A rehabilitation training method and system based on human factors engineering

Abstract

The present invention discloses a rehabilitation training method and system based on human factors engineering. The setting of mechanical structure and motion parameters is automatically completed through mutual communication between a computer simulation system and an automatically adjustable rehabilitation walker. The present invention takes human factors engineering factors into consideration and can consider different patient conditions. According to the method of first simulating and optimizing the simulation and then conducting rehabilitation training, the rehabilitation walker used for simulation is parameterized, so that it is possible to change and optimize it in a musculoskeletal motion analysis module. The corresponding parts of the real rehabilitation walker are also adjustable and automatically deform and adjust according to the simulation parameters. Simulation optimization has been performed before rehabilitation training, which greatly improves the rehabilitation effect and saves costs. Simulation, optimization and real machine adjustment can be performed automatically, saving worry and effort. The parameterized digital model is easy to use and optimize.

Description

Technical Field

[0001] The present invention relates to the technical field of rehabilitation training, and in particular to a rehabilitation training method and system based on human factors engineering. Background Art

[0002] The patient's rehabilitation mainly depends on medical staff or rehabilitation walkers. Rehabilitation training solely relying on medical staff is time-consuming and labor-intensive, and there is a trend of it being replaced by rehabilitation walkers.

[0003] Existing rehabilitation walkers are optimized and produced only from the perspective of industrial design, and cannot automatically adjust multiple parameters according to the training needs of individual patients. Individual patients vary greatly, and which part of the body is focused on and which part of the patient can be trained by rehabilitation walkers with different parameters directly affects the efficiency and cost of rehabilitation. Therefore, before the real training occurs, there needs to be an optimization simulation process to take into account all factors, including individual differences in patients, differences in the appearance of the rehabilitation walker, differences in motion parameters, and differences in musculoskeletal motor force. According to the results of the simulation, the parameters of the real rehabilitation walker are set, such as the height and width of the handrails, the height of the left and right sides, the turning angle, and the travel speed. Current rehabilitation training lacks consideration of human factors engineering factors, especially the adjustment of personalized equipment based on musculoskeletal motion analysis simulation. Existing rehabilitation training relies on experience and lacks scientific guidance. Moreover, rehabilitation walkers are mass-produced products and cannot be adjusted adaptively, which greatly reduces the efficiency of rehabilitation and increases social costs. Summary of the invention

[0004] In order to solve the problems in the prior art, the present invention proposes a rehabilitation training method and system based on ergonomics. Taking ergonomics factors into consideration, simulation optimization can be performed before rehabilitation training. The rehabilitation walker can be adaptively adjusted according to the optimized simulation results to improve the rehabilitation effect and save costs.

[0005] In order to achieve the above objectives, the present invention provides a rehabilitation training system based on ergonomics, including a computer simulation system and an automatically adjustable rehabilitation walker, the computer simulation system is communicatively connected to the rehabilitation walker, the computer simulation system includes a musculoskeletal motion analysis module and a parameterized three-dimensional digital model of the rehabilitation walker, the three-dimensional digital model of the rehabilitation walker is used to simulate the rehabilitation training parameters of the rehabilitation walker, the musculoskeletal motion analysis module is used to obtain human body model parameters, and load and import the three-dimensional digital model of the rehabilitation walker, analyze the distribution of human muscle force and skeletal force, obtain the training effect of the rehabilitation walker on relevant parts of the human body under the current rehabilitation training parameters, and compare with the threshold value, adjust and optimize the current rehabilitation training parameters of the three-dimensional digital model of the rehabilitation walker, obtain the optimal rehabilitation training parameters corresponding to the optimal training effect, the musculoskeletal motion analysis module sends the optimal rehabilitation training parameters to the rehabilitation walker, and the rehabilitation walker is adaptively adjusted according to the optimal rehabilitation training parameters.

[0006] Furthermore, the computer simulation system is communicatively connected to the rehabilitation walking vehicle via a wireless communication module.

