is the core data acquisition action in the deflation measurement stage. The purpose is to simultaneously acquire the physiological signal used for blood pressure calculation and the dynamic signal used for interference judgment, providing dual data support for accurate blood pressure calculation and artifact removal. The acquisition process runs through the entire deflation cycle, starting from when the cuff pressure drops to the second preset pressure and ending when the pressure drops to 60 mmHg, and is carried out synchronously without interruption.

[0077] Specifically, the second pressure signal is acquired based on the pressure sensor, and the second limb dynamic signal is acquired based on the triaxial accelerometer; wherein, the second pressure signal and the second limb signal differ from the first pressure signal and the first limb signal in that they are acquired at different stages.

[0078] In one embodiment, when determining the sudden artifact period based on the second limb dynamic signal, the signal change rate of the second limb dynamic signal collected at the current moment is calculated in real time, and a dynamic change rate threshold is set based on the second pressure signal collected at the current moment; the signal change rate is compared with the dynamic change rate threshold, and if the signal change rate is greater than the dynamic change rate threshold, the current moment is determined to be the sudden artifact period.

[0079] Specifically, based on the current dynamic signal of the second limb collected at the current moment, the current moment modulus corresponding to the current dynamic signal of the second limb is calculated, and the previous moment dynamic signal of the second limb collected at the previous moment is obtained, and the previous moment modulus corresponding to the previous moment dynamic signal is calculated. The absolute value difference between the current moment modulus and the previous moment modulus is calculated, and the absolute value difference is used as the signal change rate of the second limb dynamic signal collected at the current moment.

[0080] Specifically, the modulus at the current moment corresponding to the current second limb dynamic signal and the modulus at the previous moment corresponding to the previous second limb dynamic signal are calculated based on the modulus calculation formula described above.

[0081] Specifically, when calculating the absolute difference between the current modulus and the previous modulus, the current modulus and the previous modulus are substituted into a preset formula for calculating the absolute difference of modulus to obtain the absolute difference between the two. The formula for calculating the absolute difference of modulus is: j(t)=|m(t)-m(t-1)|, where j(t) is the absolute difference between the current modulus and the previous modulus, i.e., the rate of change of the signal, m(t) is the current modulus, and m(t-1) is the previous modulus.

[0082] Specifically, the dynamic rate of change threshold is not a fixed value, but is dynamically adjusted based on the pulse wave amplitude of the second pressure signal acquired at the current moment. For example, a preset multiple of the pulse wave amplitude can be set as the dynamic rate of change threshold; preferably, the preset multiple is 5 times. This is because the arterial pulsation intensity varies among different users and at different measurement stages, and the corresponding pressure oscillation wave amplitude will also change. If a fixed threshold is used, artifacts may be missed when the pulse wave amplitude is large, or normal pulsation may be mistakenly identified as artifacts when the amplitude is small. Therefore, by linking the dynamic rate of change threshold to the pulse wave amplitude of the second pressure signal, the threshold can adaptively match the current physiological signal intensity, ensuring the accuracy of artifact detection, neither missing real interference nor mistakenly eliminating effective physiological signals.

[0083] In one embodiment, each time the sensing module collects a set of second limb dynamic signals and second pressure signals, the main control module immediately and synchronously calculates the signal change rate and the dynamic change rate threshold, and then directly compares the two. If the signal change rate is greater than the dynamic change rate threshold, it means that the current limb dynamic change amplitude far exceeds the vibration range brought by normal arterial pulsation, which can be identified as a sudden artifact, such as arm swinging, coughing, muscle twitching, etc., and the moment is marked as the sudden artifact period. The core purpose of this determination is to provide accurate interference time positioning for subsequent dynamic gating strategies, ensure that the second pressure signal within this period can be processed in a targeted manner, and avoid artifacts from contaminating the core data for blood pressure calculation.

[0084] In one embodiment, the dynamic gating strategy includes a data culling method and a machine station suspension method.

