Balance monitoring method and system for sitting position balance training chair

Abstract

The invention relates to the field of rehabilitation training, and discloses a balance monitoring method and system for a seat balance training chair, and the method comprises the steps: arranging a multi-attribute monitor at a sensitive part of the seat balance training chair, monitoring the real-time data of the seat balance training chair, extracting a sitting posture image of a use object from the real-time data, and obtaining a sitting posture image of the use object; the method comprises the following steps: identifying posture features of a used object, extracting pressure sensor data and inertia measurement data in real-time data, identifying key features of a sitting position balance training chair from fusion data of the pressure sensor data and the inertia measurement data, and combining the posture features and the key features to obtain the sitting position balance training chair. Analyzing the balance state of the sitting position balance training chair and the balance sitting posture of a using object, setting a feedback mechanism of an unbalanced state based on the balance sitting posture and the balance state, and performing balance monitoring on the sitting position balance training chair in combination with a multi-attribute monitor, a balance judgment base line and the feedback mechanism. The balance monitoring precision of the sitting position balance training chair can be improved.

Description

Technical Field

[0001] The invention relates to the field of rehabilitation training, and in particular to a balance monitoring method and system for a sitting balance training chair. Background Art

[0002] A sitting balance training chair refers to a rehabilitation device that helps users improve their sitting balance ability. It is mainly used to train users' posture control ability and improve their stability and balance when sitting. With the advancement of modern medicine and the improvement of people's health awareness, rehabilitation medicine has become particularly important. In order to improve users' sitting balance ability, the sitting balance training chair has become an indispensable and important tool in the field of rehabilitation medicine, which also makes the balance monitoring of the sitting balance training chair more and more important.

[0003] In the prior art, balance monitoring of a seated balance training chair is mainly achieved by using a pressure sensor monitoring method. This method detects changes in pressure distribution in various parts of the body by installing pressure sensors under the seat or on the foot pedals, and then evaluates the user's balance state. However, this method may not be able to accurately capture subtle changes in body movements, resulting in low accuracy in the balance monitoring results of the seated balance training chair. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a balance monitoring method and system for a sitting balance training chair, which can improve the balance monitoring accuracy of the sitting balance training chair.

[0005] In a first aspect, the present invention provides a balance monitoring method for a sitting balance training chair, comprising: Acquire a sitting balance training chair to be monitored and its corresponding user, identify sensitive parts of the sitting balance training chair, and set a multi-attribute monitor for the sitting balance training chair based on the sensitive parts, wherein the multi-attribute monitor includes a pressure sensor, an inertial measurement unit, and an image acquisition device, and monitor the real-time data of the sitting balance training chair based on the multi-attribute monitor; Extracting a sitting posture image of the user from the live data, identifying position coordinates of key body parts according to the sitting posture image, calculating the inclination angle and distance ratio of the key body parts based on the position coordinates, and analyzing the posture characteristics of the user according to the inclination angle and the distance ratio; According to the multi-attribute monitor, extract the pressure sensor data and the inertial measurement data of the real-time data, perform data fusion processing on the pressure sensor data and the inertial measurement data to obtain fused data, and identify the key features of the sitting balance training chair from the fused data; In combination with the posture feature and the key feature, the balance state of the sitting balance training chair is analyzed, basic information data of the user is dispatched, wherein the basic information data includes age data and physical condition data, and the balanced sitting posture of the user is identified according to the basic information data, the posture feature and the key feature; Based on the balanced sitting posture and the balanced state, a balance judgment baseline of the sitting balance training chair is set, and according to the balance judgment baseline, the unbalanced state of the sitting balance training chair is identified, and a feedback mechanism for the unbalanced state is set. In combination with the multi-attribute monitor, the balance judgment baseline and the feedback mechanism, balance monitoring is performed on the sitting balance training chair to obtain a balance monitoring result.

[0006] In a possible implementation of the first aspect, the identifying a sensitive part of the sitting balance training chair includes: Acquiring the physical structure of the sitting balance training chair; Based on the physical structure, identifying the force-bearing surface of the sitting balance training chair; Extracting key stress points of the stress-bearing surface; Identify the specific position of the key force point on the sitting balance training chair; Based on the specific position, a sensitive part of the sitting balance training chair is identified.

[0007] In a possible implementation of the first aspect, identifying the position coordinates of the key body parts according to the sitting posture image includes: According to the sitting posture image, background removal processing is performed on the key body parts to obtain body parts; Locating the limb position corresponding to the body part, and constructing an image coordinate system of the body part according to the limb position; Identify key points of the limb position, and calculate coordinate values ​​of the key points according to the image coordinate system; Based on the coordinate values, the position coordinates of the key body parts are identified.

[0008] In a possible implementation manner of the first aspect, calculating the inclination angle of the key body part based on the position coordinates includes: Based on the position coordinates, defining a relative reference plane of the key body part, and calculating the spatial coordinates of the relative reference plane; Performing coordinate conversion on the position coordinates to obtain three-dimensional coordinates; According to the three-dimensional coordinates, identifying the key point coordinates of the key body part; Based on the key point coordinates and the space coordinates, the direction vector of the key body part is calculated using the following formula: ; in, Indicates the direction vectors of key body parts, represents the spatial coordinates, represents the key point coordinates, Indicates the direction value of the key point coordinate displacement on the x-axis to the space coordinate. Indicates the direction value of the key point coordinate displacement on the y-axis to the spatial coordinate. Indicates the direction value of the key point coordinate displacement on the z-axis to the spatial coordinate; Obtaining a normal vector relative to the reference surface; The vector angle between the direction vector and the normal vector is calculated using the following formula: ; in, represents the vector angle between the direction vector and the normal vector, represents the direction vector, b represents the normal vector, represents the magnitude of the direction vector, Represents the modulus of the normal vector; Based on the vector angle, the inclination angle of the key body part is obtained.

[0009] In a possible implementation of the first aspect, identifying key features of the sitting balance training chair from the fused data includes: Identifying data classification of the fused data, and identifying characteristic elements of the data classification; Performing time series analysis on the characteristic elements to obtain time series change data; Based on the time series change data, construct a change rate curve of the characteristic element; extracting the peak position of the characteristic element from the change rate curve; Analyzing the influence of the characteristic element on the sitting balance training chair according to the peak position; Based on the influence degree, key features of the sitting balance training chair are extracted.

