Extension and flexion assisting control method and system for knee joint brace

Abstract

The invention discloses an extension and flexion assistance control method and system for a knee joint brace, and the method comprises the steps: collecting knee joint movement track information of a user and electrical activity signals of muscles through a built-in sensing unit, and building an activity feature model of the knee joint of the user in combination with pathological information of the user; matching and calling a preliminary stretching and bending assistance control strategy from a pre-stored strategy information base, and monitoring activity state data of the user in real time; an incremental adjusting method is adopted, according to the deviation between real-time activity state data and behavior mode parameters, stretching and bending assisting power is dynamically adjusted, a stretching and bending assisting power control strategy after adjustment is fed back in real time, and the provided stretching and bending assisting power is made to be synchronous with knee joint activity of the user; by means of the method, the knee joint brace can adjust the assistance parameters of the brace in real time according to changes of the user in different rehabilitation stages, dynamic and personalized stretching and bending assistance is provided in the different rehabilitation stages of the user in the rehabilitation process, and the rehabilitation effect and the use comfort of the user are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to a method and system for controlling the extension and flexion assistance of a knee joint brace. Background Art

[0002] Knee injury and postoperative rehabilitation are common clinical treatment challenges. As an important auxiliary tool in the rehabilitation process, knee braces can significantly improve the patient's quality of life and the speed of motor function recovery while providing stable support and assistance. With the aging of the population and the increase in sports injuries, the demand for knee braces continues to grow, prompting an urgent need for technological innovation and personalized treatment methods.

[0003] Knee braces in the prior art usually use a pre-set control mode, or rely on manual adjustment by the user to achieve control of flexion and extension assistance. These braces are relatively static in design and cannot be dynamically adjusted according to the user's actual activity needs. Users need to manually adjust the brace's assistance parameters frequently to adapt to different movement states, such as squatting, standing up, or going up and down stairs. This method that relies on manual operation by the user has obvious disadvantages, lack of personalized adaptability, complexity and inconvenience in use, and difficulty in responding to real-time changes in user activities, such as unexpected postures or irregular activities, resulting in unstable assistance effects of the brace, and may even increase the user's movement risks, leading to technical problems such as poor user experience.

[0004] In view of this, it is necessary to improve the knee brace control technology in the prior art to solve the technical problem of lack of personalized adaptability. Summary of the invention

[0005] The purpose of the present invention is to provide a method and system for controlling the extension and flexion assistance of a knee brace to solve the above technical problems.

[0006] To achieve this object, the present invention adopts the following technical solutions: A method for controlling the extension and flexion assistance of a knee joint brace, comprising: During the user's adaptive wearing period, the built-in sensor unit of the knee brace collects the user's knee joint motion trajectory information and muscle electrical activity signals; By combining the collected motion trajectory information and the electrical activity signal with the user's pathological information, an activity characteristic model of the user's knee joint is established through an adaptive algorithm; the activity characteristic model reflects the user's behavior pattern parameters; Based on the established knee joint activity characteristic model, a preliminary extension and flexion assistance control strategy is matched and called from the pre-stored strategy information library; When the user is performing knee joint activities, the device executes a preliminary flexion and extension assistance control strategy and monitors the user's activity status data in real time; Adopting an incremental adjustment method, dynamically adjusting the extension and flexion assistance according to the deviation between the real-time activity state data and the behavior pattern parameters, so as to gradually adjust the control parameters of the extension and flexion assistance control strategy; The flexion and extension assistance control strategy is adjusted through real-time feedback, so that the flexion and extension assistance provided is synchronized with the user's knee joint movement.

[0007] Optionally, the collected motion trajectory information and electrical activity signal are combined with the user's pathological information to establish an activity feature model of the user's knee joint through an adaptive algorithm; the activity feature model reflects the user's behavior pattern parameters, specifically including: Preprocessing the collected motion trajectory information and electrical activity signals, wherein the preprocessing includes signal denoising, normalization, and time series analysis; A framework of the user's knee joint activity feature model is established, feature information is extracted from the preprocessed motion trajectory information and electrical activity signal, and combined with the user's pathological information, the focus of data interpretation and feature extraction in the model establishment process is adjusted.

[0008] Optionally, the adjustment of the emphasis of data interpretation and feature extraction in the process of establishing the model further includes: Adaptive algorithms are used to comprehensively analyze the pre-processed motion trajectory information, electrical activity signals, and pathological information to obtain behavioral pattern analysis results; The obtained behavior pattern analysis results and characteristic information are input into the activity characteristic model, and the activity characteristic model is optimized and verified to establish an activity characteristic model of the user's knee joint.

