Digital lower limb function closed chain training system based on suspension and plantar pressure
Through the digital lower limb functional closed-chain training system, personalized training plans are generated using modules such as suspension modules and plantar pressure monitoring, which solves the problems of insufficient training accuracy and real-time evaluation, and achieves precise control and safe lower limb training effects.
Patent Information
- Application Number
- CN202510778519.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-11
- Publication Date
- 2025-09-09
AI Technical Summary
Existing closed-chain training for lower limb function suffers from insufficient training accuracy and lack of real-time evaluation. It is difficult to precisely control the force and movement trajectory of the lower limb joints, and cannot be adjusted according to the patient's real-time physical condition, which may lead to improper training intensity and secondary injuries.
The system uses a suspension module, plantar pressure monitoring module, motion capture module, storage module, training program generation module, simulation module and execution module, combines multi-source data to generate personalized training programs, and uses the load assessment module to evaluate the patient's physical condition in real time to avoid overtraining.
It achieves precise control of the force and movement trajectory of the lower limb joints, generates personalized training plans, improves training effects and safety, and avoids the risks of improper training and overtraining.
Smart Images
Figure CN120605186A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of lower limb training, and in particular to a digital lower limb functional closed-chain training system based on suspension and plantar pressure. Background Art
[0002] Closed-chain lower-limb training refers to a training method in which the distal end of the lower limb (such as the foot) is fixed to the ground or a supporting surface, while the proximal end (such as the thigh and calf) is active. This training method, usually performed in a weight-bearing position, can stimulate receptors in the joints and muscles, inducing the co-activation of agonist and antagonist muscles, thereby promoting dynamic stability of the joints.
[0003] However, the existing closed-chain training of lower limb functions has the following disadvantages:
[0004] 1. Insufficient training accuracy: Traditional closed-chain training makes it difficult to accurately control the force and movement trajectory of the lower limb joints. Due to differences in body shape and muscle strength, different individuals are prone to improper training intensity, which affects the recovery effect and may even cause secondary injuries.
[0005] 2. Lack of real-time assessment: Traditional closed-chain training is difficult to adjust according to the patient's real-time physical condition.
[0006] Therefore, a digital lower limb functional closed-chain training system based on suspension and plantar pressure is invented. Summary of the Invention
[0007] To solve the above technical problems, according to one aspect of the present invention, the present invention provides the following technical solutions:
[0008] A digital lower limb functional closed-chain training system based on suspension and plantar pressure, comprising:
[0009] Suspension module, used to adopt adjustable suspension bracket and equipped with electric lifting device;
[0010] The plantar pressure monitoring module is used to build a pressure acquisition board using a matrix piezoresistive sensor array to collect pressure data from various areas of the plantar in real time;
[0011] The motion capture module deploys inertial sensor nodes at key lower limb joints, including the hip, knee, and ankle, and works with optical motion capture cameras to achieve real-time tracking of three-dimensional motion trajectories.
[0012] The storage module is used to store the patient's basic information, including medical history, rehabilitation stage, and past training records;
[0013] A training program generation module is used to generate a training program based on the data from the plantar pressure monitoring module, the motion capture module and the storage module;
[0014] The simulation module is used to simulate the training process according to the training plan generated by the training plan generation module to predict whether the training plan can achieve the expected results;
[0015] The execution module is used to execute the training plan that meets the expectations and realize the closed chain training of the lower limbs;
[0016] Environmental perception module, used to detect and adjust the patient's training environment;
[0017] The load assessment module is used to assess the patient's body load when performing lower limb closed chain training to avoid overtraining.
[0018] As a preferred solution of the digital lower limb functional closed-chain training system based on suspension and plantar pressure described in the present invention, the training program generation module includes:
[0019] The first acquisition module is used to collect data from the plantar pressure monitoring module and the motion capture module;
[0020] The data evaluation module is used to analyze the data collected by the first acquisition module to evaluate the current status of the patient.
[0021] As a preferred embodiment of the digital lower limb functional closed-chain training system based on suspension and plantar pressure described in the present invention, the training program generation module further includes:
[0022] A second acquisition module is used to collect data stored in the storage module;
[0023] Rehabilitation goal preset module, used to set the patient's rehabilitation goals;
[0024] The analysis module is used to analyze the data from the data evaluation module, the second acquisition module and the rehabilitation goal preset module so as to generate a training plan based on the analyzed data.
