An adaptive orthopedic rehabilitation management system

Abstract

The present invention relates to the technical field of orthopedic rehabilitation management, and particularly to an adaptive orthopedic rehabilitation management system. The system includes a training module, a collection module, an evaluation module, and an adjustment module. The training module is used to assist the user in performing training actions; the collection module respectively collects the acting muscle strength, acting range, and breathing frequency of the user when performing training actions; the evaluation module is configured to generate an evaluation result for the process of the user performing training actions based on the difference between the acting range and the standard acting range, the difference between the acting 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 action based on the evaluation result, or output a rehabilitation reminder; through the comprehensive analysis of muscle strength and acting range, the orthopedic rehabilitation degree can be effectively evaluated, and then the rehabilitation training intensity can be accurately and adaptively adjusted, effectively improving the adaptability and timeliness of the orthopedic rehabilitation management system.

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 or after surgeries in the musculoskeletal system including bones, muscles, joints, ligaments, etc. The aim is to restore limb function, relieve pain, and prevent complications through scientific interventions. Rehabilitation exercise training during the rehabilitation process is an essential part of orthopedic rehabilitation. By reasonably and effectively monitoring and controlling the rehabilitation training process, the patient's recovery process can be optimized.

[0003] For example, the Chinese patent application with the publication number CN118800397A in the prior art discloses an orthopedic joint replacement postoperative rehabilitation training monitoring system based on artificial intelligence, 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 from two aspects: the training appearance performance and the internal rehabilitation monitoring of the rehabilitation joint of the target patient to understand the rehabilitation situation of the target patient during the current rehabilitation cycle, and conducts information fusion-based periodic recovery evaluation analysis through information feedback and information fusion. It rationally adjusts and manages the subsequent rehabilitation training decision based on the information feedback situation to accelerate the recovery rate of the rehabilitation joint of the target patient. It also analyzes from the perspective of the training appearance performance and combines the rehabilitation training information to understand the recovery situation of the rehabilitation joint of the target patient, and then reasonably adjusts the rehabilitation training items.

[0004] However, in the above technical solution, there is a situation where the actual recovery status cannot be detected in a timely manner due to muscle strength compensation in both the appearance performance and the internal rehabilitation data, and thus the adaptability and timeliness of orthopedic rehabilitation management cannot be effectively ensured. 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 the actual recovery status cannot be detected in a timely manner due to muscle strength compensation in both the appearance performance and the internal rehabilitation data, and thus the adaptability and timeliness of orthopedic rehabilitation management cannot be effectively ensured.

[0006] To this end, the present invention provides an adaptive orthopedic rehabilitation management system, which includes a training module, a collection module, an evaluation module, and an adjustment module. The training module is used to assist the user in performing training actions; the collection module respectively collects the acting muscle strength, acting range, and breathing frequency of the user when performing the training actions; the evaluation module is configured to generate an evaluation result for the process of the user performing the training actions based on the difference between the acting range and the standard acting range, the difference between the acting 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 action 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 acting range is less than the standard acting range.

[0008] If not, it determines whether the acting muscle strength is less than the standard muscle strength. If so, it outputs the evaluation result to the adjustment module, and the adjustment module outputs an orthopedic rehabilitation reminder. If not, it outputs the evaluation result to the adjustment module, and the adjustment module outputs an overall rehabilitation reminder.

[0009] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the evaluation module determines whether the acting range is less than the standard acting range. If so, it outputs the evaluation result to the adjustment module, and the adjustment module:

[0010] Quantifies the acting range and the standard acting range based on the angle, and determines the angle difference between the standard acting range and the acting range after angle quantification.

[0011] Generates an orthopedic rehabilitation evaluation parameter based on the angle difference, the acting muscle strength, and the breathing frequency.

[0012] Among them, the orthopedic rehabilitation evaluation parameter is negatively correlated with the angle difference, negatively correlated with the acting muscle strength, and negatively correlated with the breathing frequency.

[0013] 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.

[0014] Specifically, if the orthopedic rehabilitation evaluation parameter exceeds the preset range upward, the training level of the next training action is increased.

[0015] If the orthopedic rehabilitation evaluation parameter exceeds the preset range downward, the training level of the next training action is decreased.

[0016] If the orthopedic rehabilitation evaluation parameter is within the preset range, the training level of the next training action is maintained.

[0017] 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

[0018] Taking the corresponding joint as the reference point and the end of the limb far from the corresponding joint as the movement point, determine the actuation angle of the movement point relative to the reference point.