[0085] In one embodiment, when the dynamic gating strategy is a data elimination method, the second pressure signal during the sudden artifact period is preprocessed to obtain a preprocessed pressure signal. Specifically, this includes: acquiring the acquisition time corresponding to each of the acquired second pressure signals, eliminating the second pressure signals whose acquisition time falls within the sudden artifact period, and using all the remaining second pressure signals as the preprocessed pressure signal.

[0086] Specifically, the acquisition time of each second pressure signal is compared with the sudden artifact period previously determined by the second limb dynamic signal. If the acquisition time of a second pressure signal falls within any of the marked artifact periods, it is determined that the second pressure signal has been contaminated by motion artifacts, such as arm movement or coughing, which cause pressure signal distortion. All second pressure signals marked as having acquisition times falling within artifact periods are discarded, directly removing such invalid data. At the same time, second pressure signals whose acquisition times are not within artifact periods are fully retained, and these undisturbed valid signals are integrated into preprocessed pressure signals. The entire process does not change the original characteristics of the valid signals, only performing a screening to retain true signals and remove false signals. This can eliminate the interference of artifacts on pressure signals from the source, avoid contaminated data from participating in envelope fitting, directly improve the purity of the subsequent envelope curve, and thus ensure the accuracy of blood pressure calculation.

[0087] In one embodiment, the number of rejected second pressure signals and the theoretical number of signals are also obtained. Based on the number of rejected signals and the theoretical number of signals, the rejection rate is calculated. If the rejection rate is greater than a preset rejection rate threshold, the current blood pressure measurement is determined to be invalid; otherwise, the current blood pressure measurement is determined to be valid.

[0088] Specifically, when calculating the rejection rate based on the number of rejections and the theoretical number of signals, the number of rejections and the theoretical number of signals are substituted into a preset rejection rate calculation formula to obtain the rejection rate. The rejection rate calculation formula is as follows:

[0089]

[0090] Among them, R Ioss N represents the rejection rate. del To remove the number of items, N all The theoretical number of signals.

[0091] In one embodiment, when the dynamic gating strategy is the mechanical station pause method, when it is determined that the current time is the period of the sudden artifact, the cuff is controlled to pause the deflation to maintain constant pressure until the current time is no longer the period of the sudden artifact, and then the deflation measurement process is resumed; the target second pressure signal when the current time is no longer the period of the sudden artifact is collected, and the target second pressure signal is used as the preprocessed pressure signal.

[0092] Specifically, the mechanical pause method uses physical interference avoidance to address persistent motion artifacts. By actively controlling the cuff deflation state, it physically skips the interference period rather than removing contaminated data afterward. Compared to data removal methods, it avoids data gaps and interpolation errors caused by removing a large amount of data, ensuring that the second pressure signal collected at each pressure level is an undisturbed, original, and valid signal, further improving the accuracy and reliability of blood pressure measurement.

[0093] Specifically, during the deflation measurement process, the main control module monitors the rate of change of the dynamic signal of the second limb in real time. When it determines that the current moment is a period of sudden artifact, it immediately sends a closing command to the controllable precision exhaust valve. At this time, the cuff stops deflation, and the internal pressure remains at the current constant value to avoid signal superposition and contamination caused by pressure changes during the interference period. After entering the pause state, the system switches to the waiting mode, and the triaxial accelerometer continuously collects the limb dynamic signal. The main control unit judges in real time whether the artifact has disappeared. When the limb dynamic signal returns to calm and this stable state lasts for more than 1 second, it is determined that the sudden artifact has disappeared. This is to avoid resuming measurement before the artifact has completely disappeared, which would cause the signal to be contaminated again. When the recovery conditions are met, the main control module sends an opening command to the exhaust valve again, controlling the valve to resume linear deflation at the originally set deflation rate. The deflation measurement process continues until the cuff pressure drops to the target lower limit.

[0094] Specifically, during the pause in venting, the system does not collect any second pressure signal and directly skips the period of artifact interference; only when venting is a non-sudden artifact period does the pressure sensor continuously collect the second pressure signal. After the measurement is completed, there is no need to perform additional rejection processing on the collected target second pressure signal. It is directly integrated into the preprocessed pressure signal, providing a complete and clean data source for subsequent envelope reconstruction.

