Ambulatory blood pressure measuring device air pump control method and system based on pulse waveform dynamic adjustment

Abstract

The invention provides an ambulatory blood pressure measuring device air pump control method and system based on pulse waveform dynamic adjustment, and relates to the technical field of ambulatory blood pressure measuring device air pump control. An optimal detection point is determined through pulse collection information of multiple detection points of an ambulatory blood pressure measuring device, and air pump and physiological data collection, adjustment and analysis are conducted; adjusting and analyzing the body position change according to the compensation fitting adjusting data, obtaining the dynamic control strategy information of the air pump to carry out control constraint analysis and adjustment, and obtaining the optimal control strategy information of the air pump; according to the air pump optimization strategy information, pulse feature anomaly analysis and adjustment are carried out, and air pump physiological adjustment data are obtained; performing pressure calibration adjustment according to the body position air pump adjustment data in combination with the pulse characteristic abnormal data so as to obtain inflation physiological fitting data; according to the method, multi-dimensional data are fused, and the physiological change and the accurate blood pressure measurement capability are dynamically adapted.

Description

Technical Field

[0001] This invention proposes a method and system for controlling the air pump of a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform, which relates to the field of air pump control technology, specifically to the field of air pump control technology for dynamic blood pressure measurement devices with dynamic adjustment of pulse waveform. Background Technology

[0002] Existing ambulatory blood pressure monitoring devices often employ fixed pressurization parameters or single-dimensional adjustment modes for their air pump control, making it difficult to adapt to dynamic changes in the user's physiological state. Traditional solutions do not fully consider individual differences in blood pressure measurement locations and the impact of positional changes (such as lying down versus sitting) on ​​pressure transmission. This often leads to distorted pulse data due to probe point deviations, resulting in a mismatch between the inflation process and vascular condition. Furthermore, the lack of a coordinated adjustment mechanism for factors such as air pump operating errors, battery power fluctuations, and abnormal pulse fluctuations easily leads to problems such as insufficient pressurization accuracy and an imbalance between battery life and measurement effectiveness. In addition, the lack of precise calibration and physiological adaptation linkage schemes after device failure, coupled with fixed pressure range settings, prevents dynamic tracking of changes in the user's heart rate, vascular elasticity, and other physiological characteristics, resulting in poor measurement consistency across different scenarios and significant user discomfort. Summary of the Invention

[0003] This invention provides a method and system for controlling the air pump of a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform, in order to solve the above-mentioned problems:

[0004] The present invention proposes a method and system for controlling the air pump of a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform. The method includes:

[0005] S1. The optimal detection point is determined by collecting pulse information from multiple detection points of the dynamic blood pressure measurement device. Data collection and adjustment analysis of air pump and physiological functions are performed to obtain compensation fit adjustment data. Based on the compensation fit adjustment data, the adjustment analysis of body position changes is performed to obtain body position air pump adjustment data.

[0006] S2. Obtain dynamic control strategy information of the air pump, perform control constraint analysis and adjustment, and obtain optimized control strategy information of the air pump; perform abnormal pulse characteristic analysis and adjustment based on the optimized control strategy information of the air pump, and obtain physiological regulation data of the air pump.

[0007] S3. Based on the body position air pump adjustment data and pulse characteristic abnormal data, pressure calibration and adjustment are performed to obtain inflatable physiological fit data.

[0008] S4. Adjust and update the pressurization parameters based on the inflation physiological fit data to obtain adjustment and update information.

[0009] Further, S1 includes:

[0010] The user's blood pressure detection area is determined by the pulse detection sensor built into the dynamic blood pressure measurement device.

[0011] Multiple pulse detection points are determined based on the user's blood pressure detection area, and pulse data is collected from multiple pulse detection points using a pulse detection sensor to obtain pulse data from multiple detection points.

[0012] Pulse signal intensity analysis is performed on the pulse data collected from the multiple detection points to obtain pulse signal intensity analysis data;

[0013] The optimal detection point is determined based on the pulse signal intensity analysis data.

[0014] Real-time acquisition of pulse waveform signals at the optimal detection point, and real-time acquisition of airbag pressure data through pressure sensors, to obtain real-time pulse waveform acquisition data and real-time airbag pressure data.

[0015] The air pump pressure is collected in real time by the air pump detection module to obtain air pump pressure data; based on the real-time pulse waveform data, characteristic curve parameters are analyzed to obtain physiological state analysis data.

[0016] Based on the physiological state analysis data, determine the air pump pressure adjustment parameters, and adjust the air pump pressure according to the air pump pressure adjustment parameters to obtain air pump fluctuation adjustment data.

[0017] Physiological state analysis data and air pump fluctuation adjustment data are combined and analyzed to obtain combined analysis data. The air pump pressure is then adjusted to compensate for the combined analysis data to obtain compensation fit adjustment data.

[0018] Based on the compensation and fit adjustment data, the postural changes were adjusted and analyzed to obtain the postural air pump adjustment data.

[0019] Furthermore, the step of performing postural adjustment analysis based on the compensation fit adjustment data to obtain postural air pump adjustment data includes:

[0020] Postural data is collected by the posture sensing unit built into the dynamic blood pressure measurement device.

[0021] Based on the changes in body position data, compensation fit adjustment data is obtained by adjusting the fit data.

[0022] Determine the air pump adjustment parameters based on the fit change data, and adjust the air pump according to the air pump adjustment parameters to obtain air pump adjustment data.

[0023] Based on the data on changes in air pump adjustment, obtain the air pump adjustment data for different body positions.

[0024] Further, S2 includes:

[0025] A trend chart of changes in real-time pulse waveform acquisition data was constructed based on physiological state analysis data.

