Self-adaptive orthopedic rehabilitation management system

Abstract

The invention relates to the technical field of orthopedic rehabilitation management, in particular to a self-adaptive orthopedic rehabilitation management system, which comprises a training module, an acquisition module, an evaluation module and an adjustment module, and is characterized in that the training module is used for assisting a user to execute training actions; the acquisition module is used for respectively acquiring the actuating muscle force, the actuating range and the breathing frequency of the user for executing the training action; the evaluation module is configured to generate an evaluation result of the training action process executed by the user on the basis of the difference between the action range and the standard action range, the difference between the action muscle force and the standard muscle force and the respiratory rate; the adjusting module is configured to correct the training level of the next training action based on the evaluation result, or output a rehabilitation prompt; through comprehensive analysis of the muscle force and the actuation range, the rehabilitation degree of the orthopedics department can be effectively evaluated, then the rehabilitation training intensity is accurately and adaptively adjusted, and the adaptability and timeliness of the rehabilitation management system for the orthopedics department are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of orthopedic rehabilitation management, and in particular to an adaptive orthopedic rehabilitation management system. Background Art

[0002] Orthopedic rehabilitation is a systematic recovery process for patients with injuries to bones, muscles, joints, ligaments and other muscular systems or after surgery. It aims to restore limb function, relieve pain and prevent complications through scientific intervention. Rehabilitation exercise training is an indispensable part of the orthopedic rehabilitation process. The patient's recovery process can be optimized through reasonable and effective monitoring and control of the rehabilitation training process.

[0003] For example, in the prior art, a Chinese patent application with publication number CN118800397A discloses an artificial intelligence-based orthopedic joint replacement postoperative rehabilitation training monitoring system, including a rehabilitation supervision platform, an information collection unit, a recovery evaluation unit, a training supervision unit, a rehabilitation monitoring unit, a periodic recovery evaluation unit, and a management response unit; it analyzes the target patient's rehabilitation joint training from two points of view: the training appearance performance and the internal rehabilitation monitoring, so as to understand the rehabilitation status of the target patient in the current rehabilitation cycle, and performs information fusion-type periodic recovery evaluation analysis through information feedback and information fusion, and rationally adjusts and manages subsequent rehabilitation training decisions based on the information feedback, so as to speed up the recovery rate of the target patient's rehabilitation joint, and analyzes from the perspective of training appearance performance, and analyzes in combination with rehabilitation training information, so as to understand the recovery status of the target patient's rehabilitation joint, and then reasonably adjust the rehabilitation training program.

[0004] However, in the above technical solutions, there is a situation where neither the external manifestations nor the internal rehabilitation data can detect the actual recovery status in time due to muscle strength compensation, and thus the adaptability and timeliness of orthopedic rehabilitation management cannot be effectively guaranteed. Summary of the invention

[0005] The purpose of the present invention is to provide an adaptive orthopedic rehabilitation management system to solve the problem in the prior art that neither the external manifestation nor the internal rehabilitation data can timely detect the actual recovery status due to muscle strength compensation, thereby failing to effectively guarantee the adaptability and timeliness of orthopedic rehabilitation management.

[0006] To this end, the present invention provides an adaptive orthopedic rehabilitation management system, which includes a training module, an acquisition module, an evaluation module and an adjustment module. The training module is used to assist users in performing training movements; the acquisition module respectively acquires the actuation muscle strength, actuation range and breathing frequency of the user performing the training movements; the evaluation module is configured to generate an evaluation result of the user's execution of the training movement process based on the difference between the actuation range and the standard actuation range, the difference between the actuation muscle strength and the standard muscle strength, and the breathing frequency; the adjustment module is configured to correct the training level of the next training movement based on the evaluation result, or output a rehabilitation reminder.

[0007] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the evaluation module determines whether the actuation range is smaller than the standard actuation range. If not, determine whether the actuating muscle strength is less than the standard muscle strength. If so, output the evaluation result to the adjustment module, and the adjustment module outputs an orthopedic rehabilitation reminder. If not, output the evaluation result to the adjustment module, and the adjustment module outputs an overall rehabilitation reminder.