[0010] In a possible implementation of the first aspect, analyzing the balance state of the sitting balance training chair in combination with the posture feature and the key feature includes: identifying a user of the sitting balance training chair according to the posture characteristics; identifying a muscle activation pattern of the user during a sitting posture, and analyzing the body balance ability of the user according to the muscle activation pattern; dispatching the live data of the key features, and identifying the angular velocity data and acceleration data of the sitting balance training chair based on the live data; Analyzing the flight posture of the sitting balance training chair during the sitting process based on the acceleration data and the angular velocity data; Analyzing the dynamic stability of the sitting balance training chair according to the flight posture; The balance state of the sitting balance training chair is analyzed in combination with the body balance ability and the dynamic stability.

[0011] In a possible implementation manner of the first aspect, identifying the balanced sitting posture of the user according to the basic information data, the posture feature, and the key feature includes: Identify the group characteristics of the user objects according to the basic information data; Based on the group characteristics, setting a normative level of the posture characteristics; Analyzing the change trajectory of the key features according to the specification level; Based on the change trajectory, analyzing the abnormal change of the sitting balance training chair; Identifying the body balance of the user under the abnormal condition; The balanced sitting posture of the user is identified according to the body balance force.

[0012] In a possible implementation of the first aspect, setting a balance judgment baseline of the sitting balance training chair based on the balanced sitting posture and the balanced state includes: Based on the balanced sitting posture, identifying a user of the sitting balance training chair; Identify key indicators of the user in the balanced sitting posture; Based on the balance state, collecting balance state data of the sitting balance training chair; Extracting the static sitting posture and the dynamic sitting posture of the user in the balanced sitting posture; Analyzing the static balance requirement and the dynamic balance requirement of the user based on the static sitting posture and the dynamic sitting posture; According to the static balance requirement, setting the static balance baseline of the sitting balance training chair; Based on the dynamic balance requirement, testing the motion tolerance limit of the sitting balance training chair to the user; According to the action tolerance limit, setting the dynamic balance baseline of the sitting balance training chair; The balance judgment baseline of the sitting balance training chair is set in combination with the static balance baseline and the dynamic balance baseline.

[0013] In a possible implementation manner of the first aspect, setting the feedback mechanism of the imbalance state according to the balance judgment baseline includes: identifying abnormal factors of the imbalance state according to the balance judgment baseline; Setting an abnormal alarm for the abnormal factor; Analyze the influencing conditions of the abnormal factors, and set a state adjustment mechanism of the abnormal factors according to the influencing conditions; In combination with the abnormal alarm and the state adjustment mechanism, a feedback mechanism for the unbalanced state is provided.

[0014] In a second aspect, the present invention provides a balance monitoring system for a sitting balance training chair, the system comprising: A data monitoring module, used for acquiring a seated balance training chair to be monitored and its corresponding user, identifying sensitive parts of the seated balance training chair, and setting a multi-attribute monitor of the seated balance training chair based on the sensitive parts, wherein the multi-attribute monitor includes a pressure sensor, an inertial measurement unit and an image acquisition device, and based on the multi-attribute monitor, real-time monitoring of the live data of the seated balance training chair; a posture feature recognition module, configured to extract a sitting posture image of the user from the live data, recognize position coordinates of key body parts according to the sitting posture image, calculate an inclination angle and a distance ratio of the key body parts based on the position coordinates, and analyze the posture feature of the user according to the inclination angle and the distance ratio; A key feature extraction module, for extracting the pressure sensor data and the inertial measurement data of the real-time data according to the multi-attribute monitor, performing data fusion processing on the pressure sensor data and the inertial measurement data to obtain fused data, and identifying the key features of the sitting balance training chair from the fused data; A balanced sitting posture analysis module, used to analyze the balance state of the sitting balance training chair in combination with the posture feature and the key feature, dispatch the basic information data of the user, wherein the basic information data includes age data and physical condition data, and identify the balanced sitting posture of the user according to the basic information data, the posture feature and the key feature; A monitoring result output module is used to set a balance judgment baseline for the sitting balance training chair based on the balanced sitting posture and the balanced state, identify the unbalanced state of the sitting balance training chair according to the balance judgment baseline, and set a feedback mechanism for the unbalanced state, and combine the multi-attribute monitor, the balance judgment baseline and the feedback mechanism to perform balance monitoring on the sitting balance training chair to obtain a balance monitoring result.

[0015] Compared with the prior art, the technical principle and beneficial effects of this solution are: The embodiment of the present invention can identify the sensitive parts of the sitting balance training chair and install sensors at the sensitive parts to monitor various parameters of the user during the sitting balance training in real time, thereby improving the comprehensiveness of the real-time data and timely discovering the subtle changes of the user during the training process to help understand the balance state of the sitting balance training chair; further, the embodiment of the present invention can intuitively display the current sitting state of the user by extracting the sitting posture image of the user from the real-time data, timely discover the balance problems of the sitting balance training chair, and identify the position coordinates of the key body parts of the user to understand the body inclination of the user in the sitting state. and the displacement of the center of gravity of the body, so as to accurately evaluate the user's sitting posture stability and the balance performance of the chair itself, and provide a scientific basis and guidance for sitting balance training; the embodiment of the present invention can identify the key features of the sitting balance training chair from the fusion data, and can judge the stability of the user in different actions by analyzing the pressure distribution and acceleration changes; further, the embodiment of the present invention can understand the stability of the sitting balance training chair under dynamic conditions by combining the posture features and the key features, improve the accuracy and reliability of the balance state evaluation of the sitting balance training chair, and combine the user The balanced sitting posture can provide a balance monitoring standard for the sitting balance training chair, identify the unbalanced sitting posture of the user, and provide personalized guidance suggestions according to the basic information data of the user; the embodiment of the present invention sets a balance judgment baseline for the sitting balance training chair based on the balanced sitting posture and the balance state, and can identify abnormal conditions of the sitting balance training chair by monitoring the balance state of the sitting balance training chair to improve the safety of the sitting balance training chair, and can identify the unbalanced state of the sitting balance training chair according to the balance judgment baseline, and set a feedback mechanism for the unbalanced state, so that when the sitting balance training chair is in an unbalanced state, it can be discovered and responded to in time. Control potential safety risks and ensure the safety and reliability of the training process; the embodiment of the present invention combines the multi-attribute monitor, the balance judgment baseline and the feedback mechanism to perform balance monitoring on the sitting balance training chair to obtain a balance monitoring result. The data collected by the multi-attribute monitor, combined with the evaluation result of the balance judgment baseline and the immediate adjustment of the feedback mechanism, can form a closed-loop monitoring and training system. The system can not only monitor the subtle changes in the user's body posture and the balance state of the sitting balance training chair, but also adaptively adjust the imbalance state of the sitting balance training chair, thereby improving the user's sitting balance ability and the overall rehabilitation effect. Therefore, the balance monitoring method of a sitting balance training chair proposed in the embodiment of the present invention can improve the balance monitoring accuracy of the sitting balance training chair. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0018] Figure 1 A schematic flow chart of a balance monitoring method for a sitting balance training chair provided in one embodiment of the present invention; Figure 2 A schematic diagram of a module of a balance monitoring system for a sitting balance training chair provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0020] An embodiment of the present invention provides a balance monitoring method for a sitting balance training chair, and the execution subject of the balance monitoring method for a sitting balance training chair includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present invention. In other words, the balance monitoring method for a sitting balance training chair can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0021] See also Figure 1 FIG. 1 is a flow chart of a balance monitoring method for a sitting balance training chair provided by an embodiment of the present invention. Figure 1 A balance monitoring method for a sitting balance training chair described in the specification includes: S1. Acquire a sitting balance training chair to be monitored and its corresponding user, identify sensitive parts of the sitting balance training chair, and based on the sensitive parts, set a multi-attribute monitor for the sitting balance training chair, wherein the multi-attribute monitor includes a pressure sensor, an inertial measurement unit, and an image acquisition device, and based on the multi-attribute monitor, monitor the real-time data of the sitting balance training chair in real time.