[0026] Based on the trend chart and the body position air pump adjustment data, determine the dynamic control strategy information for the air pump.

[0027] Based on the dynamic control strategy information of the air pump, control constraint analysis is performed to obtain control constraint analysis data;

[0028] Based on the control constraint analysis data, the dynamic control strategy of the air pump is adjusted to obtain the optimized control strategy information of the air pump.

[0029] Based on the air pump optimization strategy information, pulse characteristic anomaly analysis and adjustment are performed to obtain pulse characteristic anomaly data.

[0030] Furthermore, the step of analyzing and adjusting pulse characteristic anomalies based on the air pump optimization strategy information to obtain air pump physiological regulation data includes:

[0031] During the adjustment of the air pump, pulse waveform features are extracted from the trend graph to obtain pulse feature extraction data.

[0032] A dynamic pressure range is constructed by combining air pump optimization control strategy information with pressure calibration data;

[0033] Anomaly analysis was performed on the pulse feature extraction data based on the dynamic pressure range to obtain abnormal pulse feature data.

[0034] Based on the abnormal pulse characteristic data, the air pump optimization control strategy information is adjusted to obtain air pump physiological regulation data.

[0035] Further, S3 includes:

[0036] Establish a database of pulse characteristic curves corresponding to different body positions based on the differences in body position information between lying and sitting positions;

[0037] Perform an airway sealing test on the air pump to obtain airway test data;

[0038] Confirm the working status of the air pump based on airway detection data;

[0039] Based on the air pump's operating status and real-time airbag pressure data, deviation correction is performed to obtain pressure deviation correction data.

[0040] Inflation physiological fit data is obtained by combining the working status of the air pump with pressure deviation correction data.

[0041] Furthermore, based on the air pump's operating status and real-time airbag pressure data, deviation correction is performed to obtain pressure deviation correction data, including:

[0042] Based on the airway detection data, identify abnormal data of the air pump and device to obtain device abnormality identification data;

[0043] A multi-dimensional fault investigation process is triggered based on device anomaly identification data;

[0044] After troubleshooting multiple faults, the pressure is recalibrated using a standard pressure source. The pump speed and pressurization strategy are updated by obtaining the latest parameters from the real-time air pressure feedback data and pulse waveform characteristic curve.

[0045] Further, S4 includes:

[0046] Information on the trend of physiological changes during the stage is obtained by using inflatable physiological fit data;

[0047] By combining the physiological change trend information of the aforementioned stage with the pressure data obtained in real time by the dynamic blood pressure measurement device, the air pump pressure monitoring results and body position information, the pressure range threshold and adjustment step size are updated during the pressurization process. Based on the updated data, the air pump inflation speed and pressurization timing adjustment commands are triggered to obtain the adjustment update information.

[0048] Furthermore, the step of combining physiological state analysis data with air pump fluctuation adjustment data to obtain combined analysis data, and then adjusting the air pump pressure based on the combined analysis data to obtain compensated fit adjustment data, includes:

[0049] The blood pressure measurement module of the dynamic blood pressure measurement device confirms the fit status data of the sensor blood pressure measurement. After the pulse signal is stabilized, the air pump is started to pressurize. The periodic calibration data of pressure calibration is combined with the real-time air pressure detected by the air pump.

[0050] The algorithm extracts the characteristic curve of the pulse waveform and updates it dynamically. Based on the physiological change trend information constructed from multiple sets of data, the pumping speed of the air pump is dynamically adjusted in stages. Simultaneously, the pressure compensation coefficient of different body positions, the power consumption constraint of the battery, and the real-time feedback of the air pump's working status are combined to construct a full-dimensional dynamic pressure range.

[0051] Furthermore, the system includes:

[0052] The fit analysis module is used to determine the optimal detection point by collecting pulse information from multiple detection points of the dynamic blood pressure measurement device, to collect and analyze data on air pump and physiological functions, to obtain compensating fit adjustment data, and to analyze the adjustment of body position changes based on the compensating fit adjustment data to obtain body position air pump adjustment data.

[0053] The optimization analysis module is used to acquire dynamic control strategy information of the air pump, perform control constraint analysis and adjustment, and obtain optimized control strategy information of the air pump; based on the optimized control strategy information of the air pump, it performs pulse characteristic anomaly analysis and adjustment to obtain physiological regulation data of the air pump.

[0054] The fit adjustment module is used to perform pressure calibration and adjustment based on body position air pump adjustment data and abnormal pulse characteristic data to obtain inflatable physiological fit data.

[0055] The fit update module is used to adjust and update the pressure parameters based on the inflation physiological fit data and obtain adjustment and update information.

[0056] The beneficial effects of this invention are as follows: It constructs a multi-source fusion control system integrating physiological data, device data, and scenario data, breaking the limitations of single-parameter adjustment and making the air pump control more closely match the user's real-time physiological state, significantly improving the accuracy of blood pressure measurement; through a closed-loop process of acquisition, adjustment, calibration, and updating, it achieves dynamic self-adaptation of the air pump control, which can cope with various complex scenarios such as changes in body position, pulse fluctuations, and power fluctuations, enhancing the versatility and stability of the method; the layered decomposition of the adjustment logic (basic acquisition, body position adaptation, power optimization, anomaly correction, parameter update) reduces the impact of errors in a single link on the overall control effect, improving the robustness of the control process; all adjustment actions are based on real-time data feedback, avoiding the problem of asynchronous control between fixed parameters and user physiological changes. Attached Figure Description

[0057] Figure 1 A schematic diagram of the air pump control method for a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform;

[0058] Figure 2 This is a schematic diagram of the acquisition of detection points. Detailed Implementation

[0059] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0060] In one embodiment of the present invention, the present invention proposes a method and system for controlling the air pump of a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform, the method comprising:

[0061] S1. The optimal detection point is determined by collecting pulse information from multiple detection points of the dynamic blood pressure measurement device. Data collection and adjustment analysis of air pump and physiological functions are performed to obtain compensation fit adjustment data. Based on the compensation fit adjustment data, the adjustment analysis of body position changes is performed to obtain body position air pump adjustment data.