[0008] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the evaluation module determines whether the actuation range is smaller than the standard actuation range, and if so, outputs the evaluation result to the adjustment module, and the adjustment module: quantifying the actuation range and the standard actuation range based on the angle, and determining the angle difference between the standard actuation range and the actuation range based on the angle quantification, Generate an orthopedic rehabilitation assessment parameter based on the angle difference, the actuating muscle force and the respiratory rate; Among them, the orthopedic rehabilitation assessment parameter is negatively correlated with the angle difference, negatively correlated with the actuator muscle strength, and negatively correlated with the respiratory frequency.

[0009] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the adjustment module corrects the training level of the next training action based on the orthopedic rehabilitation evaluation parameter; Specifically, if the orthopedic rehabilitation assessment parameter exceeds the preset range, the training level of the next training action will be increased. If the orthopedic rehabilitation assessment parameter goes below the preset range, the training level of the next training action will be reduced. If the orthopedic rehabilitation assessment parameters are within the preset range, the training level of the next training action is maintained.

[0010] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the specific process of the adjustment module quantifying the actuation range based on the angle includes: The corresponding joint is taken as the reference point, and the end of the limb away from the corresponding joint is taken as the motion point, and the actuation angle of the motion point relative to the reference point is determined.

[0011] As an optimal technical solution for an adaptive orthopedic rehabilitation management system, the acquisition module identifies the muscle strength distribution of the user when performing training movements, and obtains isostrength areas with the same muscle strength, and takes the average muscle strength of each isostrength area within the influence range of the corresponding joint as the actuating muscle strength of the user to perform the training movements.

[0012] As a preferred technical solution for the adaptive orthopedic rehabilitation management system, the acquisition module identifies the muscle force distribution of the user when performing training movements through a muscle force sensor.

[0013] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the process of the acquisition module acquiring the isostrength area with the same muscle strength includes: Perform spatial interpolation on the EMG sensor data to generate a muscle force distribution heat map; The DBSCAN clustering algorithm was used to identify iso-muscle strength areas.

[0014] As a preferred technical solution for the adaptive orthopedic rehabilitation management system, the acquisition module identifies the user's range of motion through an inertial measurement unit installed at the end of the limb away from the corresponding joint.

[0015] As a preferred technical solution for the adaptive orthopedic rehabilitation management system, the acquisition module identifies the user's breathing frequency by interacting with the data of the smart bracelet.

[0016] The beneficial effects of the present invention are: The present invention can effectively evaluate the degree of orthopedic rehabilitation through comprehensive analysis of muscle strength and range of motion, and then accurately and adaptively adjust the intensity of rehabilitation training, effectively improving the adaptability and timeliness of the orthopedic rehabilitation management system.

[0017] Furthermore, the present invention performs correlation analysis between the range of motion and the standard range of motion, and the difference between the actuation muscle strength and the standard muscle strength, to effectively identify situations where the user has normal muscle strength but poor orthopedic recovery, and takes into account the degree of physical recovery in performing training movements, which can be effectively represented by the breathing rate. On the one hand, it avoids the misjudgment of orthopedic recovery caused by sufficient muscle strength to reach a certain range of motion, and on the other hand, it avoids omissions in the analysis of situations where the range of motion is normal but the muscle strength is poor. Based on the identification of the above situations, it can further discover whether the physical strength is abnormal through the breathing rate. The evaluation results obtained by combining the above three can effectively represent the user's ability to perform the current training movements, thereby achieving precise adaptation and adaptive adjustment of orthopedic rehabilitation training.

[0018] Furthermore, the present invention constructs a dynamic closed-loop logic for orthopedic rehabilitation assessment through multi-dimensional collaborative analysis of muscle strength, range of motion and respiratory rate, achieving precise adaptation of the entire chain from data collection to training adjustment. Traditional methods often lead to two types of misjudgments due to their sole reliance on joint mobility or muscle strength indicators: one is that muscle strength compensation masks insufficient joint recovery, leading to the misjudgment of good recovery; the other is ignoring potential risks when joint mobility meets standards but muscle strength is insufficient. This solution decouples the analysis of orthopedic recovery, muscle function and physical exertion through a cascade judgment mechanism combined with dynamic correction of respiratory rate, further improving the adaptability and accuracy of the rehabilitation management system.