[0019] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the acquisition module identifies the muscle force distribution when the user performs the training action, obtains the isomyotonic regions with the same muscle force, and takes the average muscle force of each isomyotonic region within the influence range of the corresponding joint as the actuation muscle force of the user when performing the training action.

[0020] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the acquisition module identifies the muscle force distribution when the user performs the training action through a muscle force sensor.

[0021] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the process of the acquisition module obtaining the isomyotonic regions with the same muscle force includes:

[0022] Perform spatial interpolation on the electromyography sensor data to generate a muscle force distribution heat map;

[0023] Use the DBSCAN clustering algorithm to identify the isomyotonic regions.

[0024] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the acquisition module identifies the user's actuation range through an inertial measurement unit installed at the end of the limb far from the corresponding joint.

[0025] As a preferred technical solution of the adaptive orthopedic rehabilitation management system, the acquisition module identifies the user's breathing frequency through data interaction with a smart bracelet.

[0026] The beneficial effects of the present invention are:

[0027] Through the comprehensive analysis of muscle force and actuation range, the present invention can effectively evaluate the degree of orthopedic rehabilitation, and then accurately and adaptively adjust the rehabilitation training intensity, effectively improving the adaptability and timeliness of the orthopedic rehabilitation management system.

[0028] Furthermore, the present invention performs correlation analysis through the differences between the actuation range and the standard actuation range, as well as the actuation muscle strength and the standard muscle strength, effectively identifying the situation where the user's muscle strength is normal but the orthopedic recovery is poor. Considering the degree of physical recovery during the execution of training actions, which can be effectively characterized by the breathing frequency, on the one hand, it avoids misjudgment of orthopedic recovery caused by sufficient muscle strength to reach a certain actuation range, and on the other hand, it can avoid the analysis omission of the situation where the actuation range is normal but the muscle strength is poor. Based on the identification of the above situations, it can further detect whether the physical strength is abnormal through the breathing frequency. The evaluation result obtained by integrating the above three aspects can effectively characterize the user's ability to perform the current training action, thereby realizing the precise adaptation and adaptive adjustment of orthopedic rehabilitation training.

[0029] Furthermore, the present invention constructs a dynamic closed-loop logic for orthopedic rehabilitation assessment through multi-dimensional collaborative analysis of muscle strength, actuation range, and breathing frequency, realizing full-chain precise adaptation from data collection to training adjustment. Traditional methods, due to relying solely on joint mobility or muscle strength indicators, often lead to two types of misjudgments: one is that muscle strength compensation masks insufficient joint recovery, misjudging as good rehabilitation; the other is ignoring potential risks when the joint mobility meets the standard but the muscle strength is insufficient. This solution decouples the analysis of orthopedic recovery, muscle function, and physical exertion through a cascading decision-making mechanism combined with the dynamic correction of breathing frequency, further improving the adaptability and precision of the rehabilitation management system.

[0030] Furthermore, the present invention extracts muscle strength distribution characteristics and performs dynamic angle tracking based on inertial measurement, converting the subjective rehabilitation state into quantifiable evaluation parameters, forming an adaptive closed-loop of "evaluation - adjustment - re-evaluation", further improving the adaptability and precision of the rehabilitation management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a structural block diagram of the adaptive orthopedic rehabilitation management system in an embodiment of the present invention;

[0032] Figure 2 It is a working flowchart of the adaptive orthopedic rehabilitation management system in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0033] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0034] In the description of the present invention, it should be noted that, unless otherwise clearly defined and limited, the terms "installation", "connection", and "coupling" 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 directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0035] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals represent the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are only used to explain the present invention and should not be construed as a limitation to the present invention.

[0036] As Figure 1 shown, this embodiment provides an adaptive orthopedic rehabilitation management system. The adaptive orthopedic rehabilitation management system includes a training module, a collection module, an evaluation module, and an adjustment module. The training module is used to assist the user in performing training actions; the collection module respectively collects the actuation muscle strength, actuation range, and breathing frequency of the user when performing training actions; the evaluation module is configured to generate an evaluation result for the process of the user performing training actions 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 action based on the evaluation result, or output a rehabilitation reminder.