[0062] S2. Obtain dynamic control strategy information of the air pump, perform control constraint analysis and adjustment, and obtain optimized control strategy information of the air pump; perform abnormal pulse characteristic analysis and adjustment based on the optimized control strategy information of the air pump, and obtain physiological regulation data of the air pump.

[0063] S3. Based on the body position air pump adjustment data and pulse characteristic abnormal data, pressure calibration and adjustment are performed to obtain inflatable physiological fit data.

[0064] S4. Adjust and update the pressure parameters based on the inflation physiological fit data, and obtain the adjustment and update information, such as... Figure 1 As shown.

[0065] The working principle and technical effects of the above-mentioned technical solution are as follows: This method focuses on accurately adapting to the user's physiological changes, and constructs a control logic of multi-dimensional acquisition, layered adjustment, and closed-loop optimization. The optimal pulse acquisition location is determined through multi-detection point screening, and physiological data (pulse waveform) and device data (air pump pressure, airbag pressure) are acquired simultaneously. Preliminary adjustments yield compensation fit adjustment data; then, combined with dynamic adaptation of air pump adjustment parameters to body position changes, body position air pump adjustment data is generated; battery power constraints are introduced to optimize the air pump control strategy, and abnormal pulse characteristics are monitored and dynamically corrected simultaneously; through pressure calibration and iterative updates of pressurization parameters, the entire process of air pump control progresses from basic adaptation to precise fit, ensuring that each adjustment is based on the user's physiological state.

[0066] A multi-source control system integrating physiological data, equipment data, and scenario data was constructed, breaking the limitations of single-parameter adjustment and making the air pump control more closely match the user's real-time physiological state, significantly improving the accuracy of blood pressure measurement. Through a closed-loop process of data acquisition, adjustment, calibration, and updating, dynamic self-adaptation of the air pump control is achieved, which can cope with various complex scenarios such as changes in body position, pulse fluctuations, and power fluctuations, enhancing the versatility and stability of the method. The adjustment logic is broken down into layers (basic data acquisition, body position adaptation, power optimization, anomaly correction, and parameter update), reducing the impact of errors in a single link on the overall control effect and improving the robustness of the control process. All adjustment actions are based on real-time data feedback, avoiding the problem of asynchronous control between fixed parameters and user physiological changes, laying the overall framework foundation for the optimization of each sub-step.

[0067] In one embodiment of the present invention, S1 includes:

[0068] The user's blood pressure detection area is determined by the pulse detection sensor built into the dynamic blood pressure measurement device.

[0069] Multiple pulse detection points are determined based on the user's blood pressure detection area, and pulse data is collected from multiple pulse detection points using a pulse detection sensor to obtain pulse data from multiple detection points.

[0070] Pulse signal intensity analysis is performed on the pulse data collected from the multiple detection points to obtain pulse signal intensity analysis data;

[0071] The optimal detection point is determined based on the pulse signal intensity analysis data, such as... Figure 2 As shown;

[0072] Real-time acquisition of pulse waveform signals at the optimal detection point, and real-time acquisition of airbag pressure data through pressure sensors, to obtain real-time pulse waveform acquisition data and real-time airbag pressure data.

[0073] The air pump pressure is collected in real time by the air pump detection module to obtain air pump pressure data; based on the real-time pulse waveform data, characteristic curve parameters are analyzed to obtain physiological state analysis data.

[0074] Based on the physiological state analysis data, determine the air pump pressure adjustment parameters, and adjust the air pump pressure according to the air pump pressure adjustment parameters to obtain air pump fluctuation adjustment data.

[0075] Physiological state analysis data and air pump fluctuation adjustment data are combined and analyzed to obtain combined analysis data. The air pump pressure is then adjusted to compensate for the combined analysis data to obtain compensation fit adjustment data.

[0076] Based on the compensation and fit adjustment data, the postural changes were adjusted and analyzed to obtain the postural air pump adjustment data.

[0077] The working principle and technical effects of the above technical solution are as follows: This method focuses on core data acquisition and preliminary adjustment. First, the blood pressure detection area is delineated through a pulse detection sensor, and multiple detection points are set to filter the signal strength to ensure that the strongest and most stable pulse waveform signal is obtained, thus solving the problem of data distortion caused by position deviation of a single detection point. Simultaneously, real-time pulse waveform, airbag pressure, and air pump pressure data of the optimal detection point are acquired, and the user's physiological state such as heart rate and vascular elasticity is analyzed through characteristic curve parameters. Then, the air pump pressure adjustment parameters are determined based on the physiological state, and compensation adjustment is performed in combination with air pump fluctuation data, forming a preliminary closed loop of acquisition, analysis, adjustment, and compensation.

[0078] The multi-detection point screening mechanism effectively avoids acquisition errors caused by individual differences in blood pressure measurement location and wearing misalignment, ensuring the integrity and reliability of pulse waveform data and providing high-quality data input for all subsequent adjustment actions;

[0079] The synchronous acquisition and linkage analysis of physiological data and equipment data realizes the direct mapping between physiological state and air pump regulation, avoids the problem of untimely regulation caused by data lag, and improves the response speed of initial regulation.