[0095] Step 103: Convert the preprocessed pressure signal into an envelope curve, and calculate the blood pressure value based on the envelope curve.

[0096] In one embodiment, when converting the preprocessed pressure signal into an envelope curve, the preprocessed pressure signal is integrated into a pressure signal sequence according to the acquisition time. It is determined whether the number of signals in the pressure signal sequence is the theoretical number of signals. If so, the pressure signal sequence is directly reconstructed into an envelope curve. If the number of signals is not the theoretical number of signals, a monotonic interpolation algorithm is used to interpolate the pressure signal sequence to obtain an interpolated pressure signal sequence, and the interpolated pressure signal sequence is reconstructed into an envelope curve.

[0097] Specifically, all pre-processed pressure signals are sorted according to the order of acquisition time to form a pressure signal sequence, ensuring that the sequence is consistent with the pressure drop trend during the cuff deflation process.

[0098] Specifically, the theoretical number of signals is an expected value derived from the total venting time and the pressure sensor sampling rate during the venting measurement process; for example, the theoretical number of signals = total venting time × pressure sensor sampling rate; where the total venting time is determined by the venting rate and the venting pressure range.

[0099] Specifically, the core of determining whether the number of signals in the pressure signal sequence is the theoretical number of signals is to compare the actual number of retained second pressure signals with the theoretical number of signals to determine whether there are signal missing due to data removal.

[0100] Specifically, if the number of preprocessed pressure signals matches the theoretical number, it indicates that there are no obvious sudden artifacts during the deflation process, or that artifacts have been avoided through mechanical pauses, and the signal sequence is complete and without gaps. In this case, no additional processing is required. Based on this complete sequence, a continuous pressure oscillation wave envelope curve can be reconstructed using a conventional oscillometric pressure oscillation wave envelope extraction algorithm. This curve can accurately reflect the change in arterial pulsation as the cuff pressure decreases.

[0101] Specifically, if the number of preprocessed pressure signals is less than the theoretical number of signals, it means that the data elimination method has removed some contaminated signals, resulting in data gaps in the sequence, that is, signals corresponding to some pressure levels are missing; in this case, a monotonic interpolation algorithm needs to be used to fill in the gaps.

[0102] Preferably, the monotonic interpolation algorithm is monotonic cubic Hermite spline interpolation. Since ordinary spline interpolation is prone to overshoot at data gaps, that is, the interpolated amplitude may be abnormally high or low, leading to incorrect systolic pressure determination; therefore, using monotonic cubic Hermite spline interpolation can ensure that the interpolation curve remains monotonic between adjacent data points and will not produce false extreme points.

[0103] Specifically, when interpolating the pressure signal sequence using a monotonic interpolation algorithm, the effective signal points before and after the missing segment are used as a reference. The interpolation algorithm generates a supplementary signal that conforms to physiological laws. After completion, the interpolated pressure signal sequence is obtained. This interpolated pressure signal sequence has the same number of signals as the theoretical signal and no data gaps. The complete envelope curve is then reconstructed based on this sequence.

[0104] In one embodiment, when calculating blood pressure based on the envelope curve, the maximum amplitude point on the envelope curve is determined, and the pressure value corresponding to the maximum amplitude point is taken as the mean pressure; a preset systolic pressure characteristic ratio and diastolic pressure characteristic ratio are obtained, and the systolic pressure and diastolic pressure are calculated based on the mean pressure, the systolic pressure characteristic ratio and the diastolic pressure characteristic ratio.

[0105] Specifically, since the mean pressure is the point of strongest arterial pulsation physiologically, it is reflected as the point of maximum amplitude on the envelope curve; therefore, the horizontal axis pressure value corresponding to the point of maximum amplitude on the envelope curve is directly extracted as the mean pressure.

[0106] Specifically, the preset systolic blood pressure characteristic ratio is 0.55, and the preset diastolic blood pressure characteristic ratio is 0.80.

[0107] Specifically, a first ratio of the mean blood pressure to the characteristic ratio of the systolic blood pressure is calculated, and the first ratio is used as the systolic blood pressure; a second ratio of the mean blood pressure to the characteristic ratio of the diastolic blood pressure is calculated, and the second ratio is used as the diastolic blood pressure.