[0019] Furthermore, the present invention converts the subjective rehabilitation state into a quantifiable evaluation parameter through muscle force distribution feature extraction and dynamic angle tracking based on inertial measurement, forming an adaptive closed loop of "assessment-adjustment-reassessment", further improving the adaptability and accuracy of the rehabilitation management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a structural block diagram of an adaptive orthopedic rehabilitation management system in an embodiment of the present invention; Figure 2 4 is a flowchart of the adaptive orthopedic rehabilitation management system in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0023] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0024] like Figure 1As shown, the present embodiment provides an adaptive orthopedic rehabilitation management system, which includes a training module, an acquisition module, an evaluation module and an adjustment module. The training module is used to assist the user in performing training movements; the acquisition module respectively acquires the actuation muscle strength, actuation range and breathing frequency of the user in performing the training movements; the evaluation module is configured to generate an evaluation result of the user's training movement process based on the difference between the actuation range and the standard actuation range, the difference between the actuation muscle strength and the standard muscle strength, and the breathing frequency; the adjustment module is configured to correct the training level of the next training movement based on the evaluation result, or output a rehabilitation reminder.

[0025] In the above embodiment, correlation analysis is performed through the actuation range and the standard actuation range, as well as the difference between the actuation muscle strength and the standard muscle strength, so as to effectively identify the situation where the user has normal muscle strength but poor orthopedic recovery, and take into account the degree of physical recovery in performing training movements, which can be effectively represented by the breathing frequency. On the one hand, it avoids the misjudgment of orthopedic recovery caused by sufficient muscle strength to reach a certain actuation range, and on the other hand, it can avoid the omission of analysis of the situation where the actuation range is normal but the muscle strength is poor. On the basis of identifying the above situations, it can be further discovered whether the physical strength is abnormal through the breathing frequency. The evaluation results obtained by combining the above three can effectively represent the user's ability to perform the current training movements, thereby achieving precise adaptation and adaptive adjustment of orthopedic rehabilitation training.

[0026] See also Figure 2 As shown, the evaluation module determines whether the range of motion of the user is smaller than the standard range of motion during the user's training action. If not, determine whether the actuating muscle strength is less than the standard muscle strength. If so, output the evaluation result to the adjustment module, and the adjustment module outputs an orthopedic rehabilitation reminder. If not, output the evaluation result to the adjustment module, and the adjustment module outputs an overall rehabilitation reminder. If yes, the evaluation result is output to the adjustment module, and the adjustment module performs the following process: Based on the angle quantification of the actuation range and the standard actuation range, and determining the angle difference between the standard actuation range and the actuation range based on the angle quantification, Generate orthopedic rehabilitation assessment parameters based on angle difference, muscle strength and respiratory rate. Among them, the orthopedic rehabilitation assessment parameter is negatively correlated with the angle difference, negatively correlated with the actuation muscle strength, and negatively correlated with the respiratory rate. It should be understood that this embodiment adopts two different methods for determining the actuation range at different stages. One is to directly compare whether the actuation range is smaller than the standard actuation range based on the actual display of the training device. It can be determined by whether the user can actuate to the specified position (the actuation range of the user to the specified position is the standard actuation range). The second is to quantify the actuation range and the standard actuation range through angles. At this time, accurate numerical representation is required for further parameter determination and training correction, which can effectively reduce the computing power consumption of the device while ensuring practicality.