[0009] Optionally, based on the established knee joint activity characteristic model, a preliminary extension and flexion assistance control strategy is matched and called from a pre-stored strategy information library, specifically including: Accessing a pre-stored strategy information library; wherein the strategy information library contains a plurality of different extension and flexion assistance control strategies, each strategy being targeted at a different preset knee joint behavior mode; By establishing the user's knee joint activity characteristic model, the reflected user behavior pattern parameters are identified.

[0010] Optionally, the method further includes identifying the user behavior pattern parameters reflected by the established user knee joint activity characteristic model, and then: Based on the user's behavior pattern parameters, the extension and flexion assistance control strategy that best meets the current user's needs is matched from the strategy information library; The matched extension and flexion assistance control strategy is loaded into the control unit of the knee brace.

[0011] Optionally, the incremental adjustment method is used to dynamically adjust the extension and flexion assistance according to the deviation between the real-time activity state data and the behavior pattern parameters, so as to gradually adjust the control parameters of the extension and flexion assistance control strategy, specifically including: Comparing the collected real-time activity data with the behavior pattern parameters and calculating the deviation between the two; Applying an incremental adjustment method, based on the size and direction of the deviation, calculating the required adjustment amount of the power-assistance parameter, wherein the adjustment amount of the power-assistance parameter includes determining the step size and direction of the adjustment, increasing or decreasing the strength of the power-assistance, and adjusting the duration of the response; The power assist output control parameters of the knee joint brace are gradually adjusted according to the calculated power assist parameter adjustment amount, so as to gradually adjust the control parameters of the extension and flexion power assist control strategy.

[0012] Optionally, the real-time feedback adjusted extension and flexion assistance control strategy synchronizes the provided extension and flexion assistance with the user's knee joint movement, and then further includes: The knee brace is connected to a remote management module, and medical staff remotely access the user's knee brace usage information through the remote management module to adjust the extension and flexion assistance control strategy. At the same time, the remote management module provides a simulated prediction of the adjustment effect to assist medical staff in verifying the effect of the strategy adjustment.

[0013] The present invention also provides a knee brace extension and flexion assist control system, which is controlled by the knee brace extension and flexion assist control method as described above, and the control system comprises: A sensor unit, used to collect the user's knee joint motion trajectory information and muscle electrical activity signals; A data processing module, used for preprocessing and feature extraction of the collected motion trajectory information and electrical activity signals; A storage area, used to store a control strategy library, wherein the control strategy library includes a plurality of different extension and flexion assist control strategies; A power assist adjustment module, used to dynamically adjust the extension and flexion assist according to the deviation between the real-time activity status data and the behavior pattern parameters; A communication unit, used for providing real-time feedback of the adjusted extension and flexion assistance control strategy, so that the provided extension and flexion assistance is synchronized with the user's knee joint movement; The safety monitoring module is used for safety monitoring, alarm and emergency stop of the knee brace.

[0014] Compared with the prior art, the present invention has the following beneficial effects: firstly, the motion trajectory information and muscle electrical activity signal of the user are collected by the sensing unit during the adaptation period, and the knee joint activity characteristic model is established by combining the user's pathological information with the adaptive algorithm. Based on the established model, the most suitable preliminary extension and flexion assistance control strategy is matched and called from the pre-stored strategy information library. While executing the preliminary strategy, the brace monitors the user's activity state data in real time, and uses the incremental adjustment method to dynamically adjust the control parameters of the extension and flexion assistance according to the deviation between the real-time data and the behavior pattern parameters, thereby providing real-time feedback and optimizing the control strategy, so that the actual assistance is synchronized with the user's knee joint activity, ensuring that the brace can provide the best support and assistance in each activity state; through this method, the knee joint brace can adjust the assistance parameters of the brace in real time according to the changes of the user in different rehabilitation stages, and provide dynamic and personalized extension and flexion assistance in different rehabilitation stages during the user's rehabilitation process, which significantly improves the rehabilitation effect and the user's comfort. The use of the adaptive algorithm enables the system to adjust the assistance parameters of the brace in real time according to the changes of the user in different rehabilitation stages to meet the user's changing physiological needs and behavior patterns. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] 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, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0016] The structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with this technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantive technical significance. Any structural modification, change in proportion or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical contents disclosed by the present invention.