[0025] As a preferred embodiment of the digital lower limb functional closed-chain training system based on suspension and plantar pressure described in the present invention, the simulation module includes:
[0026] An acquisition module is used to acquire the training plan generated by the analysis module;
[0027] A scene construction module is used to generate standardized training environments based on VR engines.
[0028] As a preferred embodiment of the digital lower limb functional closed-chain training system based on suspension and plantar pressure of the present invention, the simulation module further comprises:
[0029] A dynamic simulation module is used to drive the virtual human model to perform training in the training environment constructed by the scenario construction module according to the training plan;
[0030] The evaluation module is used to evaluate the training results simulated by the dynamic simulation module to determine whether the simulated training results meet expectations.
[0031] As a preferred embodiment of the digital lower limb functional closed-chain training system based on suspension and plantar pressure of the present invention, the simulation module further comprises:
[0032] The program adjustment module is used to adjust and optimize the training program when the training program does not meet expectations, and upload the adjusted training program to the acquisition module for re-simulation;
[0033] The feedback module is used to feed back the training plan to the execution module when the training plan meets expectations.
[0034] As a preferred solution of the digital lower limb functional closed-chain training system based on suspension and plantar pressure described in the present invention, the environmental perception module includes:
[0035] Temperature sensing module, used to detect the temperature in the training environment;
[0036] Humidity sensor module, used to detect the humidity in the training environment.
[0037] As a preferred solution of the digital lower limb functional closed-chain training system based on suspension and plantar pressure described in the present invention, the environmental perception module further includes:
[0038] Brightness sensor module, used to detect the brightness in the training environment;
[0039] The adjustment module is used to adjust the training environment accordingly according to the data detected by the temperature sensing module, the humidity sensing module and the brightness sensing module.
[0040] As a preferred solution of the digital lower limb functional closed-chain training system based on suspension and plantar pressure described in the present invention, the load assessment module includes:
[0041] The third acquisition module is used to collect the patient's physical condition, including electromyographic signals and heart rate;
[0042] A load analysis module, configured to analyze whether the patient's muscle fatigue and heart rate have reached critical values based on the data collected by the third collection module;
[0043] The adjustment module is used to control the suspension module when the patient's muscle fatigue and heart rate reach critical values, so as to reduce the suspension resistance and avoid injuries caused by overtraining.
[0044] Compared with existing technologies:
[0045] 1. By setting up a plantar pressure monitoring module, a motion capture module, a storage module, a training program generation module, a simulation module, and an execution module, it is not only possible to accurately control the force and motion trajectory of the lower limb joints, but also to combine multi-source data to generate a training program that matches the patient, avoiding improper training problems. In addition, the generated training program can be simulated and verified, thereby ensuring the feasibility of the training program and improving the training effect;
[0046] 2. By setting up a load assessment module, it is possible to perform real-time analysis and assessment of the patient's physical condition during training, so as to avoid overtraining of the patient and improve training safety. BRIEF DESCRIPTION OF THE DRAWINGS
[0047] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION
[0048] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.
[0049] The present invention provides a digital lower limb functional closed-chain training system based on suspension and plantar pressure. Figure 1 ;
[0050] It includes: a suspension module, which uses an adjustable suspension bracket and is equipped with an electric lifting device; a plantar pressure monitoring module, which uses a matrix piezoresistive sensor array to build a pressure acquisition board to collect pressure data from various areas of the plantar foot in real time; a motion capture module, which deploys inertial sensor nodes at key joints of the lower limbs, including the hip joint, knee joint, and ankle joint, and cooperates with an optical motion capture camera to achieve real-time tracking of three-dimensional motion trajectories; a storage module, which is used to store basic information of the patient, including medical history, rehabilitation stage, and past training records; a training program generation module, which is used to generate training programs based on data from the plantar pressure monitoring module, the motion capture module, and the storage module; a simulation module, which is used to simulate the training process based on the training program generated by the training program generation module to predict whether the training program can achieve expectations; an execution module, which is used to execute the training program that meets expectations to achieve closed-chain training of the lower limbs; an environmental perception module, which is used to detect and adjust the patient's training environment; and a load assessment module, which is used to assess the patient's body load when the patient performs closed-chain training of the lower limbs to avoid overtraining.
