Intelligent management method and system for intelligent blood pressure cuff

Abstract

An intelligent management method and system for an intelligent blood pressure cuff, relating to the field of data processing technology. The method comprises: obtaining the arm pressure distribution data and arm shape data of the target user; based on the arm pressure distribution data, calculating the fit between multiple segmented areas in the blood pressure cuff and the user's arm; according to the arm shape data, determining the target cuff length and target bending angle corresponding to each segmented area in the blood pressure cuff; for each segmented area, when the difference between the fit between the segmented area and the user's arm and the standard fit is greater than the fit difference threshold, adjusting the blood pressure cuff in combination with the target cuff length and target bending angle corresponding to the segmented area. The implementation of the technical solution provided in the present application achieves the effect of improving the management efficiency of the blood pressure cuff.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and specifically to an intelligent management method, system, electronic device and storage medium for an intelligent blood pressure cuff. Background Art

[0002] As people pay more and more attention to health management, blood pressure monitoring has become one of the basic health indicator detection methods. As the most commonly used blood pressure monitoring equipment, the performance of the blood pressure cuff, the core component of the sphygmomanometer, directly affects the accuracy of blood pressure measurement. Nowadays, how to manage the blood pressure cuff has become an important issue to improve the effect of blood pressure monitoring.

[0003] At present, the existing management methods for blood pressure cuffs mainly rely on using a blood pressure cuff of uniform specifications to wrap around the user's arm for blood pressure measurement. However, in actual applications, due to the large differences in arm shapes of different users, it is often difficult to make adaptive adjustments to the arm shapes of different users by only using a blood pressure cuff of uniform specifications, resulting in uneven fit between the arm and the blood pressure cuff during the measurement process, which requires repeated adjustments, resulting in low management efficiency of the blood pressure cuff. Summary of the invention

[0004] The present application provides an intelligent management method and system for an intelligent blood pressure cuff, which has the effect of improving the management efficiency of the blood pressure cuff.

[0005] In a first aspect, the present application provides an intelligent management method for an intelligent blood pressure cuff, comprising:

[0006] Obtaining arm pressure distribution data and arm shape data of the target user;

[0007] Based on the arm pressure distribution data, calculating the fit between multiple segmented areas in the blood pressure cuff and the user's arm;

[0008] Determining, according to the arm shape data, a target cuff length and a target bending angle corresponding to each segmented area in the blood pressure cuff;

[0009] For each of the segmented areas, when the difference between the degree of fit between the segmented area and the user's arm and the standard degree of fit is greater than a fit difference threshold, the blood pressure cuff is adjusted in combination with the target cuff length and target bending angle corresponding to the segmented area.

[0010] In a second aspect of the present application, an intelligent management system for an intelligent blood pressure cuff is provided, the system comprising:

[0011] A data acquisition module, used to acquire arm pressure distribution data and arm shape data of a target user;

[0012] A fit calculation module, used to calculate the fit between the multiple segmented areas in the blood pressure cuff and the user's arm based on the arm pressure distribution data;

[0013] A parameter determination module, used for determining a target cuff length and a target bending angle corresponding to each segmented area in the blood pressure cuff according to the arm shape data;

[0014] The cuff adjustment module is used to adjust the blood pressure cuff in combination with the target cuff length and target bending angle corresponding to the segmented area when the difference between the fit between the segmented area and the user's arm and the standard fit is greater than the fit difference threshold.

[0015] In a third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and a program stored in the memory and executable on the processor, wherein the program can implement an intelligent management method for an intelligent blood pressure cuff when loaded and executed by the processor.

[0016] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements an intelligent management method for an intelligent blood pressure cuff.

[0017] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0018] By adopting the above technical solution, the arm pressure distribution data and arm shape data are collected, and the actual fit between each segmented area and the arm is calculated by combining the arm pressure distribution data and the arm shape data. The system can accurately identify the area with abnormal fit, avoiding the measurement error caused by uneven fit of the traditional blood pressure cuff. When the system detects that the difference between the fit of a segmented area and the standard fit exceeds the threshold, it will make precise adjustments based on the target cuff length and target bending angle corresponding to the area. This differentiated adjustment method for different regions enables the blood pressure cuff to better adapt to the local morphological characteristics of the arm. By precisely controlling the length and bending angle of each segmented area, the blood pressure cuff can be dynamically adjusted in the entire measurement area to adapt to different user arms, avoiding the problem of fixed-specification blood pressure cuffs not fitting the user's arm and requiring repeated adjustments, thereby improving the management efficiency of the blood pressure cuff. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a flow chart of a smart management method for a smart blood pressure cuff provided in an embodiment of the present application;

[0020] Figure 2It is a structural schematic diagram of an intelligent management system for an intelligent blood pressure cuff provided in an embodiment of the present application;

[0021] Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0022] Description of reference numerals: 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0023] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0024] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0025] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0026] The present application embodiment provides an intelligent management method for an intelligent blood pressure cuff. In one embodiment, please refer to Figure 1 , Figure 1 This is a flow chart of the intelligent management method for a smart blood pressure cuff provided by an embodiment of the present application. The method can be implemented by a computer program, which can be integrated into an application or run as an independent tool application. The method can also be implemented by a single-chip microcomputer or run on an intelligent management system for a smart blood pressure cuff based on a von Neumann system. Specifically, the method can include the following steps:

[0027] Step 101: Obtain arm pressure distribution data and arm shape data of a target user.

[0028] Among them, the arm pressure distribution data refers to the collective data of the pressure values ​​at different positions on the contact surface between the blood pressure cuff and the arm when the blood pressure cuff is attached to the surface of the user's arm. These pressure values ​​are collected in real time by multiple pressure sensors set on the blood pressure cuff, and each pressure value corresponds to a specific measurement point on the blood pressure cuff. These pressure sensors are distributed in an array around the circumference of the blood pressure cuff, which can fully reflect the contact pressure distribution between the blood pressure cuff and the arm.

[0029] Arm shape data refers to the three-dimensional geometric feature data of the outer surface of the user's arm. These data fully describe the spatial contour, curvature change and local features of the arm surface. These shape data are collected by the three-dimensional scanning device integrated in the blood pressure cuff. The device uses the principle of infrared light emission and reception to obtain the depth information of each point on the arm surface by measuring the time difference from light emission to reception, thereby constructing a complete arm surface contour.