[0017] Figure 1 This is one of the flow charts of the flexion and extension assistance control method of the first embodiment; Figure 2 This is the second flow chart of the flexion and extension assistance control method of the first embodiment. DETAILED DESCRIPTION

[0018] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below 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.

[0019] In the description of the present invention, it should be understood that the terms "upper", "lower", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. It should be noted that when a component is considered to be "connected" to another component, it may be directly connected to the other component or there may be a centrally arranged component at the same time.

[0020] The technical solution of the present invention is further described below with reference to the accompanying drawings and through specific implementation methods.

[0021] Embodiment 1: Combination Figure 1 to Figure 2 As shown, an embodiment of the present invention provides a method for controlling the extension and flexion assistance of a knee joint brace, comprising: S1, during the user's adaptive wearing period, the user's knee joint motion trajectory information and muscle electrical activity signals are collected through the built-in sensor unit of the knee brace; the motion trajectory information includes but is not limited to the angle change, speed and acceleration of the knee joint, and the muscle electrical activity signal involves the potential change of the muscle.

[0022] During the user's adaptive wearing period, the sensor unit built into the knee brace collects information about the user's knee joint motion trajectory and muscle electrical activity signals. This step is the basis of the entire control system, ensuring accurate and comprehensive user physiological and motion data, which will be used for subsequent model building and power adjustment, and is the prerequisite for the implementation of personalized control strategies.

[0023] S2, establishing an activity characteristic model of the user's knee joint through an adaptive algorithm by combining the collected motion trajectory information and the electrical activity signal with the user's pathological information; the activity characteristic model reflects the user's behavior pattern parameters.

[0024] S3, based on the established knee joint activity characteristic model, matches and calls a preliminary extension and flexion assistance control strategy from the pre-stored strategy information library; the preliminary extension and flexion assistance control strategy is preset to best meet the individual needs of the user.

[0025] Based on the established knee joint activity characteristic model, the initial extension and flexion assistance control strategy suitable for the user's current state is matched and called from the pre-stored strategy information library. This step ensures that the selected control strategy is most suitable for the user's specific needs through intelligent matching, providing support for effective rehabilitation.

[0026] S4, when the user performs knee joint activities (such as squatting, standing up, going up and down stairs, etc.), executes a preliminary flexion and extension assistance control strategy, and monitors the user's activity status data in real time; the activity status data is the latest motion trajectory data and muscle electrical activity data fed back by the sensor unit.

[0027] When the user is moving the knee joint, the called initial extension and flexion assistance control strategy is executed, and the user's activity status data is monitored in real time. This step is the basis for dynamic adjustment of the assistance. Through real-time monitoring, the execution of the control strategy is closely synchronized with the user's actual activities, improving the timeliness and accuracy of the assistance.

[0028] S5, using an incremental adjustment method, dynamically adjusts the extension and flexion assistance according to the deviation between the real-time activity status data and the behavior pattern parameters, so as to gradually adjust the control parameters of the extension and flexion assistance control strategy. This method allows the system to finely adjust the assistance parameters to gradually improve the control strategy, ensure that the assistance output is highly consistent with the user's needs, and enhance the rehabilitation effect.

[0029] S6, real-time feedback of the adjusted extension and flexion assistance control strategy, so that the extension and flexion assistance provided is synchronized with the user's knee joint movement, and meets their assistance needs in different activity states.

[0030] The working principle of the present invention is as follows: first, the motion trajectory information and muscle electrical activity signals of the user are collected by the sensing unit during the user's adaptation period, and the knee joint activity characteristic model is established by combining the user's pathological information with the adaptive algorithm. Based on the established model, the most suitable preliminary extension and flexion assistance control strategy is matched and called from the pre-stored strategy information library. While executing the preliminary strategy, the brace monitors the user's activity state data in real time, and uses the incremental adjustment method to dynamically adjust the control parameters of the extension and flexion assistance according to the deviation between the real-time data and the behavior pattern parameters, thereby providing real-time feedback and optimizing the control strategy, so that the actual assistance is synchronized with the user's knee joint activity, ensuring that the brace can provide the best support and assistance in each activity state; through this method, the knee joint brace can adjust the assistance parameters of the brace in real time according to the changes of the user in different rehabilitation stages, and provide dynamic and personalized extension and flexion assistance in different rehabilitation stages during the user's rehabilitation process, which significantly improves the rehabilitation effect and the user's comfort. The use of the adaptive algorithm enables the system to adjust the assistance parameters of the brace in real time according to the changes of the user in different rehabilitation stages to meet the user's changing physiological needs and behavior patterns.