[0080] The compensation fit adjustment mechanism integrates physiological state analysis data with air pump fluctuation data to correct the inherent working errors of the air pump (such as air pressure fluctuations and mechanical delays), making the initial adjustment results closer to the user's physiological needs.

[0081] The output compensation fit adjustment data and body position air pump adjustment data provide a unified data benchmark for the detailed steps, ensuring the continuity and consistency of the entire process adjustment and reducing the error of cross-stage data adaptation.

[0082] In one embodiment of the present invention, the step of performing postural adjustment analysis based on compensation fit adjustment data to obtain postural air pump adjustment data includes:

[0083] Postural data is collected by the posture sensing unit built into the dynamic blood pressure measurement device.

[0084] Based on the changes in body position data, compensation fit adjustment data is obtained by adjusting the fit data.

[0085] Determine the air pump adjustment parameters based on the fit change data, and adjust the air pump according to the air pump adjustment parameters to obtain air pump adjustment data.

[0086] Based on the data on changes in air pump adjustment, obtain the air pump adjustment data for different body positions.

[0087] The working principle and technical effect of the above technical solution are as follows: This method addresses the impact of body position changes on blood pressure measurement. By using the posture sensing unit built into the dynamic blood pressure measurement device to capture the user's lying and sitting posture data in real time, it analyzes the influence of body position changes on the compensation fit adjustment data and clarifies the differences in airbag pressure transmission under different body positions. Based on these differences, it determines the air pump adjustment parameters, dynamically adjusts the air pump's inflation speed and pressurization rhythm, and adapts the air pump output to the user's physiological state (such as blood return speed and vascular pressure distribution) after the body position change. Finally, it generates body position air pump adjustment data corresponding to different body positions, realizing real-time linkage between body position changes and air pump adjustment.

[0088] Precise identification and targeted adjustment of body position changes solves the problem of traditional ambulatory blood pressure measurement devices' fixed inflation parameters being unable to adapt to differences in body position, avoiding measurement deviations caused by changes in body position and improving the consistency of measurement results in different scenarios. Real-time linkage between body position changes and air pump adjustment ensures that the inflation process always matches the user's physiological rhythm, reducing discomfort caused by mismatch between airbag inflation and vascular status when switching positions (such as distending pain caused by excessively rapid inflation). The output body position and air pump adjustment data provides scenario-based data support for subsequent battery power constraint optimization and anomaly detection, making subsequent adjustments more targeted and further improving the overall control accuracy. The deep integration of posture perception and air pump adjustment expands the applicable scenarios of the method, allowing users to obtain a stable and accurate measurement experience in different states such as sitting at work or lying down to rest, enhancing the product's practicality.

[0089] In one embodiment of the present invention, S2 includes:

[0090] A trend chart of changes in real-time pulse waveform acquisition data was constructed based on physiological state analysis data.

[0091] Based on the trend chart and the body position air pump adjustment data, determine the dynamic control strategy information for the air pump.

[0092] Based on the dynamic control strategy information of the air pump, control constraint analysis is performed to obtain control constraint analysis data;

[0093] Based on the control constraint analysis data, the dynamic control strategy of the air pump is adjusted to obtain the optimized control strategy information of the air pump.

[0094] Based on the air pump optimization strategy information, pulse characteristic anomaly analysis and adjustment are performed to obtain pulse characteristic anomaly data.

[0095] The working principle and technical effects of the above technical solution are as follows: This method focuses on the optimized control of the air pump under battery power constraints. First, it collects the battery power parameters of the dynamic blood pressure measurement device and analyzes the impact of power supply capacity on the working efficiency of the air pump. Then, based on the obtained physiological state analysis data, it constructs a pulse waveform change trend chart and determines the basic dynamic control strategy of the air pump by combining the body position air pump adjustment data. The battery power analysis data is used as a constraint to optimize the basic strategy and balance the pressurization effect and power consumption. At the same time, based on the optimized strategy, it monitors abnormal pulse characteristics and corrects the air pump control parameters in reverse through anomaly analysis, forming a linkage logic of power constraint, strategy optimization, and anomaly correction to ensure that the air pump can work stably under different power states.

[0096] By introducing a battery power constraint mechanism, a dynamic balance between air pump control and device endurance is achieved. When the battery is sufficient, pressurization efficiency and measurement accuracy are guaranteed. When the battery is low, strategy optimization avoids power waste and extends the single-use duration of the device. The construction of a pulse waveform trend graph extends air pump control from real-time response to trend prediction, adapting to pulse fluctuation patterns in advance, reducing adjustment lag caused by sudden physiological changes, and improving the forward-looking nature of the control. The linkage between strategy optimization and anomaly detection not only solves the control limitations caused by battery constraints, but also ensures adjustment accuracy through anomaly correction, avoiding measurement failures due to insufficient battery or abnormal pulse. The output air pump optimized control strategy information and pulse characteristic anomaly data provide an optimization basis for subsequent pressure calibration and parameter updates, making the whole process control both endurance and accuracy, enhancing the practicality of the method and the user experience.

[0097] In one embodiment of the present invention, the step of analyzing and adjusting pulse characteristic anomalies based on pneumatic pump optimization strategy information to obtain pneumatic pump physiological regulation data includes:

[0098] During the adjustment of the air pump, pulse waveform features are extracted from the trend graph to obtain pulse feature extraction data.

[0099] A dynamic pressure range is constructed by combining air pump optimization control strategy information with pressure calibration data;

[0100] Anomaly analysis was performed on the pulse feature extraction data based on the dynamic pressure range to obtain abnormal pulse feature data.