[0037] In the above embodiment, through the correlation analysis of the actuation range and the standard actuation range, and the difference between the actuation muscle strength and the standard muscle strength, the situation where the user's muscle strength is normal but the orthopedic recovery is poor is effectively identified, and the degree of physical recovery during the execution of the training action is considered. The breathing frequency can effectively represent it. Therefore, on the one hand, the misjudgment of orthopedic recovery caused by sufficient muscle strength to reach a certain actuation range is avoided, and on the other hand, the analysis omission of the situation where the actuation range is normal but the muscle strength is poor is avoided. Based on the identification of the above situations, it is possible to further discover whether the physical strength is abnormal through the breathing frequency. The evaluation result obtained by combining the above three can effectively represent the ability of the user to perform the current training action, thereby realizing the precise adaptation and adaptive adjustment of orthopedic rehabilitation training.

[0038] Please refer to Figure 2 shown, when the evaluation module determines the process of the user performing the training action, whether the actuation range is less than the standard actuation range

[0039] Otherwise, 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;

[0040] If so, output the evaluation result to the adjustment module, and the adjustment module performs the following process:

[0041] Quantify the actuating range and the standard actuating range based on the angle, and determine the angle difference between the standard actuating range and the actuating range after angle quantification;

[0042] Generate an orthopedic rehabilitation evaluation parameter based on the angle difference, the actuating muscle strength, and the breathing frequency;

[0043] Among them, the orthopedic rehabilitation evaluation parameter is negatively correlated with the angle difference, negatively correlated with the actuating muscle strength, and negatively correlated with the breathing frequency. It should be understood that in this embodiment, the determination of the actuating range adopts two different methods at different stages. One is to directly compare whether the actuating range is less than the standard actuating range based on the actual display of the training device, which can be determined by whether the user can actuate to the specified position (the actuating range when the user actuates to the specified position is the standard actuating range). The other is to quantify the actuating range and the standard actuating range by angle. At this time, accurate numerical representations are required for further parameter determination and training correction, so as to effectively reduce the computing power consumption of the device while ensuring practicality.

[0044] In the above embodiment, the evaluation module adopts a cascaded decision-making logic and a dynamic priority allocation mechanism. Its technical principle is as follows: First, judge the basic conditions of orthopedic recovery by comparing the actuating range with the standard value. If the standard is not met, directly trigger an orthopedic rehabilitation reminder; after the actuating range meets the standard, further verify the muscle strength matching. If the muscle strength is insufficient, it is determined that the muscle function recovery is lagging; only when both meet the standards, it is determined to enter the overall rehabilitation stage. This technical path solves the misjudgment problem of traditional single-index evaluation through a double-verification mechanism: when the joint range of motion meets the standard but the muscle strength is insufficient, it avoids misjudging that the orthopedic recovery is completed; when the muscle strength meets the standard but the range of motion is limited, it accurately identifies the orthopedic recovery defect. At the same time, combined with the breathing frequency monitoring, dynamically correct the evaluation result to prevent false compliance caused by physical exhaustion, and improve the timeliness of the rehabilitation plan adjustment to a minute-level response. Of course, when outputting an orthopedic rehabilitation reminder or an overall rehabilitation reminder, the other physical signs should also meet the corresponding normal physical signs.

[0045] Exemplarily, in this embodiment, the orthopedic rehabilitation evaluation parameter P is used to correct the training level. The orthopedic rehabilitation evaluation parameter P is determined based on the following formula:

[0046] ,

[0047] where, Δθ maxis the standard actuation range after angle quantization, Δθ is the actuation range after angle quantization, F is the actuation muscle force, F max is the standard muscle force, f R is the respiratory rate, f R0 is the respiratory rate reference value (16 times / minute in this embodiment), α, β, and γ are weight coefficients. In this embodiment, α is 0.5, β is 0.3, and γ is 0.1. α, β, and γ can be calibrated and modified according to the actual scenario. The above formula takes into account the influence of muscle force compensation on the actuation range and can effectively remove this influence on the evaluation of the special effect of orthopedic rehabilitation. Through the multi-dimensional collaborative analysis of muscle force, actuation range, and respiratory rate, a dynamic closed-loop logic for orthopedic rehabilitation evaluation is constructed, realizing the full-chain precise adaptation from data collection to training adjustment. Traditional methods, due to relying solely on joint range of motion or muscle force indicators, often lead to two types of misjudgments: one is that muscle force compensation masks insufficient joint recovery and is misjudged as good rehabilitation; the other is that when the joint range of motion meets the standard but the muscle force is insufficient, potential risks are ignored. This solution decouples and analyzes orthopedic recovery, muscle function, and physical exertion through a cascaded decision-making mechanism combined with the dynamic correction of the respiratory rate, further improving the adaptability and precision of the rehabilitation management system.

[0048] Specifically, modifying the training level of the next training action based on the orthopedic rehabilitation evaluation parameter specifically includes: if the orthopedic rehabilitation evaluation parameter exceeds the preset range upward, the training level of the next training action is increased.