[0022] The embodiment of the present invention can identify the monitored object and needs by acquiring the sitting balance training chair to be monitored and its corresponding user, wherein the user refers to an individual who has impaired sitting balance ability and needs to undergo rehabilitation training using the sitting balance training chair.

[0023] Furthermore, the embodiment of the present invention can install sensors at the sensitive parts of the sitting balance training chair by identifying the sensitive parts, so as to comprehensively understand the sitting balance state and training effect of the user. The sensitive parts refer to the key areas that can accurately reflect the user's balance state and posture control.

[0024] As an embodiment of the present invention, the identifying of sensitive parts of the sitting balance training chair includes: acquiring the physical structure of the sitting balance training chair; based on the physical structure, identifying the force-bearing surface of the sitting balance training chair; extracting the key force points of the force-bearing surface; identifying the specific positions of the key force points on the sitting balance training chair; based on the specific positions, identifying the sensitive parts of the sitting balance training chair.

[0025] Among them, the physical structure refers to the overall structure and components of the sitting balance training chair, including the shape, size, material and connection method of each component; the force-bearing surface refers to the part of the sitting balance training chair that is in direct contact with the user and bears the weight of the human body, such as the seat surface, back support surface, etc.; the key force point refers to a specific position on the force surface that bears greater force during use by the user; and the specific position refers to the exact position of the key force point on the sitting balance training chair.

[0026] Optionally, the extraction of key force points on the force-bearing surface can be obtained through mechanical analysis software, such as ANSYS software, and the identification of the specific positions of the key force points on the sitting balance training chair can be achieved using a three-dimensional model of the sitting balance training chair, such as determining the specific positions of the key force points through a coordinate system in the three-dimensional model.

[0027] The embodiment of the present invention sets a multi-attribute monitor for the sitting balance training chair based on the sensitive parts, so as to monitor in real time various parameters of the user during the sitting balance training process and improve the comprehensiveness of the real-time data. The multi-attribute monitor refers to a comprehensive monitoring system composed of various types of sensor devices, including pressure sensors, inertial measurement units and image acquisition devices.

[0028] Optionally, the multi-attribute monitor setting of the sitting balance training chair based on the sensitive parts can be obtained by using sensors and image acquisition devices.

[0029] Furthermore, the present invention can detect subtle changes in the user during the training process by monitoring the live data of the sitting balance training chair in real time based on the multi-attribute monitor, so as to help understand the balance state of the sitting balance training chair. The live data refers to the real-time data of the user and the sitting balance training chair during the sitting process collected by the monitoring equipment.

[0030] S2. Extract a sitting image of the user from the live data, identify the position coordinates of the key body parts according to the sitting image, calculate the inclination angle and distance ratio of the key body parts based on the position coordinates, and analyze the posture characteristics of the user according to the inclination angle and the distance ratio.

[0031] The embodiment of the present invention can intuitively display the current sitting posture state of the user and promptly discover balance problems of the sitting balance training chair by extracting the sitting posture image of the user from the real-time data. The sitting posture image refers to an image of the user sitting on the sitting balance training chair captured in real time by an image acquisition device.

[0032] Furthermore, the embodiment of the present invention can deeply analyze various details of the sitting posture by identifying the position coordinates of the key body parts based on the sitting posture image, thereby ensuring that the user maintains a correct sitting posture during the entire training process. The position coordinates refer to the specific position information of the key body parts in the two-dimensional image.

[0033] As an embodiment of the present invention, identifying the position coordinates of the key body parts based on the sitting image includes: performing background removal processing on the key body parts based on the sitting image to obtain body parts; locating limb positions corresponding to the body parts, and constructing an image coordinate system of the body parts based on the limb positions; identifying key points of the limb positions, and calculating coordinate values ​​of the key points based on the image coordinate system; and identifying the position coordinates of the key body parts based on the coordinate values.

[0034] Among them, the body part refers to the body part of the user after removing the background from the sitting image, the limb position refers to the specific position of each part of the user's body in the image, the image coordinate system refers to a set of coordinate systems defined in the image, usually with the upper left corner of the image as the origin (0, 0), the horizontal direction as the x-axis, and the vertical direction as the y-axis, the key point refers to the important feature points of each part of the user's body, such as the center of the head, the sides of the shoulders, the center of the waist, the knees, etc., and the coordinate value refers to the specific position of the key point in the image coordinate system, usually expressed as (x, y).

[0035] Optionally, the background removal processing of the key body parts based on the sitting image can be achieved by using image segmentation technology, such as background subtraction technology, and the image coordinate system construction of the body parts based on the limb positions can be obtained through a two-dimensional coordinate system.

[0036] The embodiment of the present invention calculates the inclination angle and distance ratio of the key body parts based on the position coordinates, so as to intuitively understand the body inclination and body center of gravity shift of the user in a sitting state, thereby accurately evaluating the sitting stability of the user and the balance performance of the chair itself, and providing a scientific basis and guidance for sitting balance training. The inclination angle refers to the angle of the key body part of the user relative to the plane of the chair, and the distance ratio refers to the ratio of the relative distances between various parts of the user's body or between a body part and the chair.