[0030] Specifically, the arm pressure distribution data and arm shape data of the target user are first obtained. Among them, a plurality of pressure sensors are arranged on the blood pressure cuff, and these pressure sensors are evenly distributed along the circumference of the blood pressure cuff. When the blood pressure cuff is wrapped around the user's arm, the pressure sensor can detect the contact pressure between the blood pressure cuff and the arm in real time, and transmit the detected pressure data as the arm pressure distribution data to the control module. At the same time, the blood pressure cuff is also integrated with a three-dimensional scanning device, which includes an infrared transmitter and an infrared receiver, and obtains the depth information of the user's arm surface by emitting infrared light and receiving reflected light, thereby constructing the three-dimensional contour data of the arm, that is, the arm shape data. The arm shape data obtained in this way can accurately reflect the actual shape characteristics of the user's arm, including information such as the circumference change of the arm and the surface undulation. In actual application, when the user wraps the blood pressure cuff around the arm and starts the blood pressure measurement function, the pressure sensor and the three-dimensional scanning device will start working synchronously. The data collected by the pressure sensor can reflect the real-time fitting state between the blood pressure cuff and the arm, and the data collected by the three-dimensional scanning device can provide a shape reference for subsequent intelligent adjustment. The combined use of these two types of data can fully reflect the actual use status of the blood pressure cuff and provide a reliable data basis for subsequent precise adjustment. After receiving this data, the control module will perform data preprocessing, including noise filtering, data smoothing and other operations to ensure the accuracy of subsequent calculations. The arm pressure distribution data and arm shape data obtained in this way are real-time and accurate, and can provide a reference for the intelligent adjustment of the blood pressure cuff.

[0031] Step 102: Based on the arm pressure distribution data, calculate the fit between the multiple segmented areas in the blood pressure cuff and the user's arm.

[0032] The segmented area refers to the several independently controllable areas formed by dividing the blood pressure cuff along its circumference and axis. Each segmented area contains an independent pressure sensor and drive mechanism, which can achieve localized shape adjustment and pressure control. The division of these segmented areas is determined based on the overall structural characteristics of the blood pressure cuff and the distribution of the pressure sensors. The size and shape of each segmented area are optimized to ensure that it can adapt to the local morphological changes on the arm surface.

[0033] Fit refers to the quantitative index of the actual contact state between a specific segmented area of ​​the blood pressure cuff and the user's arm. This index reflects the quality of the fit between the blood pressure cuff and the arm surface in the local area. Fit is obtained by calculating the ratio of the number of measurement points in the segmented area whose pressure values ​​fall within the standard pressure range to the total number of measurement points in the area. This standard pressure range is the pressure range required to ensure the accuracy of blood pressure measurement.

[0034] A blood pressure cuff refers to an adjustable medical measuring device, which is composed of a plurality of independently controllable segmented areas, each of which is integrated with a pressure sensor and a length and angle adjustment mechanism. The blood pressure cuff can be adaptively adjusted according to the actual shape of the user's hand to achieve intelligent covering of the arm. In the embodiment of the present application, it can be understood that the blood pressure cuff is an intelligent pressure measurement system, whose structure includes an outer fabric, a built-in inflatable bag, a pressure sensor network, and a distributed adjustment actuator. The blood pressure cuff is also provided with a plurality of retractable elastic fibers and intelligent sensors. Each segmented area can independently control its length and bending angle. For example, a segmented area can adjust the length within the range of 240 mm to 260 mm, and adjust the bending angle within the range of 0 degrees to 90 degrees. Through this segmented adjustable design, the blood pressure cuff can accurately adapt to the arm shape characteristics of different users.

[0035] Specifically, after obtaining the arm pressure distribution data, the control module needs to calculate the fit between each segmented area of ​​the blood pressure cuff and the user's arm. This calculation process is the key link to achieve intelligent adjustment. Specifically, the control module first groups the acquired arm pressure distribution data according to the preset segmented areas, and each segmented area corresponds to an independent control unit on the blood pressure cuff. For each segmented area, the control module counts the number of measurement points whose pressure values ​​fall within the standard pressure range in the area, as well as the total number of measurement points in the area, and the fit of the segmented area can be obtained by calculation. For example, when there are 16 pressure measurement points in a segmented area, and the pressure values ​​of 14 measurement points fall within the standard pressure range, the fit of the area is 0.875. This fit calculation method based on segmented areas can accurately locate the specific area where the fit problem is located. Through the quantitative fit index, the system can accurately judge the necessity and urgency of adjustment. When the fit of a segmented area is lower than the preset threshold, the system will immediately start the corresponding adjustment mechanism to ensure that a good fit is always maintained during the blood pressure measurement process, thereby improving the accuracy and reliability of blood pressure measurement.

[0036] Based on the above embodiment, as an optional embodiment, in step 102: calculating the fit between the multiple segmented areas in the blood pressure cuff and the user's arm based on the arm pressure distribution data, this step may also include the following steps:

[0037] Step 201: Divide the blood pressure cuff into a plurality of segmented areas of preset specifications; and determine the pressure measurement values ​​corresponding to a plurality of measurement points in each segmented area according to the arm pressure distribution data.

[0038] The measurement point refers to the actual installation location of the pressure sensor on the blood pressure cuff. Each measurement point can collect and output the real-time pressure value between the blood pressure cuff and the user's arm at that location. These measurement points are arranged on the surface of the blood pressure cuff according to a preset distribution pattern to form a pressure collection network for comprehensive monitoring of the pressure distribution state between the cuff and the arm.

[0039] The pressure measurement value refers to the actual pressure value collected at each measuring point on the blood pressure cuff, which reflects the contact pressure between the blood pressure cuff and the user's arm at a specific location. The pressure measurement value is a numerical signal converted from physical pressure into standard units by the pressure sensor at the measuring point.