[0031] In this embodiment, it is specifically described that step S2 specifically includes: S21, preprocessing the collected motion trajectory information and electrical activity signals, including signal denoising, normalization, and time series analysis; S22, establishing a framework of a user's knee joint activity feature model, extracting feature information from the preprocessed motion trajectory information and electrical activity signal, and combining the user's pathological information to adjust the focus of data interpretation and feature extraction in the model establishment process; S23, using an adaptive algorithm to comprehensively analyze the pre-processed motion trajectory information, electrical activity signals and pathological information to obtain behavior pattern analysis results; S24, inputting the obtained behavior pattern analysis results and characteristic information into the activity characteristic model, optimizing and verifying the activity characteristic model, so as to establish an activity characteristic model of the user's knee joint.

[0032] In this embodiment, it is specifically described that step S3 specifically includes: S31, accessing a pre-stored strategy information library; wherein the strategy information library includes a plurality of different extension and flexion assistance control strategies, each strategy being targeted at a different preset knee joint behavior mode; S32, identifying the reflected user behavior pattern parameters through the established user knee joint activity characteristic model; the behavior pattern parameters include key parameters of the frequency, amplitude, and force requirement of the knee joint activity.

[0033] S33, based on the user's behavior pattern parameters, matching the extension and flexion assistance control strategy that best meets the current user's needs from the strategy information library; the matching process involves matching the user's rehabilitation needs, behavior patterns and control logic in the strategy library.

[0034] S34, loading the matched extension and flexion assistance control strategy into the control unit of the knee joint brace.

[0035] In this embodiment, it is specifically described that step S5 specifically includes: S51, comparing the collected real-time activity data with the behavior pattern parameters, and calculating the deviation between the two; S52, applying an incremental adjustment method, based on the size and direction of the deviation, calculating the required adjustment amount of the power-assisting parameter, wherein the adjustment amount of the power-assisting parameter includes determining the step size and direction of the adjustment, increasing or decreasing the strength of the power-assisting, and adjusting the duration of the response; S53, gradually adjusting the power output control parameters of the knee brace according to the calculated power parameter adjustment amount, so as to gradually adjust the control parameters of the extension and flexion power control strategy; these adjustments are gradual to ensure that the user gradually adapts to the new power settings and avoids discomfort caused by sudden changes.

[0036] In this embodiment, it is further explained that after step S6, the following steps are further included: S7, connecting the knee brace to a remote management module, through which medical staff remotely access the user's knee brace usage information to adjust the extension and flexion assistance control strategy. At the same time, the remote management module provides a simulation prediction of the adjustment effect to assist medical staff in verifying the effect of the strategy adjustment.

[0037] Embodiment 2: The present invention further provides a knee brace extension and flexion assist control system, which is controlled by the knee brace extension and flexion assist control method of embodiment 1, and the control system comprises: A sensor unit, used to collect the user's knee joint motion trajectory information and muscle electrical activity signals; A data processing module, used for preprocessing and feature extraction of the collected motion trajectory information and electrical activity signals; A storage area, used to store a control strategy library, wherein the control strategy library includes a plurality of different extension and flexion assist control strategies; A power assist adjustment module, used to dynamically adjust the extension and flexion assist according to the deviation between the real-time activity status data and the behavior pattern parameters; A communication unit, used for providing real-time feedback of the adjusted extension and flexion assistance control strategy, so that the provided extension and flexion assistance is synchronized with the user's knee joint movement; The safety monitoring module is used for safety monitoring, alarm and emergency stop of the knee brace.

[0038] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the extension and flexion assistance of a knee joint brace, characterized in that: include: During the user's adaptive wearing period, the built-in sensor unit of the knee brace collects the user's knee joint motion trajectory information and muscle electrical activity signals; By combining the collected motion trajectory information and the electrical activity signal with the user's pathological information, an activity characteristic model of the user's knee joint is established through an adaptive algorithm; The activity feature model reflects the user's behavior pattern parameters; Based on the established knee joint activity characteristic model, a preliminary extension and flexion assistance control strategy is matched and called from the pre-stored strategy information library; When the user is performing knee joint activities, the device executes a preliminary flexion and extension assistance control strategy and monitors the user's activity status data in real time; Adopting an incremental adjustment method, dynamically adjusting the extension and flexion assistance according to the deviation between the real-time activity state data and the behavior pattern parameters, so as to gradually adjust the control parameters of the extension and flexion assistance control strategy; The flexion and extension assistance control strategy is adjusted through real-time feedback, so that the flexion and extension assistance provided is synchronized with the user's knee joint movement.