[0101] Based on the abnormal pulse characteristic data, the air pump optimization control strategy information is adjusted to obtain air pump physiological regulation data.

[0102] The working principle and technical effect of the above technical solution are as follows: This method focuses on the precise adjustment of the air pump in scenarios of abnormal pulse. During the adjustment of the air pump, pulse waveform characteristic parameters (such as peak value, period, and rising slope) are continuously extracted. Combined with pressure calibration data, a dynamic pressure range is constructed to clarify the normal range of pulse characteristics under different physiological states. The extracted pulse characteristic data is compared with the dynamic pressure range to identify abnormal pulse fluctuations (such as sudden changes in heart rate and waveform distortion). Based on the type and degree of abnormality, the air pump optimization control strategy is corrected in reverse, and parameters such as inflation speed and pressurization amplitude are adjusted so that the air pump output avoids the sensitive range of abnormal physiological states, ensuring that the inflation process does not affect the user's physiological comfort and maintains the continuity of measurement.

[0103] The construction of dynamic pressure zones combines pressure calibration data with real-time physiological status, breaking the limitations of fixed threshold judgment, improving the accuracy of pulse anomaly identification, and avoiding unnecessary adjustments caused by misjudgment. The linkage correction between pulse anomalies and the air pump strategy realizes a rapid closed loop of anomaly identification, immediate response, and precise adaptation, effectively dealing with pulse abrupt changes caused by user emotional fluctuations and slight movements, and ensuring the stability of the measurement process. By adjusting the air pump parameters to avoid physiologically sensitive areas, the discomfort caused by pressurization under abnormal pulse conditions is reduced, improving the user experience, while avoiding interference from abnormal data on the measurement results. The output air pump physiological adjustment data further optimizes the air pump control parameters, making subsequent pressure calibration more targeted, providing an adaptation basis for precise control throughout the process under abnormal scenarios, and enhancing the method's anti-interference ability.

[0104] In one embodiment of the present invention, S3 includes:

[0105] Establish a database of pulse characteristic curves corresponding to different body positions based on the differences in body position information between lying and sitting positions;

[0106] Perform an airway sealing test on the air pump to obtain airway test data;

[0107] Confirm the working status of the air pump based on airway detection data;

[0108] Based on the air pump's operating status and real-time airbag pressure data, deviation correction is performed to obtain pressure deviation correction data.

[0109] Inflation physiological fit data is obtained by combining the working status of the air pump with pressure deviation correction data.

[0110] The working principle and technical effects of the above technical solution are as follows: This method takes pressure calibration and physiological fit optimization as its core. First, based on the differences in the user's lying and sitting postures, a dedicated pulse characteristic curve database is established to clarify the physiological fit standards under different postures. Then, through airway sealing detection, the working status of the air pump is comprehensively evaluated. Combined with the collected real-time airbag pressure data, the output pressure of the air pump is corrected for deviation, eliminating the dual impact of posture differences and equipment errors. The inflation physiological fit data is obtained by combining the air pump working status with the pressure deviation correction data.

[0111] Example of obtaining the fit state:

[0112] Real-time monitoring of the air pump's operating status (such as current inflation power, running time, and start / stop frequency) and simultaneous retrieval of pressure deviation correction data obtained after calibration with a standard pressure source (such as accurate airbag pressure values ​​after eliminating the effects of sensor drift and airway leakage).

[0113] By combining the preset physiological adaptation pressure range (such as the safe fit pressure range of the airbag for postoperative patients), the real-time correction pressure corresponding to the working state of the air pump is matched with the range.

[0114] If the air pump operates at a stable power, the calibration pressure is maintained within the physiological adaptation range, and the pressure fluctuation range meets the preset requirements, it is determined that the current airbag is in good contact with the human body, and inflation physiological fit data is generated (e.g., good fit, pressure fit 92%).

[0115] If the air pump starts and stops frequently, and the calibration pressure exceeds the upper limit of the adaptation range, it is determined that the fit is too tight, and a fit abnormality is generated simultaneously. It is recommended to reduce the air pump power by 0.2kW and adjust the fit data and instructions accordingly.

[0116] The establishment of a dedicated postural pulse characteristic database makes pressure calibration more closely aligned with individual user physiological characteristics, avoiding adaptation biases caused by universal standards and improving the personalization and accuracy of adjustments. Comprehensive monitoring of the air pump's operating status eliminates potential equipment malfunctions in advance, ensuring the reliability of air pump adjustments, reducing measurement failures or errors caused by equipment problems, and enhancing the stability of the method. Combined with deviation correction based on real-time airbag pressure data, dual optimization of postural adaptation and equipment calibration is achieved, effectively offsetting the combined effects of postural changes and inherent equipment errors, and significantly improving the fit between the inflation process and physiological state. The output inflation physiological fit data makes the final air pump control parameters more targeted.

[0117] In one embodiment of the present invention, deviation correction is performed based on the air pump's operating status and real-time airbag pressure data to obtain pressure deviation correction data, including:

[0118] Based on the airway detection data, identify abnormal data of the air pump and device to obtain device abnormality identification data;

[0119] A multi-dimensional fault diagnosis process is triggered based on the device's anomaly identification data; the multi-dimensional fault diagnosis process includes airway obstruction detection, etc.

[0120] After troubleshooting multiple faults, the pressure is recalibrated using a standard pressure source. The pump speed and pressurization strategy are updated by obtaining the latest parameters from the real-time air pressure feedback data and pulse waveform characteristic curve.