[0108] In one embodiment, the oscillometric blood pressure measurement system is further provided with a human-computer interaction module, wherein the human-computer interaction module is provided with a screen for displaying the systolic blood pressure and the diastolic blood pressure for the user to view.

[0109] Example 2, see Figure 2 , Figure 2 This is a schematic diagram of an embodiment of an oscillometric blood pressure measurement system provided in this application; corresponding to the above-described oscillometric blood pressure measurement method, this application also provides an oscillometric blood pressure measurement system; the oscillometric blood pressure measurement system includes a module for performing the above-described oscillometric blood pressure measurement method, and the oscillometric blood pressure measurement system can be configured in a desktop computer, tablet computer, laptop computer, or other terminal; specifically, the oscillometric blood pressure measurement system includes a gas path control module 201, a sensing module 202, and a main control module 203.

[0110] In one embodiment, the pneumatic control module 201 includes a cuff 2011.

[0111] In one embodiment, the air circuit control module 201 further includes an air pump 2012, a rapid inflation valve 2013, and a controllable precision exhaust valve 2014; as Figure 3 As shown, Figure 3 This is a schematic diagram of the airway control module structure of an embodiment of an oscillometric blood pressure measurement system provided in this application.

[0112] Specifically, the air pump 2012 is a miniature DC diaphragm pump with an inflation rate controlled at 15-20 mmHg / s, used to inflate the cuff 2011.

[0113] Specifically, the controllable precision exhaust valve 2014 includes, but is not limited to, an electromagnetic linear proportional valve; the valve opening of the controllable precision exhaust valve 2014 is controlled by the PWM signal output by the main control module 203, which can achieve precise linear venting of 3-5 mmHg / s, and the controllable precision exhaust valve 2014 is completely closed based on the control of the main control module 203 when the main control module 203 detects a sudden afterimage interference.

[0114] Specifically, the valve opening of the rapid inflation valve 2013 is also controlled by the PWM signal output by the main control module 203.

[0115] In one embodiment, the sensing module 202 includes a pressure sensor 2021 and a triaxial accelerometer 2022; as shown Figure 4 As shown, Figure 4 This is a schematic diagram of the sensor module structure of an embodiment of an oscillometric blood pressure measurement system provided in this application.

[0116] Specifically, the pressure sensor 2021 is coupled to the cuff 2011 and is used to collect static pressure and dynamic pulse waves within the cuff 2011.

[0117] Specifically, the pressure sensor 2021 is a MEMS piezoresistive sensor, such as the Honeywell ABP series, with a range of 0-40kPa (0-300mmHg) and an accuracy of ±1%; its sampling rate is set to 100Hz.

[0118] Specifically, the triaxial accelerometer 2022 is rigidly coupled within the cuff or device body to collect limb dynamic data. For example, the triaxial accelerometer 2022 may be integrated into the inner side of the cuff, such as by soldering it onto a small rigid PCB, which is encapsulated on the outside of the cuff's air bladder. Preferably, it is placed directly above the brachial artery or on the outer side of the upper arm, or at the radial artery. The specific placement depends on the device type, such as a barrel-type or split-type device, and maintains good and stable vibration coupling with the skin. Alternatively, it can be encapsulated in a flexible, biocompatible silicone base with acoustic / vibration damping properties to enhance the pickup of target signals and isolate noise such as cuff fabric friction. It is used to detect high-frequency motion artifacts and muscle tension, and also to extract beat-by-beat intervals by capturing weak skin vibrations caused by arterial pulsation, thereby analyzing heart rate variability.

[0119] Specifically, the triaxial accelerometer 2022 is a low-power triaxial accelerometer, such as ST LIS2DW12 or Bosch BMA400; its range is configured to ±2g, which is sufficient to capture micro-movements of the human body and has high resolution; its sampling rate is configured to 200Hz-500Hz, wherein the high sampling rate is configured to ensure that the high-frequency characteristics of muscle tremors and instantaneous impact signals can be captured.