[0040] Specifically, in order to achieve precise fit control of the blood pressure cuff, the blood pressure cuff must first be divided into multiple independently controllable segmented areas. Specifically, the control module divides the blood pressure cuff into M×N segmented areas along the circumferential and axial directions according to preset specifications, and the size of each segmented area is determined according to the overall size of the blood pressure cuff and the distribution density of the pressure sensor. For example, when the circumferential length of the blood pressure cuff is 240mm and the axial width is 120mm, it can be evenly divided into 4×2 segmented areas, so that the size of each segmented area is 60mm×60mm. After completing the segmented area division, the control module will process the acquired arm pressure distribution data and establish a mapping relationship between the pressure measurement value and the corresponding segmented area. According to the actual installation position of the pressure sensor on the blood pressure cuff, the system can determine the segmented area to which each pressure measurement value belongs. In this way, the control module can obtain a set of pressure measurement values ​​of all measurement points in each segmented area. For example, when four pressure sensors are set in a segmented area, the pressure measurement value set corresponding to the area contains four values, which reflect the actual contact status between the blood pressure cuff and the arm in the area. This data division and processing method based on segmented areas lays the foundation for subsequent fit calculation and intelligent adjustment.

[0041] Step 202: For each segmented area, determine the number of measurement points whose pressure measurement values ​​are within the standard pressure range and the total number of the plurality of measurement points in the segmented area.

[0042] The standard pressure range refers to the ideal pressure range that the blood pressure cuff needs to maintain during measurement. This range is the pressure value range determined according to medical device standards and clinical practice. Specifically, this range needs to ensure the accuracy of blood pressure measurement while avoiding discomfort to the user or measurement errors.

[0043] Specifically, in order to accurately evaluate the fit status of each segmented area, the control module needs to analyze and count the pressure measurements in each segmented area. First, the system sets the standard pressure range according to the medical device standard, which is usually defined as an interval value. Then, the control module will traverse all measurement points in each segmented area and compare the pressure measurement value obtained at each measurement point with the standard pressure range. For each segmented area, two key values ​​are counted: one is the number of measurement points in the area whose pressure measurement values ​​fall within the standard pressure range, and the other is the total number of measurement points in the area. For example, there are 8 measurement points in a segmented area, of which the pressure measurement values ​​of 6 measurement points are within the standard pressure range. The number of measurement points in the area is 6 and the total number is 8. The control module will perform such statistics on all segmented areas of the blood pressure cuff to form a complete pressure distribution state data set. This statistical method can effectively reflect the uniformity of pressure distribution in each segmented area and provide an accurate data basis for subsequent calculation of fit.

[0044] Step 203: Calculate the ratio between the number of measurement points whose pressure measurement values ​​are within the standard pressure range and the total number of multiple measurement points in the segmented area, and use the ratio as the fit between the segmented area and the user's arm.

[0045] Specifically, in order to quantify the fit status of each segmented area of ​​the blood pressure cuff into a specific numerical index, the control module needs to calculate the fit degree based on the above statistical data. The control module calculates a ratio between 0 and 1 by dividing the number of measurement points whose pressure measurement values ​​are within the standard pressure range by the total number of measurement points in the segmented area, and uses the ratio as the fit degree of the segmented area. During the calculation process, the control module performs the same calculation method for each segmented area. For example, there are 8 measurement points in a segmented area, and the pressure measurement values ​​of 6 measurement points are within the standard pressure range. The fit degree of the area is 6 / 8=0.75. Through this calculation method, the system can obtain the fit value of all segmented areas of the blood pressure cuff to form a complete fit state distribution diagram. When the fit degree of a segmented area is close to 1, it means that the pressure distribution between the area and the arm is relatively uniform and ideal; when the fit degree is low, it means that the area may have uneven pressure distribution or insufficient fit. This fit evaluation method based on proportional calculation is simple and effective. It can not only accurately reflect the actual fit status of each segmented area, but also provide a clear quantitative basis for subsequent intelligent adjustment. The system can determine whether to start the adjustment mechanism based on the fit value of each area and accurately calculate the required adjustment amount, thereby ensuring that a good fit is always maintained during blood pressure measurement.

[0046] Step 103: Determine the target cuff length and target bending angle corresponding to each segmented area in the blood pressure cuff according to the arm shape data.

[0047] The target cuff length refers to the ideal length that each segment of the blood pressure cuff should reach when it fits the user's arm. This length is the optimal fitting length calculated based on the arm shape data. The target cuff length needs to take into account factors such as arm circumference, preload requirements, and pressure requirements during the measurement phase.

[0048] The target bending angle refers to the ideal bending degree that each segment of the blood pressure cuff should achieve when fitting the user's arm. This angle value is the optimal fitting angle calculated based on the curvature characteristics of the arm's cross-sectional profile. The target bending angle needs to take into account factors such as the local curvature of the arm surface, muscle contours, and anatomical characteristics of the measurement location.

[0049] Specifically, in order to make the blood pressure cuff better adapt to the actual shape of the user's arm, the control module needs to calculate the most suitable target cuff length and target bending angle for each segmented area based on the acquired arm shape data. The arm shape data contains the circumference and cross-sectional profile information of the user's arm, which is an important basis for determining the cuff adjustment parameters. The control module first calculates the target cuff length required for each segmented area of ​​the blood pressure cuff based on the arm circumference data. Since the human arm is truncated, the circumference at different heights is different, so the target length of each segmented area needs to be calculated separately. For example, when the arm circumference corresponding to a segmented area is 250mm, considering that the appropriate pressure needs to be maintained during measurement, the target cuff length of the area may need to be set to 240mm to ensure sufficient preload. At the same time, the control module also needs to calculate the target bending angle that each segmented area needs to achieve based on the arm cross-sectional profile data. The cross section of the arm is not completely circular and may present different curvatures at different positions, so each segmented area needs to determine the appropriate bending angle based on the curvature characteristics of its corresponding position. For example, when the radius of curvature of the arm surface corresponding to a segmented area is 40 mm, the target bending angle of the area may need to be set to 45 degrees to ensure that the blood pressure cuff can fit tightly against the arm surface. This parameter calculation method based on the arm shape characteristics enables the blood pressure cuff to more accurately adapt to the individual differences of the user's arm. By setting independent target cuff lengths and target bending angles for each segmented area, the system can achieve more precise fit control and improve the comfort and accuracy of blood pressure measurement.

[0050] Based on the above embodiment, as an optional embodiment, in step 103: determining the target cuff length and target bending angle corresponding to each segmented area in the blood pressure cuff according to the arm shape data, this step may also include the following steps:

[0051] Step 301: construct a three-dimensional arm model based on the arm shape data.

[0052] The 3D arm model refers to a digital arm surface model built based on actual measurement data, which describes the three-dimensional morphological characteristics of the user's arm in the form of mathematical equations and geometric parameters. This model contains complete geometric information of the arm surface, such as local curvature, cross-sectional profile, spatial coordinates and other key parameters.