[0121] The working principle and technical effects of the above technical solution are as follows: This method focuses on pressure calibration and repair under abnormal equipment scenarios. Based on air pump airway detection data, it accurately identifies the abnormal type of the air pump and device (such as airway blockage). For different abnormal types, it triggers corresponding multi-dimensional fault diagnosis processes to locate and resolve faults (such as clearing airways) to ensure that the equipment returns to normal working status. After the fault is resolved, the pressure is recalibrated using a standard pressure source to eliminate the pressure measurement deviation caused by the fault. Combining the real-time air pump pressure feedback data and the latest pulse waveform characteristic curve, the air pump inflation speed and pressurization strategy are updated to re-adapt the calibrated pressure output to the user's current physiological state.

[0122] Precise anomaly identification and targeted troubleshooting avoid the time wasted on blind troubleshooting, quickly restore normal equipment operation, and improve the method's self-healing ability and continuity of use. Post-fault recalibration completely eliminates pressure measurement deviations caused by abnormal conditions, ensuring that the equipment maintains high-precision adjustment after recovery and preventing residual faults from affecting subsequent measurements. Updating the pressurization strategy with the latest physiological data ensures that the calibrated pump control not only restores equipment accuracy but also adapts to potential physiological changes during user malfunctions, achieving the dual goals of equipment repair and physiological adaptation. A comprehensive fault handling and calibration mechanism significantly reduces the impact of equipment anomalies on user experience, enhances the reliability and durability of the ambulatory blood pressure measurement device in complex operating environments, and improves product competitiveness.

[0123] In one embodiment of the present invention, S4 includes:

[0124] Information on the trend of physiological changes during the stage is obtained by using inflatable physiological fit data;

[0125] By combining the physiological change trend information of the aforementioned stage with the pressure data obtained in real time by the dynamic blood pressure measurement device, the air pump pressure monitoring results and body position information, the pressure range threshold and adjustment step size are updated during the pressurization process. Based on the updated data, the air pump inflation speed and pressurization timing adjustment commands are triggered to obtain the adjustment update information.

[0126] The working principle and technical effects of the above technical solution are as follows: This method takes the iterative update of pressurization parameters as its core, and extracts the physiological change trend of the user stage (such as changes in pulse rhythm and vascular elasticity fluctuation trend) based on the inflation physiological fit data output by S3; it integrates the pressure data collected in real time by the dynamic blood pressure measurement device, the air pump pressure monitoring results and body position information to construct a trend model of multi-source data fusion; based on this model, it dynamically updates the pressure range threshold and adjustment step size, so that the pressure control adaptation standard is adjusted in real time with the user's physiological changes; according to the updated standard, it triggers the adjustment command of the air pump inflation speed and pressurization timing to realize the iterative optimization of pressurization parameters and ensure that the air pump control always keeps up with the changes in the user's physiological state.

[0127] The extraction and analysis of physiological change trends upgrades air pump control from real-time adaptation to trend prediction adaptation, allowing for advance adjustment of pressurization parameters. This reduces adjustment delays caused by changes in physiological state, improving the foresight and accuracy of control. A trend model based on multi-source data fusion comprehensively considers physiological state, equipment status, and scenario status, avoiding the limitations of single data dimensions and making parameter updates more comprehensive and scientific. Dynamic updates of pressure range thresholds and adjustment step sizes ensure the real-time nature of the adaptation standards, enabling air pump control to continuously adapt to user physiological changes, maintaining precise control even in scenarios with continuously fluctuating physiological states (such as post-exercise recovery or emotional calming periods). An iterative update mechanism for pressurization parameters enables continuous optimization of air pump control, allowing each measurement to further improve adaptation based on previous data, forming a virtuous cycle of measurement, optimization, remeasurement, and further optimization, continuously improving the accuracy of blood pressure measurement and user experience.

[0128] In one embodiment of the present invention, the step of combining physiological state analysis data with air pump fluctuation adjustment data to obtain combined analysis data, and then adjusting the air pump pressure according to the combined analysis data to obtain compensated fit adjustment data, includes:

[0129] The blood pressure measurement module of the dynamic blood pressure measurement device confirms the fit status data of the sensor blood pressure measurement. After the pulse signal is stabilized, the air pump is started to pressurize. The periodic calibration data of pressure calibration is combined with the real-time air pressure detected by the air pump.

[0130] The algorithm extracts the characteristic curve of the pulse waveform and updates it dynamically. Based on the physiological change trend information constructed from multiple sets of data, the pumping speed of the air pump is dynamically adjusted in stages. Simultaneously, the pressure compensation coefficient of different body positions, the power consumption constraint of the battery, and the real-time feedback of the air pump's working status are combined to construct a full-dimensional dynamic pressure range.

[0131] The working principle and technical effects of the above technical solution are as follows: This method focuses on the construction and precise compensation of a full-dimensional dynamic pressure zone. It confirms the fit of the sensor's blood pressure measurement data through the blood pressure measurement module, ensuring the stability of pulse acquisition and avoiding data distortion caused by loose wear. After the pulse signal stabilizes, the air pump is activated for pressurization. Combined with periodic calibration data from pressure calibration and real-time air pressure from the air pump, the basic accuracy of the pressure output is guaranteed. The algorithm extracts and updates the pulse waveform characteristic curve in real time, capturing subtle changes in the user's physiological state. Simultaneously, it integrates pressure compensation coefficients for different body positions, power consumption constraints of the battery, and real-time feedback on the air pump's operating status to construct a full-dimensional dynamic pressure zone under multiple constraints. Based on this zone, the air pump's inflation speed is adjusted in stages, ensuring that each pressurization process accurately adapts to the user's physiological state and the device's operating status.