[0120] In one embodiment, the main control module 203 is connected to the air path control module 201 and the sensing module 202 respectively, and can receive sensor data collected by the pressure sensor 2021 and the triaxial acceleration sensor 2022 in the sensing module 202, and control the air pump 2012, the rapid inflation valve 2013 and the controllable precision exhaust valve 2014 in the air path control module 201 to execute the inflation and deflation logic of the cuff 2011.

[0121] In one embodiment, the main control module 203 is configured to perform the oscillometric blood pressure measurement method as described in any one of Embodiment 1 above.

[0122] In one embodiment, the main control module 103 adopts an ARM Cortex-M4 core microcontroller or a higher specification, such as the STM32L4 series, with a main frequency of 80MHz, and has an FPU (floating-point unit) to support real-time fast Fourier transform and spline interpolation operations.

[0123] In one embodiment, such as Figure 5 As shown, Figure 5 This is a schematic diagram of the main control module structure of an embodiment of the oscillometric blood pressure measurement system provided in this application. The main control module 203 includes a measurement state access judgment unit 2031, a sudden artifact dynamic processing unit 2032, and a blood pressure measurement unit 2033. The measurement state access judgment unit 2031 controls the cuff to inflate to a first preset pressure, collects the user's first pressure signal and first limb dynamic signal, and determines whether the user's state meets the measurement conditions based on the first pressure signal and the first limb dynamic signal. If so, it controls the cuff to inflate to a second preset pressure and then performs deflation measurement. The sudden artifact dynamic processing unit 2032 simultaneously collects the user's second pressure signal and second limb dynamic signal during deflation measurement, determines the sudden artifact period based on the second limb dynamic signal, and preprocesses the second pressure signal during the sudden artifact period based on a dynamic gating strategy to obtain a preprocessed pressure signal. The blood pressure measurement unit 2033 converts the preprocessed pressure signal into an envelope curve and calculates the blood pressure value based on the envelope curve.

[0124] In one embodiment, the measurement state admission judgment unit 2031 is used to determine whether the user state meets the measurement conditions based on the first pressure signal and the first limb dynamic signal. Specifically, it includes: extracting multi-dimensional features from the first pressure signal and the first limb dynamic signal to obtain multi-dimensional state features; determining whether the multi-dimensional state features are within a preset multi-dimensional state feature range; if so, determining that the user state meets the measurement conditions.

[0125] In one embodiment, the measurement state admission judgment unit 2031 is used to extract multidimensional features from the first pressure signal and the first limb dynamic signal to obtain multidimensional state features, specifically including: calculating the limb position angle based on the first limb dynamic signal and using the limb position angle as a position angle feature; performing spectral analysis on the first limb dynamic signal, calculating the energy ratio of the first energy in the first target frequency band and the second energy in the second target frequency band, and using the energy ratio as a muscle tension feature; calculating the real-time synthetic modulus of the first limb dynamic signal, calculating the variance of the real-time synthetic modulus within a preset time window, and using the variance as a physical stability feature; extracting the beat interval sequence from the first pressure signal, calculating the short-term heart rate variability index based on the beat interval sequence, and using the short-term heart rate variability index as an autonomic nervous system state feature; and integrating the position angle feature, the muscle tension feature, the physical stability feature, and the autonomic nervous system state feature to obtain multidimensional state features.

[0126] In one embodiment, the sudden artifact dynamic processing unit 2032 is used to determine the sudden artifact period based on the second limb dynamic signal, specifically including: calculating the signal change rate of the second limb dynamic signal collected at the current moment in real time; setting a dynamic change rate threshold based on the second pressure signal collected at the current moment; comparing the signal change rate with the dynamic change rate threshold; if the signal change rate is greater than the dynamic change rate threshold, then determining the current moment as the sudden artifact period.

[0127] In one embodiment, the sudden artifact dynamic processing unit 2032 is used to preprocess the second pressure signal during the sudden artifact period based on a dynamic gating strategy to obtain a preprocessed pressure signal. Specifically, this includes: acquiring the acquisition time corresponding to each acquired second pressure signal; removing second pressure signals whose acquisition time falls within the sudden artifact period; and using all the remaining second pressure signals as preprocessed pressure signals; or, when it is determined that the current time is the sudden artifact period, controlling the cuff to pause deflation to maintain constant pressure until the current time is no longer the sudden artifact period, and then resuming the deflation measurement process; acquiring the target second pressure signal when the current time is not the sudden artifact period, and using the target second pressure signal as the preprocessed pressure signal.