[0053] Specifically, in order to accurately obtain the three-dimensional structural characteristics of the user's arm, the control module needs to build a complete three-dimensional arm model based on the collected arm shape data. This three-dimensional model will serve as the basis for calculating the blood pressure cuff adjustment parameters, so that the system can more comprehensively understand and adapt to the actual shape of the user's arm. The control module first processes and integrates the collected arm shape data. These data include the circumference data of the arm at different heights, the cross-sectional profile data, and the spatial coordinate information of key anatomical feature points. Through mathematical modeling methods, the system converts these discrete measurement data points into continuous surface equations to construct a three-dimensional digital model that can accurately reflect the arm's morphological characteristics. For example, the system can use a spline interpolation algorithm to fit the contour curve of the arm surface, and then generate a complete three-dimensional surface model by rotation scanning. This three-dimensional model constructed based on measured data can accurately reflect the individual characteristics of the arm, including detailed features such as muscle bulges and bone bumps. Through this precise digital model, the system can extract the local morphological parameters of the arm at any position, providing a more accurate reference for the segmented adjustment of the blood pressure cuff.

[0054] Based on the above embodiment, as an optional embodiment, in step 301: constructing a three-dimensional arm model according to the arm shape data, this step may also include the following steps:

[0055] Step 311: extract multiple feature points of the user's arm from the arm shape data.

[0056] Among them, feature points refer to locations on the surface of the user's arm with significant geometric or anatomical features, which can reflect the key morphological characteristics and structural changes of the arm. Feature points include the spatial coordinate information of key locations such as local curvature extreme points, anatomical landmarks, and morphological mutation points on the arm surface.

[0057] Specifically, in order to accurately identify and analyze the key morphological features of the user's arm, the control module needs to extract multiple feature points from the collected arm shape data. These feature points are locations on the arm surface with significant geometric or anatomical features, and they are of great guiding significance for building an accurate three-dimensional model of the arm. First, the arm shape data is feature analyzed, and the key locations on the arm surface are located through curvature detection and morphological feature recognition algorithms. The system focuses on anatomical landmarks on the arm, such as muscle contour feature points such as the highest point of the biceps brachii and the deltoid muscle bulge, as well as bone feature points such as the elbow joint process. In each area of ​​interest, the system accurately locates the spatial coordinates of the feature points by analyzing the gradient changes and curvature distribution of the local shape data. For example, when it is detected that the surface curvature of a certain position suddenly changes significantly, and the change has a certain spatial persistence, the system will mark the position as a feature point. This feature point-based morphological analysis method enables the system to better understand and describe the three-dimensional structural features of the arm. Through the spatial distribution information of these feature points, the system can more accurately divide different areas of the arm, providing a reliable reference benchmark for subsequent three-dimensional model construction.

[0058] Step 321: calibrate the spatial coordinates of each feature point to obtain the spatial coordinates corresponding to each feature point.

[0059] Specifically, in order to accurately describe the spatial position information of the arm feature points, the control module needs to calibrate the spatial coordinates of each extracted feature point. This calibration process can convert the position information of the feature points into standard three-dimensional coordinate data, providing an accurate spatial reference for subsequent model construction. First, a unified spatial coordinate system is established, and a rectangular coordinate system is established with a fixed reference position of the arm as the origin. For example, the center of the elbow joint can be selected as the coordinate origin, the z-axis can be determined along the axial direction of the arm, the y-axis can be determined perpendicular to the surface of the arm, and the x-axis direction can be determined from this. In this unified coordinate system, the system converts the position information of each feature point into the corresponding three-dimensional coordinate value through a spatial position solution algorithm. For each feature point, the system calculates its spatial distance and direction angle relative to the origin to obtain accurate spatial coordinate data. This spatial calibration method based on a unified coordinate system enables the system to describe and store the position information of feature points in a standardized form. Through accurate coordinate data, the system can reconstruct the spatial relationship between feature points and provide key geometric information for building a complete three-dimensional model of the arm.

[0060] Step 331: Generate a mesh surface based on the spatial coordinates of each feature point; perform surface smoothing on the mesh surface to obtain a three-dimensional model of the arm.

[0061] The mesh surface refers to a discretized geometric surface composed of multiple triangular facets. These triangular facets are connected together by sharing vertices and edges to form a complete surface mesh structure, which is used to approximate the continuous surface shape of the arm. Each triangular facet consists of three vertices and three edges. The position of the vertex is determined by the three-dimensional space coordinates, and the edge represents the connection relationship between adjacent vertices.

[0062] Specifically, in order to build a three-dimensional model that accurately reflects the user's arm shape, the control module needs to realize the digital reconstruction of the arm shape through two key steps, mesh surface generation and smoothing, based on the calibrated spatial coordinates of the feature points. This three-dimensional reconstruction method based on feature points can effectively capture the detailed features of the arm and provide a reliable morphological reference for the precise adjustment of the blood pressure cuff. First, the initial mesh surface is constructed based on the spatial coordinates of the feature points. The system uses a triangular meshing method to connect adjacent feature points to form triangular facets, and constructs a mesh structure that characterizes the arm surface through the combination of these triangular facets. During the mesh generation process, the system dynamically adjusts the mesh density according to the distribution density of the feature points, and uses denser meshing in areas with obvious morphological changes to better describe local detail features. After the initial mesh surface is generated, the system needs to perform surface smoothing on it to eliminate local discontinuities and mutations that may be caused by meshing. The control module uses the Laplace smoothing algorithm to achieve a smooth transition between adjacent facets by adjusting the positions of the mesh vertices. During the smoothing process, the system keeps the position of the feature points fixed and only adjusts other mesh vertices, which can ensure the smoothness of the model and retain the key morphological features of the arm. At the same time, the system will control the number of smoothing iterations to avoid excessive smoothing that may lead to the loss of important detail features.

[0063] Step 302: extracting the contour curve corresponding to each segmented area in the three-dimensional arm model.

[0064] The contour curve refers to the transverse cross-sectional curve at a specific height position in the three-dimensional model of the arm, which accurately describes the circumferential shape characteristics of the arm at that position. The contour curve reflects the local geometric characteristics of the arm surface, including curvature changes, bumps and other detailed information.