2. The method for controlling the extension and flexion assistance of a knee joint brace according to claim 1, characterized in that: The collected motion trajectory information and electrical activity signals are combined with the user's pathological information to establish an activity characteristic model of the user's knee joint through an adaptive algorithm; The activity feature model reflects the user's behavior pattern parameters, including: Preprocessing the collected motion trajectory information and electrical activity signals, wherein the preprocessing includes signal denoising, normalization, and time series analysis; A framework of the user's knee joint activity feature model is established, feature information is extracted from the preprocessed motion trajectory information and electrical activity signal, and combined with the user's pathological information, the focus of data interpretation and feature extraction in the model establishment process is adjusted.

3. The method for controlling the extension and flexion assistance of a knee joint brace according to claim 2, characterized in that: The focus of data interpretation and feature extraction in the process of adjusting the model establishment further includes: Adaptive algorithms are used to comprehensively analyze the pre-processed motion trajectory information, electrical activity signals, and pathological information to obtain behavioral pattern analysis results; The obtained behavior pattern analysis results and characteristic information are input into the activity characteristic model, and the activity characteristic model is optimized and verified to establish an activity characteristic model of the user's knee joint.

4. The method for controlling the extension and flexion assistance of a knee joint brace according to claim 1, characterized in that: Based on the established knee joint activity characteristic model, a preliminary extension and flexion assistance control strategy is matched and called from the pre-stored strategy information library, including: Accessing a pre-stored strategy information library; wherein the strategy information library contains a plurality of different extension and flexion assistance control strategies, each strategy being targeted at a different preset knee joint behavior mode; By establishing the user's knee joint activity characteristic model, the reflected user behavior pattern parameters are identified.

5. The method for controlling the extension and flexion assistance of a knee joint brace according to claim 4, characterized in that: The user's knee joint activity characteristic model is established to identify the user's behavior pattern parameters reflected, and then further includes: Based on the user's behavior pattern parameters, the extension and flexion assistance control strategy that best meets the current user's needs is matched from the strategy information library; The matched extension and flexion assistance control strategy is loaded into the control unit of the knee brace.

6. The method for controlling the extension and flexion assistance of a knee joint brace according to claim 1, characterized in that: The incremental adjustment method is used to dynamically adjust the extension and flexion assistance according to the deviation between the real-time activity state data and the behavior pattern parameters, so as to gradually adjust the control parameters of the extension and flexion assistance control strategy, specifically including: Comparing the collected real-time activity data with the behavior pattern parameters and calculating the deviation between the two; Applying an incremental adjustment method, based on the size and direction of the deviation, calculating the required adjustment amount of the power-assistance parameter, wherein the adjustment amount of the power-assistance parameter includes determining the step size and direction of the adjustment, increasing or decreasing the strength of the power-assistance, and adjusting the duration of the response; The power assist output control parameters of the knee joint brace are gradually adjusted according to the calculated power assist parameter adjustment amount, so as to gradually adjust the control parameters of the extension and flexion power assist control strategy.

7. The knee brace extension and flexion assistance control method according to claim 1, characterized in that: The real-time feedback-adjusted extension and flexion assistance control strategy synchronizes the provided extension and flexion assistance with the user's knee joint activity, and then further includes: The knee brace is connected to a remote management module, and medical staff remotely access the user's knee brace usage information through the remote management module to adjust the extension and flexion assistance control strategy. At the same time, the remote management module provides a simulated prediction of the adjustment effect to assist medical staff in verifying the effect of the strategy adjustment.

8. A knee joint brace extension and flexion assist control system, characterized in that: The method for controlling the extension and flexion assistance of the knee joint brace according to any one of claims 1 to 7 is adopted, and the control system comprises: A sensor unit, used to collect the user's knee joint motion trajectory information and muscle electrical activity signals; A data processing module, used for preprocessing and feature extraction of the collected motion trajectory information and electrical activity signals; A storage area, used to store a control strategy library, wherein the control strategy library includes a plurality of different extension and flexion assist control strategies; A power assist adjustment module, used to dynamically adjust the extension and flexion assist according to the deviation between the real-time activity status data and the behavior pattern parameters; A communication unit, used for providing real-time feedback of the adjusted extension and flexion assistance control strategy, so that the provided extension and flexion assistance is synchronized with the user's knee joint movement; The safety monitoring module is used for safety monitoring, alarm and emergency stop of the knee brace.

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