[0128] In one embodiment, the blood pressure measurement unit 2033 is used to convert the preprocessed pressure signal into an envelope curve, specifically including: integrating the preprocessed pressure signal into a pressure signal sequence according to the acquisition time; determining whether the number of signals in the pressure signal sequence is the theoretical number of signals; if so, directly reconstructing the pressure signal sequence into an envelope curve; if the number of signals is not the theoretical number of signals, using a monotonic interpolation algorithm to interpolate the pressure signal sequence to obtain an interpolated pressure signal sequence, and reconstructing the interpolated pressure signal sequence into an envelope curve.

[0129] In one embodiment, the blood pressure measurement unit 2033 is used to calculate blood pressure values ​​based on the envelope curve, specifically including: determining the maximum amplitude point on the envelope curve and taking the pressure value corresponding to the maximum amplitude point as the mean pressure; obtaining preset systolic pressure characteristic ratio and diastolic pressure characteristic ratio, and calculating systolic pressure and diastolic pressure based on the mean pressure, the systolic pressure characteristic ratio and the diastolic pressure characteristic ratio.

[0130] In one embodiment, the oscillometric blood pressure measurement system further includes a human-computer interaction unit 204.

[0131] In one embodiment, the human-computer interaction unit 204 includes a display screen, buttons, and / or a buzzer.

[0132] Specifically, the human-computer interaction unit 204 is used to display the blood pressure measurement results and, when triggered in the measurement state access decision stage, to issue clear and operable prompts to the user, such as "Please relax" or "Please remain still".

[0133] Specifically, the button serves as a trigger element for the blood pressure measurement process. When the user wears the cuff 2011 and the button is pressed, the blood pressure measurement described in Example 1 is executed.

[0134] The oscillometric blood pressure measurement system described above can implement the oscillometric blood pressure measurement method of the above method embodiments; the options in the above method embodiments are also applicable to this embodiment, and will not be described in detail here.

[0135] like Figure 6 As shown, Figure 6 This is a schematic diagram of the structure of a computer device provided in this application; it includes a processor 111, a communication interface 112, a memory 113 and a communication bus 114, wherein the processor 111, the communication interface 112 and the memory 113 communicate with each other through the communication bus 114, and the memory 113 is used to store computer programs.

[0136] In one embodiment of this application, the processor 111, when executing the program stored in the memory 113, implements the oscillometric blood pressure measurement method provided in any of the aforementioned method embodiments.

[0137] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program may be stored in a storage medium, which is a computer-readable storage medium. The computer program is executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0138] Therefore, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the oscillometric blood pressure measurement method provided in any of the foregoing method embodiments.

[0139] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk, or any other physical storage medium capable of storing program code. The computer-readable storage medium can be non-volatile or volatile.

[0140] 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 the various examples 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 application.

[0141] In the embodiments provided in this application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of each unit is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0142] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the system of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0143] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0144] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0145] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Since these modifications and variations fall within the scope of the claims and their equivalents, this application also intends to include these modifications and variations.

[0146] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An oscillometric blood pressure measurement method, characterized in that, The method, applicable to oscillometric blood pressure measurement systems incorporating cuffs, includes: The cuff is inflated to a first preset pressure, and the user's first pressure signal and first limb dynamic signal are collected. Based on the first pressure signal and the first limb dynamic signal, it is determined whether the user's state meets the measurement conditions. If so, the cuff is inflated to a second preset pressure and then deflation measurement is performed. During the deflation measurement process, the user's second pressure signal and second limb dynamic signal are collected simultaneously. Based on the second limb dynamic signal, the sudden artifact period is determined. Based on the dynamic gating strategy, the second pressure signal during the sudden artifact period is preprocessed to obtain the preprocessed pressure signal. The preprocessed pressure signal is converted into an envelope curve, and the blood pressure value is calculated based on the envelope curve.