[0027] In the above embodiment, the evaluation module adopts cascade judgment logic and dynamic priority allocation mechanism, and its technical principle is: first, the basic conditions for orthopedic recovery are judged by comparing the range of motion with the standard value. If the standard is not met, the orthopedic rehabilitation reminder is directly triggered; when the range of motion meets the standard, the muscle strength matching is further verified. If the muscle strength is insufficient, it is judged that the muscle function recovery is lagging behind; only when both meet the standard, it is determined to enter the overall rehabilitation stage. This technical path solves the misjudgment problem of traditional single indicator evaluation through a double verification mechanism: when the joint range of motion meets the standard but the muscle strength is insufficient, it avoids mistaking the orthopedic recovery for completion; when the muscle strength meets the standard but the range of motion is limited, the orthopedic recovery defects are accurately identified. At the same time, combined with respiratory rate monitoring, the evaluation results are dynamically corrected to prevent false standards caused by physical overdraft, so that the timeliness of rehabilitation program adjustment is improved to minute-level response. Of course, when outputting orthopedic rehabilitation reminders or overall rehabilitation reminders, the remaining physical signs should also meet the corresponding normal signs.

[0028] Exemplarily, in this embodiment, the orthopedic rehabilitation assessment parameter P is used to correct the training level. The orthopedic rehabilitation assessment parameter P is determined based on the following formula: , Among them, Δθ max is the standard actuation range after angle quantification, Δθ is the actuation range after angle quantification, F is the actuation muscle force, F max is the standard muscle strength, f R is the respiratory rate, f R0is the reference value of respiratory rate (16 times / min in this embodiment), α, β and γ are weight coefficients, in this embodiment, α is 0.5, β is 0.3, γ is 0.1, and α, β and γ can be calibrated and modified according to the actual scenario. The above formula takes into account the influence of muscle compensation on the range of motion, and can effectively remove this influence on the evaluation of the special effect of orthopedic rehabilitation. Through multi-dimensional collaborative analysis of muscle strength, range of motion and respiratory rate, a dynamic closed-loop logic for orthopedic rehabilitation evaluation is constructed, and accurate adaptation of the entire chain from data collection to training adjustment is achieved. Traditional methods often lead to two kinds of misjudgments due to their single reliance on joint range of motion or muscle strength indicators: one is that muscle compensation masks insufficient joint recovery and is misjudged as good recovery; the other is that potential risks are ignored when the joint range of motion meets the standard but the muscle strength is insufficient. This scheme decouples orthopedic recovery, muscle function and physical exertion through a cascade judgment mechanism combined with dynamic correction of respiratory rate, further improving the adaptability and accuracy of the rehabilitation management system.

[0029] In detail, the training level of the next training action is corrected based on the orthopedic rehabilitation assessment parameter, which specifically includes: if the orthopedic rehabilitation assessment parameter exceeds the preset range, the training level of the next training action is increased; If the orthopedic rehabilitation assessment parameter goes below the preset range, the training level of the next training action will be reduced. If the orthopedic rehabilitation assessment parameter is within the preset range, the training level of the next training action is maintained. It is understandable that the preset range is dynamically set based on clinical statistical data and individual rehabilitation stages, and needs to be calibrated in combination with actual scenarios to meet the best rehabilitation training effect of users within the preset range. The division of training levels can be finely divided based on the duration of training movements, movement resistance and standard range of motion (the standard range of motion should change with the rehabilitation process), and the shorter the duration of the training movement, the higher the training level, and the larger the standard range of motion and movement resistance, the higher the training level. Through the synergy of orthopedic rehabilitation assessment parameters and preset ranges, precise and adaptive adjustment of orthopedic rehabilitation training is achieved. Its hierarchical response strategy significantly improves rehabilitation efficiency while ensuring safety, and provides a quantifiable technical path for intelligent rehabilitation management. In the above embodiment, through the dynamic monitoring of orthopedic rehabilitation assessment parameters (P values) and the synergy of preset ranges, precise adjustment of training levels is achieved, which significantly improves the adaptability and safety of rehabilitation training. When the P value exceeds the preset range, the system automatically adjusts the training level upward, accelerates functional reconstruction and avoids rehabilitation stagnation by increasing resistance, expanding the range of motion or shortening the duration of training movements (maintaining training movements only increases the speed of the training module); when the P value exceeds the preset range, the system automatically adjusts the training level downward, effectively preventing secondary injuries and relieving fatigue accumulation by reducing resistance or reducing the range of motion and extending the actuation time; when the P value is within the preset range, the system maintains the current training level and continuously monitors the trend of P value changes. If it approaches the boundary, it triggers an early warning prompt to ensure the stability of the rehabilitation process. Through the above mechanism, the system can dynamically adjust the training intensity according to the patient's real-time status, significantly improve the matching degree between the training intensity and the patient's needs, significantly reduce the interruption rate of users due to discomfort in intensity, and greatly shorten the response delay of abnormal events, which is significantly more efficient than the traditional manual adjustment scheme. In addition, the graded response strategy ensures joint stability through the coordinated adjustment of resistance and range of motion, providing a scientific and reliable technical path for intelligent rehabilitation management.