[0051] The training program generation module includes: a first acquisition module, which is used to collect data from the plantar pressure monitoring module and the motion capture module; a data evaluation module, which is used to analyze the data collected by the first acquisition module to evaluate the patient's current condition; a second acquisition module, which is used to collect data stored in the storage module; a rehabilitation goal preset module, which is used to set the patient's rehabilitation goal; and an analysis module, which is used to analyze the data from the data evaluation module, the second acquisition module and the rehabilitation goal preset module so as to generate a training program based on the analyzed data.
[0052] The simulation module includes: an acquisition module for acquiring the training plan generated by the analysis module; a scene construction module for generating a standardized training environment based on the VR engine; a dynamic simulation module for driving the virtual human model to perform training in the training environment constructed by the scene construction module according to the training plan; an evaluation module for evaluating the training results simulated by the dynamic simulation module to determine whether the simulated training results meet expectations; a plan adjustment module for adjusting and optimizing the training plan when the training plan does not meet expectations, and uploading the adjusted training plan to the acquisition module for re-simulation; and a feedback module for feeding back the training plan to the execution module when the training plan meets expectations.
[0053] The environmental perception module includes: a temperature sensing module for detecting the temperature in the training environment; a humidity sensing module for detecting the humidity in the training environment; a brightness sensing module for detecting the brightness in the training environment; and an adjustment module for adjusting the training environment accordingly based on the data detected by the temperature sensing module, the humidity sensing module, and the brightness sensing module.
[0054] The load assessment module includes: a third acquisition module for collecting the patient's physical condition, including electromyographic signals and heart rate; a load analysis module for analyzing whether the patient's muscle fatigue and heart rate have reached a critical value based on the data collected by the third acquisition module; and an adjustment module for controlling the suspension module when the patient's muscle fatigue and heart rate reach a critical value to reduce the suspension resistance and avoid injuries caused by overtraining.
[0055] During specific use, the operating steps of those skilled in the art are as follows:
[0056] S1: First, the suspension module uses an adjustable suspension bracket equipped with an electric lifting device. Next, the plantar pressure monitoring module uses a matrix piezoresistive sensor array to build a pressure acquisition board to collect real-time pressure data from various areas of the plantar. Finally, the motion capture module deploys inertial sensor nodes at key joints of the lower limbs and, in conjunction with an optical motion capture camera, achieves real-time tracking of three-dimensional motion trajectories.
[0057] S2: The data of the plantar pressure monitoring module and the motion capture module are collected by the first collection module. After the collection, the data collected by the first collection module will be analyzed by the data evaluation module to evaluate the patient's current condition. After the evaluation, the data stored in the storage module will be collected by the second collection module. After the collection, the rehabilitation goal of the patient will be set by the rehabilitation goal preset module. After the setting, the data of the data evaluation module, the second collection module and the rehabilitation goal preset module will be analyzed by the analysis module to generate a training plan based on the analyzed data;
[0058] S3: The training plan generated by the analysis module is acquired through the acquisition module. After acquisition, a standardized training environment is generated according to the VR engine through the scene construction module. After construction, the virtual human body model is driven by the dynamic simulation module to train in the training environment constructed by the scene construction module according to the training plan. After training, the training results simulated by the dynamic simulation module are evaluated by the evaluation module to determine whether the simulated training results meet expectations. If not, the training plan will be adjusted and optimized through the plan adjustment module, and the adjusted training plan can be uploaded to the acquisition module for re-simulation. If it meets expectations, the training plan will be fed back to the execution module through the feedback module, so that the execution module can execute the training plan that meets expectations and realize closed-chain training of the lower limbs.
[0059] S4: During training, the temperature, humidity and brightness of the training environment will be detected through the temperature sensing module, humidity sensing module and brightness sensing module. If the temperature, humidity and brightness do not meet the preset requirements, the training environment will be adjusted accordingly through the adjustment module, including adjusting the temperature, humidity and brightness in the training environment to improve training comfort;
[0060] S5: During training, the patient's physical condition will also be collected through the third acquisition module, including electromyographic signals and heart rate. After collection, the load analysis module will analyze whether the patient's muscle fatigue and heart rate have reached the critical value based on the data collected by the third acquisition module. If so, the suspension module will be controlled through the adjustment module to reduce the suspension resistance and avoid injuries caused by overtraining.