2. The method as described in claim 1, characterized in that, The step of determining whether the user's state meets the measurement conditions based on the first pressure signal and the first limb dynamic signal specifically includes: Multidimensional feature extraction is performed on the first pressure signal and the first limb dynamic signal to obtain multidimensional state features; Determine whether the multidimensional state features are within the preset multidimensional state feature range. If so, determine that the user state meets the measurement conditions.

3. The method as described in claim 2, characterized in that, The step of extracting multidimensional features from the first pressure signal and the first limb dynamic signal to obtain multidimensional state features specifically includes: The limb position angle is calculated based on the first limb dynamic signal, and the limb position angle is used as the position angle feature. Spectral analysis is performed on the first limb dynamic signal to calculate the energy ratio of the first energy in the first target frequency band and the second energy in the second target frequency band, and the energy ratio is used as a muscle tension feature. Calculate the real-time synthetic modulus of the first limb dynamic signal, calculate the variance of the real-time synthetic modulus within a preset time window, and use the variance as a physical stability feature; Extract the beat interval sequence from the first pressure signal, calculate the short-term heart rate variability index based on the beat interval sequence, and use the short-term heart rate variability index as a feature of the autonomic nervous system state. By integrating the body position angle features, muscle tension features, physical stability features, and autonomic nervous system state features, multidimensional state features are obtained.

4. The method as described in claim 1, characterized in that, The determination of the sudden artifact time period based on the second limb dynamic signal specifically includes: The rate of change of the second limb dynamic signal collected at the current moment is calculated in real time, and a dynamic change rate threshold is set based on the second pressure signal collected at the current moment; The signal change rate is compared with the dynamic change rate threshold. If the signal change rate is greater than the dynamic change rate threshold, the current moment is determined to be a sudden artifact period.

5. The method as described in claim 1, characterized in that, The preprocessing of the second pressure signal during the burst artifact period based on the dynamic gating strategy to obtain the preprocessed pressure signal specifically includes: Acquire the acquisition time corresponding to each of the second pressure signals, remove the second pressure signals whose acquisition time falls within the burst artifact period, and use all the remaining second pressure signals as preprocessed pressure signals; or, When the current time is determined to be the period of the sudden artifact, the control cuff is paused to maintain constant pressure until the current time is no longer the period of the sudden artifact, at which point the deflation measurement process is resumed. Collect the target's second pressure signal when the current time is not during the period of the sudden artifact, and use the target's second pressure signal as the preprocessed pressure signal.

6. The method as described in claim 1, characterized in that, The step of converting the preprocessed pressure signal into an envelope curve specifically includes: The preprocessed pressure signals are integrated into a pressure signal sequence according to the acquisition time. It is determined whether the number of signals in the pressure signal sequence is the theoretical number of signals. If so, the pressure signal sequence is directly reconstructed into an envelope curve. If the number of signals is not the theoretical number of signals, a monotonic interpolation algorithm is used to interpolate the pressure signal sequence to obtain an interpolated pressure signal sequence, and the interpolated pressure signal sequence is reconstructed into an envelope curve.

7. The method as described in claim 1, characterized in that, The calculation of blood pressure values ​​based on the envelope curve specifically includes: The point of maximum amplitude on the envelope curve is determined, and the pressure value corresponding to the point of maximum amplitude is taken as the average pressure; Obtain the preset systolic blood pressure characteristic ratio and diastolic blood pressure characteristic ratio, and calculate the systolic blood pressure and diastolic blood pressure based on the mean blood pressure, the systolic blood pressure characteristic ratio and the diastolic blood pressure characteristic ratio.

8. An oscillometric blood pressure measurement system, characterized in that, include: The system comprises a pneumatic control module, a sensing module, and a main control module. The air circuit control module includes a cuff; The main control module is connected to the airway control module and the sensing module respectively, and is configured to perform the oscillometric blood pressure measurement method as described in any one of claims 1-7.

9. A computer device, characterized in that, The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, can implement the method as described in any one of claims 1-7.

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