[0065] Specifically, in order to accurately obtain the arm surface features corresponding to each segmented area of ​​the blood pressure cuff, the control module needs to extract the corresponding contour curve information from the constructed three-dimensional model of the arm. These contour curves can accurately reflect the cross-sectional shape and curvature changes of the arm at a specific height position, and are the direct basis for calculating the target cuff length and target bending angle. The control module first determines the spatial position range of each segmented area in the three-dimensional model of the arm, and then performs a horizontal interception at the center position of each segmented area to obtain the contour curve equation of the position. For example, for a segmented area located in the middle of the upper arm, the system can obtain a closed contour curve by performing a plane interception at this height. In this way, the system can obtain a set of contour curves corresponding to all segmented areas of the blood pressure cuff. This method of extracting contour curves based on a three-dimensional model enables the system to accurately grasp the target surface shape that each segmented area needs to fit. By analyzing the geometric features of the contour curve, such as parameters such as curve length and local curvature, the system can calculate the optimal adjustment parameters for each segmented area.

[0066] Step 303: For the contour curve corresponding to each segmented area, the arc length of the contour curve is calculated and used as the target cuff length of the segmented area; the tangent angle between the contour curve and the adjacent contour curve is calculated and used as the target bending angle of the segmented area.

[0067] The arc length refers to the actual length of the contour curve from the starting point to the end point, which reflects the true circumference of the arm at a specific height. The arc length is the integral value of the infinitesimal line segment length on the contour curve, which takes into account all local bends and undulations of the curve.

[0068] The tangent angle refers to the angle between the tangent vectors of two adjacent contour curves at corresponding positions. This angle reflects the degree of spatial curvature of the arm surface between adjacent segmented areas. The tangent angle describes the change in curvature of the arm surface in the longitudinal direction, reflecting the curvature characteristics when transitioning from one cross section to the adjacent cross section.

[0069] Specifically, in order to accurately control the adjustment parameters of each segmented area of ​​the blood pressure cuff, the control module needs to calculate the target cuff length and target bending angle based on the extracted contour curve. These adjustment parameters directly determine whether the blood pressure cuff can accurately fit the arm surface, which has an important impact on the accuracy of the measurement. The control module traverses the contour curve corresponding to each segmented area and calculates the arc length of the curve using a numerical integration method. During the calculation, the contour curve is divided into several small segments, and the lengths of these segments are accumulated to obtain complete circumference data. This arc length data reflects the actual circumference of the arm at this position, and the system directly sets it as the target cuff length of the segmented area. The rationality of this setting is that when the blood pressure cuff is adjusted to a length equal to the circumference of the arm, it can ensure sufficient fit without generating excessive preload. At the same time, the control module also needs to calculate the target bending angle of each segmented area. The system selects two adjacent contour curves and calculates their tangent directions at the corresponding positions. By calculating the angle between the two tangent directions, the spatial curvature of the arm surface in this area is obtained. This tangent angle accurately reflects the three-dimensional curvature of the arm surface, and the system sets it as the target curvature angle of the segmented area. This setting method ensures that the blood pressure cuff can accurately match the natural curvature of the arm after adjustment. This parameter calculation method based on contour curve characteristics establishes a direct mapping relationship between the arm shape characteristics and the blood pressure cuff adjustment parameters. By converting the actual measured geometric features into specific adjustment parameters, the system can accurately control the state of each segmented area, so that the blood pressure cuff can achieve the best fit.

[0070] Step 104: For each segmented area, when the difference between the degree of fit between the segmented area and the user's arm and the standard degree of fit is greater than the fit difference threshold, the blood pressure cuff is adjusted in combination with the target cuff length and target bending angle corresponding to the segmented area.

[0071] Specifically, to ensure the accuracy of blood pressure measurement, the control module needs to monitor and dynamically adjust the fit state of each segmented area in real time. When the actual fit between a segmented area and the arm deviates too much from the standard fit, the system needs to accurately adjust the blood pressure cuff according to the pre-calculated target parameters to achieve the best measurement conditions. First, the actual fit data of each segmented area is obtained in real time through the sensor, and it is compared with the preset standard fit. When it is detected that the fit difference of a segmented area exceeds the threshold set by the system, it indicates that the fit state of the area can no longer meet the measurement requirements and needs to be adjusted. For example, when the actual fit of a segmented area is 85%, the standard fit is 95%, and the fit difference threshold is 5%, the system will start the adjustment program because the actual difference of 10% exceeds the threshold. When adjusting, the control module will control the actuator at the same time according to the target cuff length and target bending angle pre-calculated for the segmented area. The system first adjusts the cuff length, and gradually makes the cuff length in this area approach the target value through the telescopic mechanism. At the same time, the spatial bending angle of this area is adjusted through the bending mechanism to match the target bending angle. This dual-parameter coordinated adjustment method can ensure that the blood pressure cuff always accurately follows the arm contour during the adjustment process. This dynamic adjustment method based on the difference in fit enables the blood pressure cuff to actively adapt to subtle changes in the arm shape. Through real-time monitoring and timely adjustment, the system can always maintain an ideal fit and effectively avoid uneven pressure distribution caused by poor fit during the measurement process.

[0072] Based on the above embodiment, as an optional embodiment, in step 104: adjusting the blood pressure cuff in combination with the target cuff length and target bending angle corresponding to the segmented area, this step may also include the following steps:

[0073] Step 401: Determine the longitudinal expansion amount corresponding to the expandable elastic fibers in the blood pressure cuff according to the target cuff length.

[0074] Among them, stretchable elastic fiber refers to a special fiber material with good elastic deformation ability. This material has controllable stretching characteristics and stable mechanical properties. It can produce reversible deformation under the action of external force and return to its original state after the external force is removed. This fiber material is usually made of polymer elastomers and has a clear stress-strain relationship and predictable deformation behavior. The blood pressure cuff is embedded with stretchable elastic fibers. By sensing the contour and pressure distribution of the arm, the data is transmitted to the microprocessor. The microprocessor controls the expansion and contraction of the elastic fiber according to the received data to achieve automatic adjustment of the cuff size.

[0075] Longitudinal stretch refers to the change in length of the stretchable elastic fiber in the longitudinal direction, which indicates the displacement of the fiber from the initial length state to the target length state. This value can be positive (indicating elongation) or negative (indicating contraction), reflecting the degree of deformation of the elastic fiber in the axial direction.