[0007] The present invention also provides a rehabilitation training method based on ergonomics, which adopts the above-mentioned system and includes: establishing a three-dimensional digital model of the rehabilitation walker according to the rehabilitation training parameters of the rehabilitation walker; the musculoskeletal movement analysis module obtains the human body model parameters, and loads and imports the three-dimensional digital model of the rehabilitation walker, analyzes the distribution of muscle force and skeletal force of the human body, obtains the training effect of the rehabilitation walker on relevant parts of the human body under the current rehabilitation training parameters, and compares with the threshold value, adjusts and optimizes the current rehabilitation training parameters of the three-dimensional digital model of the rehabilitation walker, obtains the optimal rehabilitation training parameters corresponding to the optimal training effect, and the musculoskeletal movement analysis module sends the optimal rehabilitation training parameters to the rehabilitation walker, and the rehabilitation walker performs adaptive adjustment according to the optimal rehabilitation training parameters to start rehabilitation training.

[0008] Furthermore, the human body model parameters include height, weight, joint width and bone length.

[0009] Furthermore, the rehabilitation training parameters of the rehabilitation walker include handrail height, handrail width, left and right side heights of the rehabilitation walker, turning angle and travel speed.

[0010] Furthermore, the three-dimensional digital model of the rehabilitation walker includes initial default rehabilitation training parameters. After the musculoskeletal motion analysis module obtains the human body model parameters, it loads and imports the three-dimensional digital model of the rehabilitation walker, analyzes the distribution of human muscle force and skeletal force according to the initial default rehabilitation training parameters, and obtains the training effect of the rehabilitation walker on relevant parts of the human body under the initial default rehabilitation training parameters.

[0011] Furthermore, the initial default rehabilitation training parameters are obtained based on machine learning training.

[0012] Furthermore, the computer simulation system includes a storage module, and the musculoskeletal motion analysis module encodes the optimal rehabilitation training parameters corresponding to the optimal training effect according to different human bodies, and sends the encoding to the storage module for storage.

[0013] Furthermore, the computer simulation system includes a training database, which classifies and stores the optimal rehabilitation training parameters corresponding to different human bodies, obtains the optimal rehabilitation training parameters corresponding to human bodies with different diseases, and classifies and corrects the initial default rehabilitation training parameters.

[0014] Furthermore, the musculoskeletal motion analysis module sends the optimal rehabilitation training parameters to the rehabilitation walker through the wireless communication module.