[0132] The blood pressure fit confirmation mechanism ensures the reliability of pulse data from the source, avoiding adjustment deviations caused by wearing issues. The combination of periodic pressure calibration and real-time air pump pressure feedback provides dual protection for pressure output, significantly reducing inherent device errors and improving the basic accuracy of pressure control. The construction of a full-dimensional dynamic pressure range integrates constraints from physiological, scenario, and device dimensions, breaking the limitations of single-constraint adjustment and enabling air pump control to cope with complex scenarios involving multiple factors. Phased air pump speed adjustment allows for more precise adaptation of the pressurization process to the user's physiological state (e.g., slow adaptation in the initial stage, precise follow-up in the middle stage, and fine-tuning of fit in the stabilization stage), improving measurement accuracy and reducing discomfort during pressurization. This method, as the core support for compensating fit adjustment, further strengthens the linkage control of physiological, device, and scenario states, making the compensation adjustment data more accurate and adaptable, providing high-quality core data support for all subsequent adjustment steps.

[0133] In one embodiment of the present invention, the system includes:

[0134] The fit analysis module is used to determine the optimal detection point by collecting pulse information from multiple detection points of the dynamic blood pressure measurement device, to collect and analyze data on air pump and physiological functions, to obtain compensating fit adjustment data, and to analyze the adjustment of body position changes based on the compensating fit adjustment data to obtain body position air pump adjustment data.

[0135] The optimization analysis module is used to acquire dynamic control strategy information of the air pump, perform control constraint analysis and adjustment, and obtain optimized control strategy information of the air pump; based on the optimized control strategy information of the air pump, it performs pulse characteristic anomaly analysis and adjustment to obtain physiological regulation data of the air pump.

[0136] The fit adjustment module is used to perform pressure calibration and adjustment based on body position air pump adjustment data and abnormal pulse characteristic data to obtain inflatable physiological fit data.

[0137] The fit update module is used to adjust and update the pressure parameters based on the inflation physiological fit data and obtain adjustment and update information.

[0138] The working principle and technical effects of the above-mentioned technical solution are as follows: This method focuses on accurately adapting to the user's physiological changes, and constructs a control logic of multi-dimensional acquisition, layered adjustment, and closed-loop optimization. The optimal pulse acquisition location is determined through multi-detection point screening, and physiological data (pulse waveform) and device data (air pump pressure, airbag pressure) are acquired simultaneously. Preliminary adjustments yield compensation fit adjustment data; then, combined with dynamic adaptation of air pump adjustment parameters to body position changes, body position air pump adjustment data is generated; battery power constraints are introduced to optimize the air pump control strategy, and abnormal pulse characteristics are monitored and dynamically corrected simultaneously; through pressure calibration and iterative updates of pressurization parameters, the entire process of air pump control progresses from basic adaptation to precise fit, ensuring that each adjustment is based on the user's physiological state.

[0139] A multi-source control system integrating physiological data, equipment data, and scenario data was constructed, breaking the limitations of single-parameter adjustment and making the air pump control more closely match the user's real-time physiological state, significantly improving the accuracy of blood pressure measurement. Through a closed-loop process of data acquisition, adjustment, calibration, and updating, dynamic self-adaptation of the air pump control is achieved, which can cope with various complex scenarios such as changes in body position, pulse fluctuations, and power fluctuations, enhancing the versatility and stability of the method. The adjustment logic is broken down into layers (basic data acquisition, body position adaptation, anomaly correction, and parameter update), reducing the impact of errors in a single link on the overall control effect and improving the robustness of the control process. All adjustment actions are based on real-time data feedback, avoiding the problem of asynchronous control between fixed parameters and user physiological changes.

[0140] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for dynamically adjusting the air pump control of a dynamic blood pressure measurement device based on a pulse waveform, characterized by, The method includes: S1. The optimal detection point is determined by collecting pulse information from multiple detection points of the dynamic blood pressure measurement device. Data collection and adjustment analysis of air pump and physiological functions are performed to obtain compensation fit adjustment data. Based on the compensation fit adjustment data, the adjustment analysis of body position changes is performed to obtain body position air pump adjustment data. S2. Obtain dynamic control strategy information of the air pump, perform control constraint analysis and adjustment, and obtain optimized control strategy information of the air pump; perform abnormal pulse characteristic analysis and adjustment based on the optimized control strategy information of the air pump, and obtain physiological regulation data of the air pump. S3. Based on the body position air pump adjustment data and pulse characteristic abnormal data, pressure calibration and adjustment are performed to obtain inflatable physiological fit data. S4. Adjust and update the pressurization parameters based on the inflation physiological fit data to obtain adjustment and update information.

2. The method according to claim 1, wherein S1 includes: The user's blood pressure detection area is determined by the pulse detection sensor built into the dynamic blood pressure measurement device. Multiple pulse detection points are determined based on the user's blood pressure detection area, and pulse data is collected from multiple pulse detection points using a pulse detection sensor to obtain pulse data from multiple detection points. Pulse signal intensity analysis is performed on the pulse data collected from the multiple detection points to obtain pulse signal intensity analysis data; The optimal detection point is determined based on the pulse signal intensity analysis data. Real-time acquisition of pulse waveform signals at the optimal detection point, and real-time acquisition of airbag pressure data through pressure sensors, to obtain real-time pulse waveform acquisition data and real-time airbag pressure data. The air pump pressure is collected in real time by the air pump detection module to obtain air pump pressure data; based on the real-time pulse waveform data, characteristic curve parameters are analyzed to obtain physiological state analysis data. Based on the physiological state analysis data, determine the air pump pressure adjustment parameters, and adjust the air pump pressure according to the air pump pressure adjustment parameters to obtain air pump fluctuation adjustment data. Physiological state analysis data and air pump fluctuation adjustment data are combined and analyzed to obtain combined analysis data. The air pump pressure is then adjusted to compensate for the combined analysis data to obtain compensation fit adjustment data. Based on the compensation and fit adjustment data, the postural changes were adjusted and analyzed to obtain the postural air pump adjustment data. 3.The method of claim 2, wherein, The step of performing postural adjustment analysis based on compensation fit adjustment data to obtain postural air pump adjustment data includes: Postural data is collected by the posture sensing unit built into the dynamic blood pressure measurement device. Based on the changes in body position data, compensation fit adjustment data is obtained by adjusting the fit data. Determine the air pump adjustment parameters based on the fit change data, and adjust the air pump according to the air pump adjustment parameters to obtain air pump adjustment data. Based on the data on changes in air pump adjustment, obtain the air pump adjustment data for different body positions.