[0037] Optionally, the distance ratio calculation of the key body parts based on the position coordinates can be implemented using the Euclidean distance formula.

[0038] As an embodiment of the present invention, the calculating the inclination angle of the key body part based on the position coordinates includes: defining a relative reference plane of the key body part based on the position coordinates, and calculating the spatial coordinates of the relative reference plane; performing coordinate conversion on the position coordinates to obtain three-dimensional coordinates; identifying the key point coordinates of the key body part according to the three-dimensional coordinates; calculating the direction vector of the key body part based on the key point coordinates and the spatial coordinates; obtaining the normal vector of the relative reference plane; calculating the vector angle between the direction vector and the normal vector; and obtaining the inclination angle of the key body part based on the vector angle.

[0039] Among them, the relative reference plane refers to the chair plane of the sitting balance training chair, the spatial coordinates refer to the three-dimensional coordinates of the chair plane, the three-dimensional coordinates refer to the coordinate information of the body parts in the three-dimensional space, the key point coordinates refer to the specific position of the key body parts in the three-dimensional space, the direction vector refers to the direction of the key body parts in the three-dimensional space, the normal vector refers to the normal direction of the relative reference plane, and the vector angle refers to the angle between the normal vector of the reference plane and the direction vector of the body part.

[0040] Optionally, the coordinate transformation of the position coordinates can be achieved using a visual positioning method, such as a method for obtaining depth information using a depth camera. Based on the position coordinates, the relative reference plane definition of the key body part can be obtained by obtaining the chair plane, and the normal vector relative to the reference plane can be obtained by using the cross product of any two non-collinear points on the reference plane.

[0041] In an optional embodiment of the present invention, based on the key point coordinates and the space coordinates, the direction vector of the key body part is calculated using the following formula: ; in, represents the direction vector of the key body parts, represents the spatial coordinates, represents the key point coordinates, Indicates the direction value of the key point coordinate displacement on the x-axis to the space coordinate. Indicates the direction value of the key point coordinate displacement on the y-axis to the spatial coordinate. Indicates the direction value of the key point coordinate displacement on the z-axis to the space coordinate.

[0042] In another optional embodiment of the present invention, the vector angle between the direction vector and the normal vector is calculated using the following formula: ; in, represents the vector angle between the direction vector and the normal vector, represents the direction vector, b represents the normal vector, represents the magnitude of the direction vector, Indicates the magnitude of the normal vector.

[0043] Furthermore, the embodiment of the present invention can grasp the body balance state information of the user during the sitting process, identify the balance ability of the sitting balance training chair, and thus predict the imbalance risk by analyzing the posture characteristics of the user according to the inclination angle and the distance ratio, and the posture characteristics refer to the posture, movement and behavior characteristics of the user on the chair.

[0044] Optionally, the posture feature analysis of the object according to the tilt angle and the distance ratio may be implemented using a skeleton tracking technology, such as Microsoft Kinect software technology.

[0045] S3. According to the multi-attribute monitor, extract the pressure sensor data and the inertial measurement data of the real-time data, perform data fusion processing on the pressure sensor data and the inertial measurement data to obtain fused data, and identify the key features of the sitting balance training chair from the fused data.

[0046] The embodiment of the present invention can identify the pressure distribution of various parts of the body on the surface of the chair and obtain the posture changes of the chair to obtain a more accurate balance state by extracting the pressure sensor data and inertial measurement data of the real-time data according to the multi-attribute monitor. The pressure sensor data refers to the information about the pressure distribution of various parts on the sitting balance training chair collected by the pressure sensor, and the inertial measurement data refers to the information data such as the posture, acceleration and angular velocity of the sitting balance training chair collected by the inertial measurement unit.

[0047] Optionally, according to the multi-attribute monitor, the extraction of the pressure sensor data and inertial measurement data of the real-time data can be achieved by utilizing the pressure sensor and IMU of the multi-attribute monitor.

[0048] Furthermore, the embodiment of the present invention performs data fusion processing on the pressure sensor data and the inertial measurement data to obtain fused data, which can improve the accuracy and reliability of the data and facilitate the analysis of the state characteristics of the sitting balance training chair. The fused data refers to the comprehensive data obtained after data fusion processing.

[0049] Optionally, the data fusion processing of the pressure sensor data and the inertial measurement data may be obtained by a data fusion algorithm, such as a fusion algorithm in a Kalman filter.

[0050] The embodiment of the present invention can identify the key features of the sitting balance training chair from the fused data and judge the stability of the user in different actions by analyzing the pressure distribution and acceleration changes. The key features refer to features extracted from the fused data that are crucial to the sitting balance assessment, such as pressure distribution, acceleration, angular velocity, etc.

[0051] As an embodiment of the present invention, identifying the key features of the sitting balance training chair from the fused data includes: identifying data classification of the fused data, and identifying characteristic elements of the data classification; performing time series analysis on the characteristic elements to obtain time series change data; based on the time series change data, constructing a change rate curve of the characteristic elements; extracting the peak position of the characteristic elements from the change rate curve; analyzing the degree of influence of the characteristic elements on the sitting balance training chair according to the peak position; and extracting the key features of the sitting balance training chair based on the degree of influence.

[0052] Among them, the data classification refers to the data obtained after classifying the fused data according to different attributes, the characteristic elements refer to the characteristic parameters of the classified data that affect the change of the state of the sitting balance training chair, such as pressure distribution, angular velocity and acceleration, etc., the time series change data refers to the change data of the characteristic elements over time, the change rate curve refers to the curve of the change rate of the characteristic elements over time, the peak position refers to the point on the change rate curve that reaches the maximum or minimum value, and the degree of influence refers to the influence range of the characteristic elements causing the change of the state of the sitting balance training chair.

[0053] Optionally, the time series analysis of the characteristic elements can be implemented using a Python library, and the construction of the change rate curve of the characteristic elements based on the time series change data can be obtained through a NumPy database and a Matplotlib database, such as by differentiating the time series change data using a differential function of the NumPy database, calculating the change rate of the characteristic elements, and then drawing the change rate curve using the Matplotlib database. The analysis of the degree of influence of the characteristic elements on the sitting balance training chair based on the peak position can be achieved by using the degree of influence of the deviation range of the peak position on the stability of the sitting balance training chair.