[0049] If the orthopedic rehabilitation evaluation parameter exceeds the preset range downward, the training level of the next training action is decreased.

[0050] If the orthopedic rehabilitation evaluation parameter is within the preset range, the training level of the next training action is maintained. It can be understood that the preset range is dynamically set based on clinical statistical data and individual rehabilitation stages, and needs to be calibrated in combination with the actual scenario. As long as the rehabilitation training effect of the user within the preset range is the best, the division of the training level can be finely divided based on the training action duration, action resistance, and standard action range (the standard action range should change with the rehabilitation process). It is sufficient that the smaller the training action duration, the higher the training level, and the larger the standard action range and action resistance, the higher the training level. Through the synergistic effect of the orthopedic rehabilitation evaluation parameter and the preset range, the precision and adaptive adjustment of orthopedic rehabilitation training are achieved. Its hierarchical response strategy significantly improves the rehabilitation efficiency while ensuring safety, providing a quantifiable technical path for intelligent rehabilitation management. In the above embodiment, through the dynamic monitoring of the orthopedic rehabilitation evaluation parameter (P value) and the synergistic effect of the preset range, the precise adjustment of the training level is achieved, significantly improving the adaptability and safety of the rehabilitation training. When the P value exceeds the preset range upwards, the system automatically increases the training level, accelerating functional reconstruction and avoiding rehabilitation stagnation by increasing resistance, expanding the movement amplitude, or shortening the training action duration (maintaining the training action and only increasing the movement speed of the training module); when the P value exceeds the preset range downwards, the system automatically decreases the training level, effectively preventing secondary injuries and alleviating fatigue accumulation by reducing resistance or narrowing the movement amplitude and prolonging the action time; when the P value is within the preset range, the system maintains the current training level, and at the same time continuously monitors the change trend of the P value. If it approaches the boundary, a warning prompt is triggered to ensure the stability of the rehabilitation process. Through the above mechanism, the system can dynamically adjust the training intensity according to the real-time state of the patient, significantly improving the matching degree between the training intensity and the patient's needs, significantly reducing the interruption rate caused by inappropriate intensity for the user, and at the same time greatly shortening the response delay of abnormal events, with significantly improved efficiency compared to the traditional manual adjustment scheme. In addition, the hierarchical response strategy ensures joint stability through the coordinated adjustment of resistance and movement amplitude, providing a scientific and reliable technical path for intelligent rehabilitation management.

[0051] Specifically, the specific process of the adjustment module for quantifying the action range based on the angle includes,

[0052] Taking the corresponding joint as the reference point and the end of the limb away from the corresponding joint as the movement point, the actuation angle of the movement point relative to the reference point is determined. 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 cooperation of joint angle quantization and the 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. Taking the corresponding joint as the reference point and the distal end of the limb as the movement point, the actuation angle is determined by calculating the spatial position change of the movement point relative to the reference point. The core of this process lies in using 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 being able to convert the raw data into joint rotation angles through the quaternion algorithm. 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 status of joint mobility and generate a comprehensive assessment result in combination with muscle strength and respiratory frequency data. This technical path not only solves the problems of low efficiency and large errors in traditional solutions but also realizes the dynamic adjustment of training intensity through a real-time feedback mechanism, significantly improving 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 the user experience and compliance.

[0053] Specifically, the acquisition module identifies the muscle strength distribution when the user performs the training action, obtains the isomyostatic regions with the same muscle strength, and takes the average muscle strength of each isomyostatic region within the influence range of the corresponding joint as the actuation muscle strength when the user performs the training action.

[0054] Specifically, the acquisition module identifies the user's respiratory frequency through data interaction with the smart bracelet, and the respiratory frequency can also be obtained through the respiratory piezoelectric sensor integrated in the chest strap. The acquisition module identifies the muscle strength distribution when the user performs the training action through the muscle strength sensor. Specifically, the electromyography sensor array is arranged at the attachment points of the target muscle groups, the sampling rate should be ≥1000Hz, and it includes 16-channel differential electrodes;

[0055] On the basis of the above embodiments, the process by which the acquisition module obtains the isomyostatic regions with the same muscle strength includes:

[0056] Performing spatial interpolation on the electromyography sensor data to generate a muscle strength distribution heat map;