[0030] Specifically, the specific process of the adjustment module based on the angle quantification range includes: The corresponding joint is used as the reference point, and the end of the limb away from the corresponding joint is used as the motion point to determine the actuation angle of the motion point relative to the reference point. Specifically, the acquisition module identifies the user's actuation range through the inertial measurement unit installed at the end of the limb away from the corresponding joint. Through the synergy of joint angle quantification and inertial measurement unit, accurate measurement and dynamic feedback of the actuation range are achieved, significantly improving the accuracy and real-time performance of orthopedic rehabilitation assessment. The corresponding joint is used as the reference point, and the distal end of the limb is used as the motion point. The actuation angle is determined by calculating the spatial position change of the motion point relative to the reference point. The core of this process is to use the inertial measurement unit installed at the distal end of the limb to collect motion data in real time, including acceleration, angular velocity and magnetic field strength, and to convert the raw data into joint rotation angles through quaternion algorithms. The high sampling rate and low latency characteristics of the inertial measurement unit ensure the real-time performance of angle measurement, and its anti-interference ability further improves the reliability of the data. By comparing the quantified actuation angle with the standard actuation range, the system can dynamically identify the recovery state of joint mobility and generate comprehensive evaluation results in combination with muscle strength and respiratory rate data. This technical approach not only solves the problems of low efficiency and large errors in traditional solutions, but also realizes dynamic adjustment of training intensity through real-time feedback mechanism, which significantly improves the adaptability of rehabilitation training. In addition, the non-invasive installation method of the inertial measurement unit avoids the sense of restraint of traditional sensors, significantly improving user experience and compliance.

[0031] Specifically, the acquisition module identifies the muscle strength distribution of the user when performing the training action, and obtains the isostrength areas with the same muscle strength, and takes the average muscle strength of each isostrength area within the influence range of the corresponding joint as the actuating muscle strength of the user to perform the training action.

[0032] Specifically, the acquisition module identifies the user's breathing rate by interacting with the data of the smart bracelet, and the breathing rate can also be obtained through the respiratory piezoelectric sensor integrated in the chest strap. The acquisition module identifies the muscle force distribution of the user when performing training movements through the muscle force sensor. In detail, the electromyographic sensor array is arranged at the attachment point of the target muscle group, the sampling rate should be ≥1000Hz, and it contains 16-channel differential electrodes; Based on the above embodiment, the process of the acquisition module acquiring the iso-muscle strength area with the same muscle strength includes: Perform spatial interpolation on the EMG sensor data to generate a muscle force distribution heat map; The DBSCAN clustering algorithm is used to identify equal muscle strength areas. Through muscle strength distribution identification and equal muscle strength area extraction technology, accurate quantification and dynamic evaluation of the actuating muscle strength are achieved, which significantly improves the scientificity and adaptability of orthopedic rehabilitation management. Specifically, the acquisition module uses a high-density electromyographic sensor array to monitor the muscle strength distribution of the user when performing training movements in real time, uses a spatial interpolation algorithm to generate a muscle strength distribution heat map, and identifies equal muscle strength areas with similar muscle strength levels through cluster analysis. The system further selects the equal muscle strength areas within the influence range of the corresponding joints and calculates their average muscle strength as the actuating muscle strength. The core of this process is to eliminate the interference of local muscle activation abnormalities (such as tremor or fatigue) on the overall muscle strength assessment through the synchronous acquisition and fusion processing of multi-channel electromyographic signals, and ensure the representativeness and reliability of the data. By comparing the actuating muscle strength with the standard muscle strength, the system can dynamically identify the recovery state of muscle function and generate comprehensive evaluation results in combination with joint range of motion and respiratory rate data. This technical approach not only solves the problem of single function and fragmented data of traditional muscle strength testing equipment, but also realizes a comprehensive assessment of rehabilitation status through multi-dimensional data fusion, significantly improving the adaptability of training programs. In addition, the visual analysis of muscle strength distribution provides therapists with an intuitive reference basis, further optimizing rehabilitation intervention strategies.