[0076] Specifically, in order to achieve accurate adjustment of the blood pressure cuff length, the control module needs to convert the target cuff length into the specific amount of expansion and contraction of the retractable elastic fiber. This parameter conversion process ensures the accuracy of cuff adjustment and enables the system to achieve the expected cuff length by controlling the expansion and contraction state of the elastic fiber. First, based on the structural characteristics of the blood pressure cuff, the corresponding relationship between the target cuff length and the expansion and contraction amount of the elastic fiber is established. Since the retractable elastic fiber is arranged longitudinally in the cuff, its expansion and contraction deformation directly determines the overall length of the cuff. The system calculates the amount of elastic fiber expansion and contraction required to adjust the cuff to the target length through the pre-calibrated elastic coefficient and stress-strain relationship. For example, when the cuff length of a certain segmented area needs to be increased by 20 mm, the system will accurately calculate the longitudinal expansion and contraction required to achieve this length change based on the material properties and initial state of the elastic fiber. This parameter conversion method based on elastic properties enables the system to convert the abstract target length into specific execution parameters. By establishing an accurate parameter mapping relationship, the system can accurately control the expansion and contraction state of the elastic fiber in each segmented area, thereby achieving accurate adjustment of the cuff length.

[0077] Step 402: Determine the lateral expansion and contraction amount corresponding to the expandable elastic fibers in the blood pressure cuff according to the target bending angle.

[0078] The transverse expansion refers to the deformation of the elastic fiber in the direction perpendicular to its axis, which indicates the magnitude of the transverse displacement of the fiber when it is bent. This value can also be positive (indicating expansion to the outside) or negative (indicating contraction to the inside), reflecting the degree of deformation of the elastic fiber in the transverse direction.

[0079] Specifically, in order to achieve precise bending deformation of the blood pressure cuff, the control module needs to convert the target bending angle into the lateral expansion and contraction of the retractable elastic fiber. This angle-to-expansion conversion process ensures the accuracy of the cuff bending adjustment, enabling the system to achieve the expected spatial bending effect by controlling the lateral deformation of the elastic fiber. First, based on the geometric relationship, a mapping relationship between the target bending angle and the lateral expansion and contraction of the elastic fiber is established. Since the inner fiber of the blood pressure cuff needs to contract and the outer fiber needs to stretch during the bending process, the system calculates the lateral expansion and contraction required to achieve the target bending angle through the spatial distribution characteristics and bending deformation principle of the elastic fiber. For example, when a segmented area needs to produce a 30-degree bending angle, the system will accurately calculate the differentiated lateral deformation required for the inner and outer fibers based on the width of the area and the arrangement density of the elastic fiber. During the calculation process, the system takes into account the deformation characteristics and stress distribution law of the elastic fiber to ensure that the calculation results can achieve the expected bending effect. This parameter conversion method based on geometric relationships enables the system to convert abstract angle requirements into specific execution parameters. By establishing an accurate angle-extension correspondence, the system can precisely control the lateral deformation state of the elastic fibers in each segmented area, thereby achieving precise adjustment of the cuff bending angle.

[0080] Step 403: Based on the longitudinal expansion and lateral expansion, the stretchable elastic fibers corresponding to the segmented areas in the blood pressure cuff are adjusted.

[0081] Specifically, in order to achieve precise adjustment of the blood pressure cuff, the control module needs to simultaneously control the longitudinal and lateral deformation of the retractable elastic fibers. This two-way coordinated adjustment method can ensure that the blood pressure cuff reaches both the target length and the expected bending angle, so as to accurately fit the morphological characteristics of the user's arm. First, according to the calculated longitudinal and lateral expansion amounts, the retractable elastic fibers in the segmented area are precisely controlled by the execution component. During the adjustment process, the system adopts a step-by-step collaborative strategy, first controlling the longitudinal expansion to adjust the cuff length, and then applying lateral control to achieve bending deformation. For example, when a segmented area needs to increase the length by 20 mm and form a 30-degree bending angle, the system first controls the elastic fibers in the area to produce a longitudinal extension of 20 mm, and then through differential control, the outer fibers produce a lateral expansion of 2 mm and the inner fibers produce a lateral contraction of 1.5 mm, thereby forming the expected spatial form. During the entire adjustment process, the control module monitors the actual deformation state of each elastic fiber through a real-time feedback system to ensure that its deformation always meets the expected requirements. The system adopts a closed-loop control strategy to dynamically adjust the control parameters according to the feedback data, compensate for possible errors, and ensure the accuracy and stability of the adjustment process. At the same time, the system also monitors the stress state of the fiber to ensure that it is always within a safe working range and avoid performance degradation due to excessive deformation. This precise adjustment method based on bidirectional expansion enables the blood pressure cuff to accurately achieve the expected spatial form. Through the coordinated control of longitudinal and lateral deformation, the system can make the cuff accurately fit the local curvature of the arm while maintaining the appropriate length, effectively avoiding wrinkles and gaps during the measurement process.

[0082] Based on the above embodiment, as an optional embodiment, in step 104: adjusting the blood pressure cuff in combination with the target cuff length and target bending angle corresponding to the segmented area, this step may further include the following steps:

[0083] Step 501: Obtain the number of times the airbag connected to the blood pressure cuff is inflated and deflated and the duration of use; when the number of times the airbag is inflated and deflated is greater than or equal to a threshold number, or the duration of use is greater than or equal to a threshold duration, generate a replacement prompt message and send it to the target user's mobile device.

[0084] Among them, the number of inflation and deflation times refers to the cumulative number of times the blood pressure cuff is connected to the airbag to complete a complete cycle of inflation and deflation, which reflects the frequency of the actual working of the airbag; the usage time refers to the cumulative time from the first use of the airbag to the current moment, which reflects the actual service time of the airbag. These two parameters together constitute the key indicators for evaluating the usage status of the airbag. In the embodiment of the present application, it can be understood that the number of inflation and deflation times is an integer value, which records each inflation and deflation cycle completed by the airbag. For example, when a blood pressure measurement is completed, the airbag usually needs to go through one or more inflation and deflation cycles, and the system will accumulate and record these cycles. The usage time is counted in hours or days, starting from the first use of the airbag, and continues to count even when the device is in standby or off state. For example, an airbag has been used for 280 days and has completed 850 inflation and deflation cycles. These data will be recorded and updated by the system in real time.