[0054] S4. Analyze the balance state of the sitting balance training chair in combination with the posture characteristics and the key characteristics, and dispatch the basic information data of the user, wherein the basic information data includes age data and physical condition data, and identify the balanced sitting posture of the user according to the basic information data, the posture characteristics and the key characteristics.

[0055] The embodiment of the present invention combines the posture features and the key features to analyze the balance state of the sitting balance training chair, so as to understand the stability of the sitting balance training chair under dynamic conditions and improve the accuracy and reliability of the balance state evaluation of the sitting balance training chair. The balance state refers to the ability of the sitting balance training chair to maintain a stable balance during the overall sitting posture of the user, including static balance and dynamic balance.

[0056] As an embodiment of the present invention, the analysis of the balance state of the sitting balance training chair by combining the posture features and the key features includes: identifying the user of the sitting balance training chair according to the posture features; identifying the muscle activation pattern of the user during the sitting process, and analyzing the body balance ability of the user according to the muscle activation pattern; scheduling the real-time data of the key features, and identifying the angular velocity data and acceleration data of the sitting balance training chair based on the real-time data; analyzing the flight posture of the sitting balance training chair in the sitting process based on the acceleration data and the angular velocity data; analyzing the dynamic stability of the sitting balance training chair according to the flying posture; analyzing the balance state of the sitting balance training chair in combination with the body balance ability and the dynamic stability.

[0057] Among them, the sitting process refers to the entire process in which the user maintains a sitting position for a period of time, the muscle activation mode refers to the order and intensity of the human body's muscles being activated during the sitting process, the body balance ability refers to the ability of the human body to maintain balance under static or dynamic conditions, the angular velocity data refers to the speed data of the sitting balance training chair rotating during the sitting process, the acceleration data refers to the acceleration change data of the sitting balance training chair during the sitting process, the flying posture refers to the dynamic posture of the sitting balance training chair during the sitting process, and the dynamic stability refers to the ability of the sitting balance training chair to maintain a balanced state under the action of external force.

[0058] Optionally, the muscle activation pattern recognition of the user during the sitting process can be obtained through biomechanical analysis software, such as OpenSim software; the body balance ability analysis of the user based on the muscle activation pattern can be achieved using a balance function training and evaluation system, such as the Xiangyu Medical Balance Function Training and Evaluation System; and the dynamic stability analysis of the sitting balance training chair based on the flying posture can be obtained through ABAQUS dynamic analysis software.

[0059] As another embodiment of the present invention, the analysis of the flight posture of the sitting balance training chair in the sitting process based on the acceleration data and the angular velocity data includes: identifying the acceleration and angular velocity of the sitting balance training chair based on the acceleration data and the angular velocity data; calculating the pitch angle and roll angle of the acceleration relative to the direction of gravity, and calculating the yaw angle of the angular velocity; performing data fusion processing on the pitch angle, the roll angle and the yaw angle to obtain a fused posture angle; constructing a rotation matrix of the sitting balance training chair based on the fused posture angle; and analyzing the flight posture of the sitting balance training chair in the sitting process according to the rotation matrix.

[0060] Among them, the acceleration refers to the acceleration of the sitting balance training chair along three axes (usually X-axis, Y-axis and Z-axis) in space, the angular velocity refers to the rotation speed of the sitting balance training chair around three axes (usually X-axis, Y-axis and Z-axis), the gravity direction refers to the direction of the earth's gravity, the pitch angle refers to the angle describing the inclination of the sitting balance training chair relative to the horizontal plane, the roll angle refers to the rotation angle of the sitting balance training chair relative to the vertical axis, the yaw angle refers to the rotation angle of the sitting balance training chair relative to a fixed reference direction, the fused attitude angle refers to the comprehensive attitude angle calculated by fusing the data of the accelerometer and the angular velocity meter, and the rotation matrix refers to a tool for describing the rotation of an object in three-dimensional space.

[0061] Optionally, the data fusion processing of the pitch angle, the roll angle and the yaw angle can be implemented using the Mahony fusion algorithm, the pitch angle of the acceleration relative to the gravity direction can be calculated by the component of the accelerometer in the XY plane, the roll angle calculation of the acceleration relative to the gravity direction can be calculated by the component of the accelerometer in the XZ plane, the yaw angle calculation of the angular velocity can be implemented using time integration, and the rotation matrix construction of the sitting balance training chair based on the fused posture angle can be obtained through the matrix operation function of the Numpy library.

[0062] Furthermore, the embodiment of the present invention can understand the body posture of each user by scheduling the basic information data of the user, and provide a personalized balance monitoring method for the user of the sitting balance training chair. The basic information data refers to the basic personal information and physical condition data related to the user.

[0063] Optionally, the basic information data scheduling of the usage object can be implemented by using the user's registration information.

[0064] The embodiment of the present invention can provide a balance monitoring standard for the sitting balance training chair by identifying the balanced sitting posture of the user based on the basic information data, the posture characteristics and the key characteristics, identify the unbalanced sitting posture of the user, and provide personalized guidance suggestions based on the basic information data of the user. The balanced sitting posture means that the user can maintain a stable, comfortable and correct posture on the sitting balance training chair.

[0065] As an embodiment of the present invention, identifying the balanced sitting posture of the user based on the basic information data, the posture characteristics and the key characteristics includes: identifying the group characteristics of the user based on the basic information data; setting the standard level of the posture characteristics based on the group characteristics; analyzing the change trajectory of the key characteristics based on the standard level; analyzing the abnormal situation of the sitting balance training chair based on the change trajectory; identifying the body balance force of the user under the abnormal situation; and identifying the balanced sitting posture of the user based on the body balance force.

[0066] Among them, the group characteristics refer to the characteristics of the user group identified based on the basic information data, such as age group, health status, etc., the standard level refers to the degree of conformity between the posture characteristics and the standard sitting posture, the change trajectory refers to the changes of key characteristics over time, the abnormal situation refers to the degree of change of the state of the sitting balance training chair caused by the changes of key characteristics over time, and the body balance force refers to the user's balance ability under abnormal conditions.

[0067] Optionally, according to the basic information data, the group characteristic identification of the users can be obtained by statistically analyzing the basic information data, based on the group characteristics, the standard level setting of the posture characteristics can be achieved by utilizing the research results of medicine and ergonomics, according to the standard level, the change trajectory analysis of the key characteristics can be obtained by the change of real-time data, based on the change trajectory, the abnormal situation analysis of the sitting balance training chair can be achieved by analyzing the force applied to the surface of the chair by the change trajectory of the key characteristics, and the body balance force identification of the users in the abnormal situation can be obtained by posture detection tools, such as MediaPipe tools.