4. The air pump control method for a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform according to claim 1, characterized in that, S2 includes: A trend chart of changes in real-time pulse waveform acquisition data was constructed based on physiological state analysis data. Based on the trend chart and the body position air pump adjustment data, determine the dynamic control strategy information for the air pump. Based on the dynamic control strategy information of the air pump, control constraint analysis is performed to obtain control constraint analysis data; Based on the control constraint analysis data, the dynamic control strategy of the air pump is adjusted to obtain the optimized control strategy information of the air pump. Based on the air pump optimization strategy information, pulse characteristic anomaly analysis and adjustment are performed to obtain pulse characteristic anomaly data.

5. The air pump control method for a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform according to claim 4, characterized in that, The step of analyzing and adjusting abnormal pulse characteristics based on the air pump optimization strategy information to obtain air pump physiological regulation data includes: During the adjustment of the air pump, pulse waveform features are extracted from the trend graph to obtain pulse feature extraction data. A dynamic pressure range is constructed by combining air pump optimization control strategy information with pressure calibration data; Anomaly analysis was performed on the pulse feature extraction data based on the dynamic pressure range to obtain abnormal pulse feature data. Based on the abnormal pulse characteristic data, the air pump optimization control strategy information is adjusted to obtain air pump physiological regulation data.

6. The air pump control method for a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform according to claim 2, characterized in that, S3 includes: Establish a database of pulse characteristic curves corresponding to different body positions based on the differences in body position information between lying and sitting positions; Perform an airway sealing test on the air pump to obtain airway test data; Confirm the working status of the air pump based on airway detection data; Based on the air pump's operating status and real-time airbag pressure data, deviation correction is performed to obtain pressure deviation correction data. Inflation physiological fit data is obtained by combining the working status of the air pump with pressure deviation correction data.

7. The air pump control method for a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform according to claim 6, characterized in that, Based on the air pump's operating status and real-time airbag pressure data, deviation correction is performed to obtain pressure deviation correction data, including: Based on the airway detection data, identify abnormal data of the air pump and device to obtain device abnormality identification data; A multi-dimensional fault investigation process is triggered based on device anomaly identification data; After troubleshooting multiple faults, the pressure is recalibrated using a standard pressure source. The pump speed and pressurization strategy are updated by obtaining the latest parameters from the real-time air pressure feedback data and pulse waveform characteristic curve.

8. The air pump control method for a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform according to claim 1, characterized in that, S4 includes: Information on the trend of physiological changes during the stage is obtained by using inflatable physiological fit data; By combining the physiological change trend information of the aforementioned stage with the pressure data obtained in real time by the dynamic blood pressure measurement device, the air pump pressure monitoring results and body position information, the pressure range threshold and adjustment step size are updated during the pressurization process. Based on the updated data, the air pump inflation speed and pressurization timing adjustment commands are triggered to obtain the adjustment update information.

9. The air pump control method for a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform according to claim 2, characterized in that, The step of combining physiological state analysis data with air pump fluctuation adjustment data to obtain combined analysis data, and then adjusting the air pump pressure based on the combined analysis data to obtain compensated fit adjustment data, includes: The blood pressure measurement module of the dynamic blood pressure measurement device confirms the fit status data of the sensor blood pressure measurement. After the pulse signal is stabilized, the air pump is started to pressurize. The periodic calibration data of pressure calibration is combined with the real-time air pressure detected by the air pump. The characteristic curves of the pulse waveform are extracted and dynamically updated. Based on the physiological change trend information constructed from multiple sets of data, the air pump speed is dynamically adjusted in stages. Simultaneously, the pressure compensation coefficients for different body positions, the power consumption constraints of the battery, and the real-time feedback of the air pump's working status are combined to construct a full-dimensional dynamic pressure range.

10. A pump control system for a dynamic blood pressure measurement device based on dynamic adjustment of pulse waveform, characterized in that, The system includes: The fit analysis module is used to determine the optimal detection point by collecting pulse information from multiple detection points of the dynamic blood pressure measurement device, to collect and analyze data on air pump and physiological functions, to obtain compensating fit adjustment data, and to analyze the adjustment of body position changes based on the compensating fit adjustment data to obtain body position air pump adjustment data. The optimization analysis module is used to acquire dynamic control strategy information of the air pump, perform control constraint analysis and adjustment, and obtain optimized control strategy information of the air pump; based on the optimized control strategy information of the air pump, it performs pulse characteristic anomaly analysis and adjustment to obtain physiological regulation data of the air pump. The fit adjustment module is used to perform pressure calibration and adjustment based on body position air pump adjustment data and abnormal pulse characteristic data to obtain inflatable physiological fit data. The fit update module is used to adjust and update the pressure parameters based on the inflation physiological fit data and obtain adjustment and update information.

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