[0061] Although the present invention has been described above with reference to embodiments, various modifications may be made thereto and equivalent components may be substituted without departing from the scope of the present invention. In particular, as long as there are no structural conflicts, the various features of the embodiments disclosed herein may be combined with each other in any manner, and the omission of an exhaustive description of such combinations in this specification is solely for the sake of space and resource conservation. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.
Claims
1. A digital lower limb functional closed-chain training system based on suspension and plantar pressure, characterized in that: include: Suspension module, used to adopt adjustable suspension bracket and equipped with electric lifting device; The plantar pressure monitoring module is used to build a pressure acquisition board using a matrix piezoresistive sensor array to collect pressure data from various areas of the plantar in real time; The motion capture module deploys inertial sensor nodes at key lower limb joints, including the hip, knee, and ankle, and works with optical motion capture cameras to achieve real-time tracking of three-dimensional motion trajectories. The storage module is used to store the patient's basic information, including medical history, rehabilitation stage, and past training records; A training program generation module is used to generate a training program based on the data from the plantar pressure monitoring module, the motion capture module and the storage module; The simulation module is used to simulate the training process according to the training plan generated by the training plan generation module to predict whether the training plan can achieve the expected results; The execution module is used to execute the training plan that meets the expectations and realize the closed chain training of the lower limbs; Environmental perception module, used to detect and adjust the patient's training environment; The load assessment module is used to assess the patient's body load when performing lower limb closed chain training to avoid overtraining.
2. A digital lower limb functional closed-chain training system based on suspension and plantar pressure according to claim 1, characterized in that: The training scheme generation module includes: The first acquisition module is used to collect data from the plantar pressure monitoring module and the motion capture module; The data evaluation module is used to analyze the data collected by the first acquisition module to evaluate the current status of the patient.
3. The digital lower limb functional closed-chain training system based on suspension and plantar pressure according to claim 2, characterized in that: The training scheme generation module also includes: A second acquisition module is used to collect data stored in the storage module; Rehabilitation goal preset module, used to set the patient's rehabilitation goals; The analysis module is used to analyze the data from the data evaluation module, the second acquisition module and the rehabilitation goal preset module so as to generate a training plan based on the analyzed data.
4. A digital lower limb functional closed-chain training system based on suspension and plantar pressure according to claim 3, characterized in that: The simulation module includes: An acquisition module is used to acquire the training plan generated by the analysis module; A scene construction module is used to generate standardized training environments based on VR engines.
5. The digital lower limb functional closed-chain training system based on suspension and plantar pressure according to claim 4, characterized in that: The simulation module further includes: The dynamic simulation module is used to drive the virtual human model to perform training in the training environment constructed by the scenario construction module according to the training plan; The evaluation module is used to evaluate the training results simulated by the dynamic simulation module to determine whether the simulated training results meet expectations.
6. The digital lower limb functional closed-chain training system based on suspension and plantar pressure according to claim 5, characterized in that: The simulation module further includes: The program adjustment module is used to adjust and optimize the training program when the training program does not meet expectations, and upload the adjusted training program to the acquisition module for re-simulation; The feedback module is used to feed back the training plan to the execution module when the training plan meets expectations.
7. The digital lower limb functional closed-chain training system based on suspension and plantar pressure according to claim 1, characterized in that: The environment perception module includes: Temperature sensing module, used to detect the temperature in the training environment; Humidity sensor module, used to detect the humidity in the training environment.
8. The digital lower limb functional closed-chain training system based on suspension and plantar pressure according to claim 7, characterized in that: The environment perception module also includes: Brightness sensor module, used to detect the brightness in the training environment; The adjustment module is used to adjust the training environment accordingly according to the data detected by the temperature sensing module, the humidity sensing module and the brightness sensing module.
9. The digital lower limb functional closed-chain training system based on suspension and plantar pressure according to claim 1, characterized in that: The load assessment module includes: The third acquisition module is used to collect the patient's physical condition, including electromyographic signals and heart rate; A load analysis module, configured to analyze whether the patient's muscle fatigue and heart rate have reached critical values based on the data collected by the third collection module; The adjustment module is used to control the suspension module when the patient's muscle fatigue and heart rate reach critical values, so as to reduce the suspension resistance and avoid injuries caused by overtraining.