[0068] S5. Based on the balanced sitting posture and the balanced state, a balance judgment baseline of the sitting balance training chair is set; according to the balance judgment baseline, an unbalanced state of the sitting balance training chair is identified; and a feedback mechanism for the unbalanced state is set; and the balance monitoring of the sitting balance training chair is performed in combination with the multi-attribute monitor, the balance judgment baseline and the feedback mechanism to obtain a balance monitoring result.

[0069] The embodiment of the present invention sets a balance judgment baseline for the sitting balance training chair based on the balanced sitting posture and the balanced state. It can identify abnormal conditions of the sitting balance training chair by monitoring the balance state of the sitting balance training chair, thereby improving the safety of the sitting balance training chair. The balance judgment baseline refers to a standard for evaluating whether the balance state of the user is abnormal during the sitting posture.

[0070] As an embodiment of the present invention, setting the balance judgment baseline of the sitting balance training chair based on the balanced sitting posture and the balanced state includes: identifying the user of the sitting balance training chair based on the balanced sitting posture; identifying the key indicators of the user in the balanced sitting posture; collecting the balance state data of the sitting balance training chair based on the balanced state; extracting the static sitting posture and dynamic sitting posture of the user in the balanced sitting posture; analyzing the static balance demand and dynamic balance demand of the user based on the static sitting posture and the dynamic sitting posture; setting the static balance baseline of the sitting balance training chair according to the static balance demand; testing the action tolerance limit of the sitting balance training chair for the user based on the dynamic balance demand; setting the dynamic balance baseline of the sitting balance training chair according to the action tolerance limit; and setting the balance judgment baseline of the sitting balance training chair in combination with the static balance baseline and the dynamic balance baseline.

[0071] Among them, the key indicators refer to the center of gravity distribution, muscle tension, joint mobility, etc. of the human body in a balanced sitting posture; the balance state data refers to various sensor data recorded in a balanced sitting posture, including pressure distribution, acceleration, angular velocity, etc.; the static sitting posture refers to the sitting posture maintained by the user in a static state; the dynamic sitting posture refers to the sitting posture maintained by the user in a dynamic situation, such as sitting down, standing up, adjusting the sitting posture, etc.; the static balance requirement refers to the balance condition that the user needs to meet in a static sitting posture; the dynamic balance requirement refers to the balance condition that the user needs to meet in a static sitting posture; the static balance baseline refers to the balance standard set in a static sitting posture; the motion tolerance limit refers to the maximum motion range that the sitting balance training chair can withstand in a dynamic situation; and the dynamic balance baseline refers to the balance standard set in a dynamic sitting posture.

[0072] Optionally, based on the dynamic balance requirement, the motion tolerance limit test of the sitting balance training chair on the user can be implemented by using the Adafruit BNO055 posture solving tool.

[0073] Furthermore, the embodiment of the present invention identifies the imbalance state of the sitting balance training chair according to the balance judgment baseline, and sets a feedback mechanism for the imbalance state, so that when the sitting balance training chair is in an imbalance state, potential safety risks can be discovered and controlled in time to ensure the safety and reliability of the training process. The imbalance state refers to the situation that the user cannot maintain a stable sitting posture due to various reasons during the use of the training chair, or the training chair itself experiences unstable phenomena such as shaking and tilting. The feedback mechanism refers to the feedback made after the imbalance state is detected.

[0074] Optionally, according to the balance judgment baseline, the imbalance state identification of the sitting balance training chair can be obtained by setting a judgment threshold of the balance judgment baseline.

[0075] As an embodiment of the present invention, the feedback mechanism of the unbalanced state is set according to the balance judgment baseline, including: identifying abnormal factors of the unbalanced state according to the balance judgment baseline; setting abnormal alarms for the abnormal factors; analyzing the influencing conditions of the abnormal factors, and setting a state adjustment mechanism for the abnormal factors according to the influencing conditions; and setting a feedback mechanism for the unbalanced state in combination with the abnormal alarm and the state adjustment mechanism.

[0076] Among them, the abnormal factor refers to the specific factor that causes the sitting balance training chair to fail to meet the balance standard, the influencing condition refers to the reason that affects the imbalance state of the sitting balance training chair, such as human body shaking, chair failure, etc., the abnormal alarm refers to the warning signal issued when the abnormal factor of the imbalance state is detected, and the state adjustment mechanism refers to a series of measures used to adjust the user's sitting posture and the state of the sitting balance training chair to restore balance when the abnormal factor is detected.

[0077] Optionally, the abnormal alarm setting of the abnormal factor can be implemented using an alarm system, such as a sound alarm system, and based on the abnormal alarm, the state adjustment mechanism setting of the abnormal factor can be obtained by automatically adjusting the parameters of the chair through an adaptive control system, such as a PID controller.

[0078] The embodiment of the present invention performs balance monitoring on the sitting balance training chair by combining the multi-attribute monitor, the balance judgment baseline and the feedback mechanism to obtain a balance monitoring result. A closed-loop monitoring and training system can be formed by combining the data collected by the multi-attribute monitor with the evaluation result of the balance judgment baseline and the real-time adjustment of the feedback mechanism. The system can not only monitor the subtle changes in the body posture of the user and the balance state of the sitting balance training chair, but also adaptively adjust the imbalance state of the sitting balance training chair, thereby improving the user's sitting balance ability and the overall rehabilitation effect. The balance monitoring result refers to the output result of monitoring the balance state of the sitting balance training chair through the multi-attribute monitor, the balance judgment baseline and the feedback mechanism.