[0033] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the devices, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart can be implemented with a dedicated hardware-based device that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0034] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. An adaptive orthopedic rehabilitation management system, characterized in that: include: A training module, used to assist users in performing training actions; A collection module collects the actuation muscle strength, actuation range and breathing frequency of the user when performing the training action; An evaluation module configured to generate an evaluation result of the user's training action process based on the difference between the actuation range and the standard actuation range, the difference between the actuation muscle strength and the standard muscle strength, and the breathing frequency; An adjustment module, configured to modify the training level of the next training action based on the evaluation result, or output a rehabilitation reminder; The evaluation module determines whether the actuation range is smaller than the standard actuation range. If not, determine whether the actuating muscle strength is less than the standard muscle strength. If so, output the evaluation result to the adjustment module, and the adjustment module outputs an orthopedic rehabilitation reminder. If not, output the evaluation result to the adjustment module, and the adjustment module outputs an overall rehabilitation reminder. The evaluation module determines whether the actuation range is smaller than the standard actuation range, and if so, outputs the evaluation result to the adjustment module, and the adjustment module: quantifying the actuation range and the standard actuation range based on the angle, and determining the angle difference between the standard actuation range and the actuation range based on the angle quantification, Generate an orthopedic rehabilitation assessment parameter based on the angle difference, the actuating muscle force and the respiratory rate; Among them, the orthopedic rehabilitation assessment parameter is negatively correlated with the angle difference, positively correlated with the muscle strength difference, and negatively correlated with the respiratory frequency.

2. The adaptive orthopedic rehabilitation management system according to claim 1, characterized in that: The adjustment module corrects the training level of the next training action based on the orthopedic rehabilitation assessment parameter; Specifically, if the orthopedic rehabilitation assessment parameter exceeds the preset range, the training level of the next training action will be increased. If the orthopedic rehabilitation assessment parameter exceeds the preset range, the training level of the next training action will be reduced. If the orthopedic rehabilitation assessment parameters are within the preset range, the training level of the next training action is maintained.

3. The adaptive orthopedic rehabilitation management system according to claim 2, characterized in that: The specific process of the adjustment module quantifying the actuation range based on the angle includes: The corresponding joint is taken as the reference point, and the end of the limb away from the corresponding joint is taken as the motion point, and the actuation angle of the motion point relative to the reference point is determined.

4. The adaptive orthopedic rehabilitation management system according to claim 1, characterized in that: The acquisition module identifies the muscle strength distribution of the user when performing the training action, obtains isostrength areas with the same muscle strength, and uses the average muscle strength of each isostrength area within the influence range of the corresponding joint as the actuating muscle strength of the user to perform the training action.

5. The adaptive orthopedic rehabilitation management system according to claim 4, characterized in that: The acquisition module identifies the muscle force distribution of the user when performing training movements through the muscle force sensor.

6. The adaptive orthopedic rehabilitation management system according to claim 5, characterized in that: The process of obtaining the equal muscle strength area with the same muscle strength by the acquisition module includes: Perform spatial interpolation on the EMG sensor data to generate a muscle force distribution heat map; The DBSCAN clustering algorithm was used to identify iso-muscle strength areas.

7. The adaptive orthopedic rehabilitation management system according to claim 1, characterized in that: The acquisition module identifies the user's range of motion through an inertial measurement unit installed at the end of the limb away from the corresponding joint.

8. The adaptive orthopedic rehabilitation management system according to claim 1, characterized in that: The acquisition module identifies the user's breathing frequency by interacting with the data of the smart bracelet.

Images