[0085] Specifically, to ensure the accuracy and safety of blood pressure measurement, the control module needs to monitor the use status of the blood pressure cuff connected to the airbag in real time. As a key component in the blood pressure measurement process, the performance of the airbag will gradually decrease with the increase in the number of uses and the passage of time. Therefore, it is necessary to establish a complete monitoring and reminder mechanism to promptly remind users to replace the aging airbag. Through the built-in counter and timer, the number of times the airbag is inflated and deflated and the cumulative use time are continuously recorded. The system accurately records the inflation and deflation operations during each blood pressure measurement process, and calculates the cumulative working time from the first use of the airbag. When it is detected that the number of inflation and deflation reaches or exceeds the system preset number threshold (for example, 1000 times), or the cumulative use time reaches or exceeds the preset time threshold (for example, 12 months), the system will automatically generate a replacement reminder message. This reminder message contains the airbag usage status data and replacement suggestions, which are sent to the user's mobile device through the wireless communication module. This monitoring and reminder method based on usage status enables the system to actively prevent measurement errors caused by airbag aging. By tracking the use of the airbag in real time and promptly reminding the user when it is approaching the end of its service life, the problem of measuring accuracy being affected by airbag performance degradation can be effectively avoided.

[0086] Based on the above embodiment, as an optional embodiment, in step 104: adjusting the blood pressure cuff in combination with the target cuff length and target bending angle corresponding to the segmented area, this step may further include the following steps:

[0087] Step 502: In response to the query request of the target user, generate the measurement record and remaining usage times of the blood pressure cuff, and send the measurement record and remaining usage times of the blood pressure cuff to the mobile device of the target user.

[0088] Specifically, in order to help users understand the usage history and remaining life of the blood pressure cuff, the control module needs to establish a complete data recording and query mechanism. This transparent information management method not only helps users to arrange measurement plans reasonably, but also can predict the equipment replacement time in advance, thereby ensuring the continuity and reliability of blood pressure measurement. When the system receives a query request sent by the target user through the mobile device, the control module will immediately retrieve the historical measurement records of the blood pressure cuff from the data storage unit, including detailed information such as measurement time, measurement results, and usage time. At the same time, the system calculates the remaining available times based on the preset number threshold and the current number of inflation and deflation times used. For example, if the system presets the number threshold as 1000 times and has been used 850 times, the remaining number of uses is 150 times. The control module integrates this information into a data packet in a standard format and sends it to the user's mobile device through the wireless communication module. This information feedback mechanism based on user queries makes the blood pressure measurement device more manageable and predictable. By obtaining the usage status information of the device in a timely manner, users can better understand the usage of the device, reasonably plan the measurement frequency, and avoid interrupting the measurement plan due to the sudden need to replace the device.

[0089] Reference Figure 2 , is an intelligent management system for an intelligent blood pressure cuff provided in an embodiment of the present application, the system comprises: a data acquisition module, a fit calculation module, a parameter determination module, and a cuff adjustment module, wherein:

[0090] A data acquisition module, used to acquire arm pressure distribution data and arm shape data of a target user;

[0091] A fit calculation module, used to calculate the fit between multiple segmented areas in the blood pressure cuff and the user's arm based on the arm pressure distribution data;

[0092] A parameter determination module, used to determine the target cuff length and target bending angle corresponding to each segmented area in the blood pressure cuff according to the arm shape data;

[0093] The cuff adjustment module is used to adjust the blood pressure cuff for each segmented area, in combination with the target cuff length and target bending angle corresponding to the segmented area, when the difference between the fit between the segmented area and the user's arm and the standard fit is greater than the fit difference threshold.

[0094] Based on the above embodiment, the fit calculation module is also used to divide the blood pressure cuff into multiple segmented areas of preset specifications; determine the pressure measurement values ​​corresponding to multiple measurement points in each segmented area according to the arm pressure distribution data; for each segmented area, determine the number of measurement points whose pressure measurement values ​​are within the standard pressure range and the total number of multiple measurement points in the segmented area; calculate the ratio between the number of measurement points whose pressure measurement values ​​are within the standard pressure range and the total number of multiple measurement points in the segmented area, and use the ratio as the fit between the segmented area and the user's arm.

[0095] Based on the above embodiment, the parameter determination module is also used to construct an arm three-dimensional model according to the arm shape data; extract the contour curve corresponding to each segmented area in the arm three-dimensional model; for the contour curve corresponding to each segmented area, calculate the arc length of the contour curve, and use the arc length as the target cuff length of the segmented area, calculate the tangent angle between the contour curve and the adjacent contour curve, and use the tangent angle as the target bending angle of the segmented area.

[0096] Based on the above embodiment, the parameter determination module is also used to extract multiple feature points of the user's arm from the arm shape data; calibrate the spatial coordinates of each feature point to obtain the spatial coordinates corresponding to each feature point; generate a mesh surface based on the spatial coordinates of each feature point; and perform surface smoothing on the mesh surface to obtain a three-dimensional model of the arm.

[0097] Based on the above embodiments, the cuff adjustment module is also used to determine the longitudinal expansion amount corresponding to the stretchable elastic fibers in the blood pressure cuff according to the target cuff length; determine the lateral expansion amount corresponding to the stretchable elastic fibers in the blood pressure cuff according to the target bending angle; and adjust the stretchable elastic fibers corresponding to the segmented areas in the blood pressure cuff based on the longitudinal expansion amount and the lateral expansion amount.

[0098] Based on the above embodiment, the cuff adjustment module is also used to obtain the number of inflation and deflation times and the usage time of the airbag connected to the blood pressure cuff; when the number of inflation and deflation times is greater than or equal to the number threshold, or the usage time is greater than or equal to the time threshold, a replacement prompt message is generated and sent to the target user's mobile device.

[0099] Based on the above embodiment, the cuff adjustment module is also used to generate measurement records and remaining usage times of the blood pressure cuff in response to the query request of the target user, and send the measurement records and remaining usage times of the blood pressure cuff to the mobile device of the target user.

[0100] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0101] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0102] The communication bus 302 is used to realize the connection and communication between these components.

[0103] The user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0104] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0105] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface diagrams and applications, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0106] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program for an intelligent management method of an intelligent blood pressure cuff.