[0079] It can be seen that the embodiment of the present invention can install sensors on the sensitive parts of the sitting balance training chair by identifying the sensitive parts, so as to monitor various parameters of the user in the sitting balance training process in real time, improve the comprehensiveness of the real-time data, and timely discover the subtle changes of the user in the training process to help understand the balance state of the sitting balance training chair; further, the embodiment of the present invention can intuitively display the current sitting state of the user by extracting the sitting posture image of the user from the real-time data, timely discover the balance problems of the sitting balance training chair, and identify the position coordinates of the key body parts of the user to understand the body inclination of the user in the sitting state. The tilt condition and the displacement condition of the center of gravity of the body can accurately evaluate the user's sitting posture stability and the balance performance of the chair itself, and provide a scientific basis and guidance for sitting balance training; the embodiment of the present invention can identify the key features of the sitting balance training chair from the fusion data, and can judge the stability of the user in different actions by analyzing the pressure distribution and acceleration changes; further, the embodiment of the present invention can understand the stability of the sitting balance training chair under dynamic conditions by combining the posture features and the key features, improve the accuracy and reliability of the balance state evaluation of the sitting balance training chair, and combine the use of The invention can provide a balance monitoring standard for the sitting balance training chair, identify the unbalanced sitting posture of the user, and provide personalized guidance suggestions according to the basic information data of the user; the embodiment of the invention sets a balance judgment baseline for the sitting balance training chair based on the balanced sitting posture and the balanced state, and can identify the abnormal situation of the sitting balance training chair by monitoring the balanced state of the sitting balance training chair, thereby improving the safety of the sitting balance training chair, and identify the unbalanced state of the sitting balance training chair according to the balance judgment baseline, and set a feedback mechanism for the unbalanced state, so as to timely discover the unbalanced state of the sitting balance training chair when the unbalanced state occurs. And control potential safety risks to ensure the safety and reliability of the training process; the embodiment of the present invention combines the multi-attribute monitor, the balance judgment baseline and the feedback mechanism to monitor the balance of the sitting balance training chair to obtain a balance monitoring result. The data collected by the multi-attribute monitor, combined with the evaluation results of the balance judgment baseline and the immediate adjustment of the feedback mechanism, can form a closed-loop monitoring and training system. The system can not only monitor the subtle changes in the body posture of the user and the balance state of the sitting balance training chair, but also adaptively adjust the imbalance state of the sitting balance training chair, thereby improving the user's sitting balance ability and the overall rehabilitation effect. Therefore, the balance monitoring method of a sitting balance training chair proposed in the embodiment of the present invention can improve the balance monitoring accuracy of the sitting balance training chair.

[0080] like Figure 2FIG. 1 is a diagram showing a system functional module of a balance monitoring system for a sitting balance training chair according to the present invention.

[0081] The balance monitoring system 200 of the sitting balance training chair of the present invention can be installed in an electronic device. According to the functions to be implemented, the balance monitoring system of the sitting balance training chair can include a data monitoring module 201, a posture feature recognition module 202, a key feature extraction module 203, a balanced sitting posture analysis module 204, and a monitoring result output module 205. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0082] In the embodiment of the present invention, the functions of each module / unit are as follows: The data monitoring module 201 is used to obtain the seated balance training chair to be monitored and its corresponding user, identify the sensitive parts of the seated balance training chair, and set a multi-attribute monitor of the seated balance training chair based on the sensitive parts, wherein the multi-attribute monitor includes a pressure sensor, an inertial measurement unit and an image acquisition device, and monitor the real-time data of the seated balance training chair based on the multi-attribute monitor; A posture feature recognition module 202 is used to extract a sitting posture image of the user from the live data, identify the position coordinates of the key body parts according to the sitting posture image, calculate the inclination angle and distance ratio of the key body parts based on the position coordinates, and analyze the posture feature of the user according to the inclination angle and the distance ratio; A key feature extraction module 203 is used to extract the pressure sensor data and the inertial measurement data of the real-time data according to the multi-attribute monitor, perform data fusion processing on the pressure sensor data and the inertial measurement data to obtain fused data, and identify the key features of the sitting balance training chair from the fused data; A balanced sitting posture analysis module 204 is used to analyze the balance state of the sitting balance training chair in combination with the posture feature and the key feature, dispatch the basic information data of the user, wherein the basic information data includes age data and physical condition data, and identify the balanced sitting posture of the user according to the basic information data, the posture feature and the key feature; The monitoring result output module 205 is used to set a balance judgment baseline for the sitting balance training chair based on the balanced sitting posture and the balanced state, identify the unbalanced state of the sitting balance training chair according to the balance judgment baseline, and set a feedback mechanism for the unbalanced state, and combine the multi-attribute monitor, the balance judgment baseline and the feedback mechanism to perform balance monitoring on the sitting balance training chair to obtain a balance monitoring result.

[0083] In detail, the modules in the balance monitoring system 200 of the sitting balance training chair described in the embodiment of the present invention are used in the same manner as described above. Figure 1 The same technical means as the method for balance monitoring of a sitting balance training chair described in the invention can produce the same technical effects, which will not be described in detail here.

[0084] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A balance monitoring method for a sitting balance training chair, characterized in that: The method comprises: Acquire a sitting balance training chair to be monitored and its corresponding user, identify sensitive parts of the sitting balance training chair, and set a multi-attribute monitor for the sitting balance training chair based on the sensitive parts, wherein the multi-attribute monitor includes a pressure sensor, an inertial measurement unit, and an image acquisition device, and monitor the real-time data of the sitting balance training chair based on the multi-attribute monitor; Extracting a sitting posture image of the user from the live data, identifying position coordinates of key body parts according to the sitting posture image, calculating the inclination angle and distance ratio of the key body parts based on the position coordinates, and analyzing the posture characteristics of the user according to the inclination angle and the distance ratio; According to the multi-attribute monitor, extract the pressure sensor data and the inertial measurement data of the real-time data, perform data fusion processing on the pressure sensor data and the inertial measurement data to obtain fused data, and identify the key features of the sitting balance training chair from the fused data; In combination with the posture feature and the key feature, the balance state of the sitting balance training chair is analyzed, basic information data of the user is dispatched, wherein the basic information data includes age data and physical condition data, and the balanced sitting posture of the user is identified according to the basic information data, the posture feature and the key feature; Based on the balanced sitting posture and the balanced state, a balance judgment baseline of the sitting balance training chair is set, and according to the balance judgment baseline, the unbalanced state of the sitting balance training chair is identified, and a feedback mechanism for the unbalanced state is set. In combination with the multi-attribute monitor, the balance judgment baseline and the feedback mechanism, balance monitoring is performed on the sitting balance training chair to obtain a balance monitoring result.

2. The method according to claim 1, characterized in that The step of identifying the sensitive parts of the sitting balance training chair comprises: Acquiring the physical structure of the sitting balance training chair; Based on the physical structure, identifying the force-bearing surface of the sitting balance training chair; Extracting key stress points of the stress-bearing surface; Identify the specific position of the key force point on the sitting balance training chair; Based on the specific position, a sensitive part of the sitting balance training chair is identified.