[0057] The DBSCAN clustering algorithm is used to identify isometric force regions. Through the force distribution identification and isometric force region extraction technology, the accurate quantification and dynamic assessment of the actuating muscle force are realized, significantly improving the scientificity and adaptability of orthopedic rehabilitation management. Specifically, the acquisition module uses a high-density electromyography sensor array to continuously monitor the force distribution of the user during the execution of training actions, generates a force distribution heat map using a spatial interpolation algorithm, and identifies isometric force regions with similar force levels through cluster analysis. The system further filters out the isometric force regions within the influence range of the corresponding joint and calculates the average value of their muscle forces as the actuating muscle force. The core of this process lies in the synchronous acquisition and fusion processing of multi-channel electromyography signals to eliminate the interference of abnormal local muscle activation (such as tremors or fatigue) on the overall muscle force assessment, ensuring the representativeness and reliability of the data. By comparing the actuating muscle force with the standard muscle force, the system can dynamically identify the recovery status of muscle function and generate a comprehensive assessment result in combination with joint range of motion and respiratory frequency data. This technical path not only solves the problems of single function and fragmented data of traditional muscle force testing equipment but also realizes a comprehensive assessment of the rehabilitation status through multi-dimensional data fusion, significantly improving the adaptability of the training plan. In addition, the visual analysis of the force distribution provides an intuitive reference for therapists, further optimizing the rehabilitation intervention strategy.

[0058] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of devices, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that 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 blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based device for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0059] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention and are not intended to limit the implementation manners of the present invention. For those of ordinary skill 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 implementation manners here. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the claims of the present invention.

Claims

1. An adaptive orthopedic rehabilitation management system, characterized in that, Including: A training module for assisting a user to perform training actions; An acquisition module for respectively acquiring the acting muscle strength, acting range and breathing frequency of the user performing the training actions; An evaluation module configured to generate an evaluation result for the process of the user performing the training actions based on the difference between the acting range and the standard acting range, the difference between the acting muscle strength and the standard muscle strength, and the breathing frequency; An adjustment module configured to correct the training level of the next training action based on the evaluation result, or output a rehabilitation reminder; Wherein, the evaluation module determines whether the acting range is less than the standard acting range; If not, it determines whether the acting muscle strength is less than the standard muscle strength. If so, it outputs the evaluation result to the adjustment module, and the adjustment module outputs an orthopedic rehabilitation reminder. If not, it outputs the evaluation result to the adjustment module, and the adjustment module outputs an overall rehabilitation reminder; The evaluation module determines whether the acting range is less than the standard acting range. If so, it outputs the evaluation result to the adjustment module, and the adjustment module: Quantifies the acting range and the standard acting range based on angles, and determines the angular difference between the standard acting range and the acting range after angle quantification; Generates an orthopedic rehabilitation evaluation parameter based on the angular difference, the acting muscle strength and the breathing frequency; Wherein, the orthopedic rehabilitation evaluation parameter is negatively correlated with the angular difference, negatively correlated with the acting muscle strength, and negatively correlated with the breathing frequency.

2. The adaptive orthopedic rehabilitation management system according to claim 1, wherein The adjustment module corrects the training level of the next training action based on the orthopedic rehabilitation evaluation parameter; Specifically including, if the orthopedic rehabilitation evaluation parameter exceeds the preset range upward, the training level of the next training action is increased; If the orthopedic rehabilitation evaluation parameter exceeds the preset range downward, the training level of the next training action is decreased; If the orthopedic rehabilitation evaluation parameter is 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 acting range based on angles includes: Taking the corresponding joint as the reference point position and the end of the limb far from the corresponding joint as the movement point position, and determining the acting angle of the movement point relative to the reference point position.

4. The adaptive orthopedic rehabilitation management system according to claim 1, wherein The acquisition module identifies the muscle strength distribution when the user performs the training actions, obtains the equal muscle strength regions with the same muscle strength, and takes the average muscle strength of each equal muscle strength region within the influence range of the corresponding joint as the acting muscle strength of the user performing the training actions.

5. The adaptive orthopedic rehabilitation management system according to claim 4, wherein The acquisition module identifies the muscle strength distribution when the user performs the training actions through a muscle strength sensor.

6. The adaptive orthopedic rehabilitation management system according to claim 5, wherein, The process of the acquisition module obtaining the equal muscle strength regions with the same muscle strength includes: Performing spatial interpolation on the electromyography sensor data to generate a muscle strength distribution heat map; Using the DBSCAN clustering algorithm to identify the equal muscle strength regions.

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

8. The adaptive orthopedic rehabilitation management system according to claim 1, wherein The acquisition module identifies the breathing frequency of the user through data interaction with a smart bracelet.

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