[0107] exist Figure 3In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the memory 305 to store an application program for an intelligent management method for an intelligent blood pressure cuff. When executed by one or more processors 301, the electronic device 300 executes one or more methods in the above-mentioned embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited to the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0108] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0109] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0110] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0111] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0112] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, 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, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0113] The above are only exemplary embodiments of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0114] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not recorded in the present disclosure. The description and examples are to be regarded as exemplary only.

Claims

1. An intelligent management method for an intelligent blood pressure cuff, characterized in that: include: Obtaining arm pressure distribution data and arm shape data of the target user; Based on the arm pressure distribution data, calculating the fit between multiple segmented areas in the blood pressure cuff and the user's arm; Determining, according to the arm shape data, a target cuff length and a target bending angle corresponding to each segmented area in the blood pressure cuff; For each of the segmented areas, when the difference between the degree of fit between the segmented area and the user's arm and the standard degree of fit is greater than a fit difference threshold, the blood pressure cuff is adjusted in combination with a target cuff length and a target bending angle corresponding to the segmented area; The calculating the fit between the multiple segmented areas in the blood pressure cuff and the user's arm based on the arm pressure distribution data includes: Dividing the blood pressure cuff into a plurality of segmented areas of preset specifications; Determining pressure measurement values ​​corresponding to a plurality of measurement points in each of the segmented areas according to the arm pressure distribution data; For each of the segmented areas, determining the number of measurement points where the pressure measurement value is within the standard pressure range and the total number of the plurality of measurement points in the segmented area; Calculating the ratio between the number of measurement points where the pressure measurement values ​​are within the standard pressure range and the total number of the plurality of measurement points in the segmented area, and using the ratio as the fit between the segmented area and the user's arm; Determining the target cuff length and target bending angle corresponding to each segmented area in the blood pressure cuff according to the arm shape data includes: Constructing a three-dimensional arm model according to the arm shape data; Extracting the contour curve corresponding to each segmented area in the three-dimensional model of the arm; For the contour curve corresponding to each segmented area, the arc length of the contour curve is calculated, and the arc length is used as the target cuff length of the segmented area, and the tangent angle between the contour curve and the adjacent contour curve is calculated, and the tangent angle is used as the target bending angle of the segmented area; The step of constructing a three-dimensional arm model according to the arm shape data comprises: extracting a plurality of feature points of the user's arm from the arm shape data; Calibrate the spatial coordinates of each of the feature points to obtain the spatial coordinates corresponding to each of the feature points; Based on the spatial coordinates of each of the feature points, a mesh surface is generated; The mesh surface is smoothed to obtain a three-dimensional model of the arm.

2. The intelligent management method for an intelligent blood pressure cuff according to claim 1, characterized in that: The adjusting the blood pressure cuff in combination with the target cuff length and the target bending angle corresponding to the segmented area comprises: Determining the longitudinal expansion amount corresponding to the expandable elastic fibers in the blood pressure cuff according to the target cuff length; Determining a lateral expansion amount corresponding to the expandable elastic fibers in the blood pressure cuff according to the target bending angle; Based on the longitudinal expansion and contraction amount and the lateral expansion and contraction amount, the stretchable elastic fibers corresponding to the segmented areas in the blood pressure cuff are adjusted.

3. The intelligent management method for an intelligent blood pressure cuff according to claim 1, characterized in that: After adjusting the blood pressure cuff in combination with the target cuff length and target bending angle corresponding to the segmented area, the method further includes: Obtaining the number of times the air bag connected to the blood pressure cuff is inflated and deflated and the duration of use; When the number of times of inflation and deflation is greater than or equal to the number threshold, or the usage time is greater than or equal to the time threshold, a replacement prompt message is generated and sent to the mobile device of the target user.

4. The intelligent management method for an intelligent blood pressure cuff according to claim 1, characterized in that: After adjusting the blood pressure cuff in combination with the target cuff length and target bending angle corresponding to the segmented area, the method further includes: In response to the query request of the target user, a measurement record and a remaining number of uses of the blood pressure cuff are generated, and the measurement record and the remaining number of uses of the blood pressure cuff are sent to a mobile device of the target user.

5. An intelligent management system for an intelligent blood pressure cuff, characterized in that: The system comprises: A data acquisition module, used to acquire arm pressure distribution data and arm shape data of a target user; A fit calculation module, used to calculate the fit between the multiple segmented areas in the blood pressure cuff and the user's arm based on the arm pressure distribution data; A parameter determination module, used for determining a target cuff length and a target bending angle corresponding to each segmented area in the blood pressure cuff according to the arm shape data; a cuff adjustment module, for adjusting the blood pressure cuff in combination with a target cuff length and a target bending angle corresponding to each segmented area when the difference between the fit between the segmented area and the user's arm and the standard fit is greater than a fit difference threshold; The calculating the fit between the multiple segmented areas in the blood pressure cuff and the user's arm based on the arm pressure distribution data includes: Dividing the blood pressure cuff into a plurality of segmented areas of preset specifications; Determining pressure measurement values ​​corresponding to a plurality of measurement points in each of the segmented areas according to the arm pressure distribution data; For each of the segmented areas, determining the number of measurement points where the pressure measurement value is within the standard pressure range and the total number of the plurality of measurement points in the segmented area; Calculating the ratio between the number of measurement points where the pressure measurement values ​​are within the standard pressure range and the total number of the plurality of measurement points in the segmented area, and using the ratio as the fit between the segmented area and the user's arm; Determining the target cuff length and target bending angle corresponding to each segmented area in the blood pressure cuff according to the arm shape data includes: Constructing a three-dimensional arm model according to the arm shape data; Extracting the contour curve corresponding to each segmented area in the three-dimensional model of the arm; For the contour curve corresponding to each segmented area, the arc length of the contour curve is calculated, and the arc length is used as the target cuff length of the segmented area, and the tangent angle between the contour curve and the adjacent contour curve is calculated, and the tangent angle is used as the target bending angle of the segmented area; The step of constructing a three-dimensional arm model according to the arm shape data comprises: extracting a plurality of feature points of the user's arm from the arm shape data; Calibrate the spatial coordinates of each of the feature points to obtain the spatial coordinates corresponding to each of the feature points; Based on the spatial coordinates of each of the feature points, a mesh surface is generated; The mesh surface is smoothed to obtain a three-dimensional model of the arm.

6. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the intelligent management method for the smart blood pressure cuff as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the intelligent management method for the smart blood pressure cuff as described in any one of claims 1-4 is executed.

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