3. The method according to claim 1, characterized in that The step of identifying the position coordinates of the key body parts according to the sitting posture image includes: According to the sitting posture image, background removal processing is performed on the key body parts to obtain body parts; Locating the limb position corresponding to the body part, and constructing an image coordinate system of the body part according to the limb position; Identify key points of the limb position, and calculate coordinate values ​​of the key points according to the image coordinate system; Based on the coordinate values, the position coordinates of the key body parts are identified.

4. The method according to claim 1, characterized in that: The step of calculating the tilt angle of the key body part based on the position coordinates includes: Based on the position coordinates, defining a relative reference plane of the key body part, and calculating the spatial coordinates of the relative reference plane; Performing coordinate conversion on the position coordinates to obtain three-dimensional coordinates; According to the three-dimensional coordinates, identifying the key point coordinates of the key body part; Based on the key point coordinates and the space coordinates, the direction vector of the key body part is calculated using the following formula: ； in, represents the direction vector of the key body parts, represents the spatial coordinates, represents the key point coordinates, Indicates the direction value of the key point coordinate displacement on the x-axis to the space coordinate. Indicates the direction value of the key point coordinate displacement on the y-axis to the spatial coordinate. Indicates the direction value of the key point coordinate displacement on the z-axis to the spatial coordinate; Obtaining a normal vector relative to the reference surface; The vector angle between the direction vector and the normal vector is calculated using the following formula: ； in, represents the vector angle between the direction vector and the normal vector, represents the direction vector, b represents the normal vector, represents the magnitude of the direction vector, Represents the modulus of the normal vector; Based on the vector angle, the inclination angle of the key body part is obtained.

5. The method according to claim 1, characterized in that The identifying key features of the sitting balance training chair from the fused data includes: Identifying data classification of the fused data, and identifying characteristic elements of the data classification; Performing time series analysis on the characteristic elements to obtain time series change data; Based on the time series change data, construct a change rate curve of the characteristic element; extracting the peak position of the characteristic element from the change rate curve; Analyzing the influence of the characteristic element on the sitting balance training chair according to the peak position; Based on the influence degree, key features of the sitting balance training chair are extracted.

6. The method according to claim 1, characterized in that The step of analyzing the balance state of the sitting balance training chair by combining the posture feature and the key feature includes: identifying a user of the sitting balance training chair according to the posture characteristics; identifying a muscle activation pattern of the user during a sitting posture, and analyzing the user's body balance ability based on the muscle activation pattern; dispatching the live data of the key features, and identifying the angular velocity data and acceleration data of the sitting balance training chair based on the live data; Analyzing the flight posture of the sitting balance training chair during the sitting process based on the acceleration data and the angular velocity data; Analyzing the dynamic stability of the sitting balance training chair according to the flight posture; The balance state of the sitting balance training chair is analyzed in combination with the body balance ability and the dynamic stability.

7. The method according to claim 1, characterized in that The identifying the balanced sitting posture of the user according to the basic information data, the posture feature and the key feature includes: Identify the group characteristics of the user objects according to the basic information data; Based on the group characteristics, setting a normative level of the posture characteristics; Analyzing the change trajectory of the key features according to the specification level; Based on the change trajectory, analyzing the abnormal change of the sitting balance training chair; Identifying the body balance of the user under the abnormal condition; The balanced sitting posture of the user is identified according to the body balance force.

8. The method according to claim 1, characterized in that The step of setting a balance judgment baseline of the sitting balance training chair based on the balanced sitting posture and the balanced state includes: Based on the balanced sitting posture, identifying a user of the sitting balance training chair; Identify key indicators of the user in the balanced sitting posture; Based on the balance state, collecting balance state data of the sitting balance training chair; Extracting the static sitting posture and the dynamic sitting posture of the user in the balanced sitting posture; Analyzing the static balance requirement and the dynamic balance requirement of the user based on the static sitting posture and the dynamic sitting posture; According to the static balance requirement, setting the static balance baseline of the sitting balance training chair; Based on the dynamic balance requirement, testing the motion tolerance limit of the sitting balance training chair to the user; According to the action tolerance limit, setting the dynamic balance baseline of the sitting balance training chair; The balance judgment baseline of the sitting balance training chair is set in combination with the static balance baseline and the dynamic balance baseline.

9. The method according to claim 1, characterized in that: The step of setting the feedback mechanism of the imbalance state according to the balance judgment baseline includes: identifying abnormal factors of the imbalance state according to the balance judgment baseline; Setting an abnormal alarm for the abnormal factor; Analyze the influencing conditions of the abnormal factors, and set a state adjustment mechanism of the abnormal factors according to the influencing conditions; In combination with the abnormal alarm and the state adjustment mechanism, a feedback mechanism for the unbalanced state is provided.

10. A balance monitoring system for a sitting balance training chair, characterized in that: The system comprises: A data monitoring module, used for acquiring a seated balance training chair to be monitored and its corresponding user, identifying sensitive parts of the seated balance training chair, and setting a multi-attribute monitor of the seated balance training chair based on the sensitive parts, wherein the multi-attribute monitor includes a pressure sensor, an inertial measurement unit and an image acquisition device, and based on the multi-attribute monitor, real-time monitoring of the live data of the seated balance training chair; a posture feature recognition module, configured to extract a sitting posture image of the user from the live data, recognize position coordinates of key body parts according to the sitting posture image, calculate an inclination angle and a distance ratio of the key body parts based on the position coordinates, and analyze the posture feature of the user according to the inclination angle and the distance ratio; A key feature extraction module, for extracting the pressure sensor data and the inertial measurement data of the real-time data according to the multi-attribute monitor, performing data fusion processing on the pressure sensor data and the inertial measurement data to obtain fused data, and identifying the key features of the sitting balance training chair from the fused data; A balanced sitting posture analysis module, used to analyze the balance state of the sitting balance training chair in combination with the posture feature and the key feature, dispatch the basic information data of the user, wherein the basic information data includes age data and physical condition data, and identify the balanced sitting posture of the user according to the basic information data, the posture feature and the key feature; A monitoring result output module is used to set a balance judgment baseline for the sitting balance training chair based on the balanced sitting posture and the balanced state, identify the unbalanced state of the sitting balance training chair according to the balance judgment baseline, and set a feedback mechanism for the unbalanced state, and combine the multi-attribute monitor, the balance judgment baseline and the feedback mechanism to perform balance monitoring on the sitting balance training chair to obtain a balance monitoring result.

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