[0015] Compared with the prior art, the present invention automatically completes the setting of mechanical structure and motion parameters through mutual communication between a computer simulation system and an automatically adjustable rehabilitation walker. The computer simulation system includes a musculoskeletal motion analysis module and a parameterized three-dimensional digital model of the rehabilitation walker. The three-dimensional digital model of the rehabilitation walker is used to simulate the rehabilitation training parameters of the rehabilitation walker. The musculoskeletal motion analysis module is used to obtain human body model parameters, load and import the three-dimensional digital model of the rehabilitation walker, analyze the distribution of muscle force and skeletal force of the human body, obtain the training effect of the rehabilitation walker on relevant parts of the human body under the current rehabilitation training parameters, and compare with the threshold value to adjust and optimize the current rehabilitation training parameters of the three-dimensional digital model of the rehabilitation walker to obtain the optimal rehabilitation training parameters corresponding to the optimal training effect. The musculoskeletal motion analysis module sends the optimal rehabilitation training parameters to the rehabilitation walker, and the rehabilitation walker performs adaptive adjustment according to the optimal rehabilitation training parameters to optimize the actual training effect. The present invention takes into account ergonomic factors and can consider different patient conditions. According to the method of first simulating and optimizing the simulation and then conducting rehabilitation training, the rehabilitation walker used in the simulation is parameterized, making it possible to change and optimize it in the musculoskeletal motion analysis module. The corresponding parts of the real rehabilitation walker are also adjustable and automatically deform and adjust according to the simulation parameters. Simulation optimization has been performed before rehabilitation training, which greatly improves the rehabilitation effect and saves costs. Simulation, optimization and real machine adjustment can proceed automatically, saving worry and effort. The parameterized digital model is easy to use and optimize. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A system block diagram of an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, 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 described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 On the one hand, an embodiment of the present invention provides a rehabilitation training system based on human factors engineering, including a computer simulation system and an automatically adjustable rehabilitation walker, the computer simulation system is communicatively connected to the rehabilitation walker, the computer simulation system includes a musculoskeletal motion analysis module and a parameterized three-dimensional digital model of the rehabilitation walker, the three-dimensional digital model of the rehabilitation walker is used to simulate the rehabilitation training parameters of the rehabilitation walker, the musculoskeletal motion analysis module is used to obtain human body model parameters, and load and import the three-dimensional digital model of the rehabilitation walker, analyze the distribution of muscle force and skeletal force of the human body, obtain the training effect of the rehabilitation walker on relevant parts of the human body under the current rehabilitation training parameters, and compare with the threshold value, adjust and optimize the current rehabilitation training parameters of the three-dimensional digital model of the rehabilitation walker, obtain the optimal rehabilitation training parameters corresponding to the optimal training effect, the musculoskeletal motion analysis module sends the optimal rehabilitation training parameters to the rehabilitation walker, and the rehabilitation walker is adaptively adjusted according to the optimal rehabilitation training parameters.

[0019] Preferably, the computer simulation system is communicatively connected to the rehabilitation walking vehicle via a wireless communication module.

[0020] Preferably, the computer simulation system includes a storage module, and the musculoskeletal movement analysis module can encode the optimal rehabilitation training parameters corresponding to the optimal training effect according to different human bodies and send them to the storage module for storage.

[0021] Further preferably, the computer simulation system includes a training database, which is used to classify and store optimal rehabilitation training parameters corresponding to different human bodies, obtain optimal rehabilitation training parameters corresponding to human bodies with different diseases, and classify and correct initial default rehabilitation training parameters.

[0022] The main function of the musculoskeletal motion analysis module is to analyze the distribution of muscle strength and skeletal force of different human bodies. The human body model parameters including height, weight, joint width and bone length can be changed according to actual conditions. After loading the three-dimensional digital model of the rehabilitation walker, the patient's rehabilitation exercise can be simulated. The musculoskeletal motion analysis module can give the muscle strength of each part and the distribution of force on each bone in real time, so as to obtain the training effect of the rehabilitation walker on the relevant parts of the patient under the current rehabilitation training parameters. The musculoskeletal motion analysis module obtains the optimal training effect by optimizing the three-dimensional digital model of the rehabilitation walker, and sends the optimal rehabilitation training parameters under the optimal effect to the real rehabilitation walker through the wireless communication module. After receiving the optimal rehabilitation training parameters, the rehabilitation walker automatically adjusts its own size, speed and inclination to optimize the real training effect.

[0023] On the other hand, an embodiment of the present invention provides a rehabilitation training method based on ergonomics. The system based on the embodiment of the present invention includes: establishing a three-dimensional digital model of a rehabilitation walker according to the rehabilitation training parameters of the rehabilitation walker; a musculoskeletal motion analysis module obtains human body model parameters, and loads and imports the three-dimensional digital model of the rehabilitation walker, analyzes the distribution of muscle force and skeletal force of the human body, obtains the training effect of the rehabilitation walker on relevant parts of the human body under the current rehabilitation training parameters, and compares with the threshold value, adjusts and optimizes the current rehabilitation training parameters of the three-dimensional digital model of the rehabilitation walker, obtains the optimal rehabilitation training parameters corresponding to the optimal training effect, and the musculoskeletal motion analysis module sends the optimal rehabilitation training parameters to the rehabilitation walker through the wireless communication module, and the rehabilitation walker performs adaptive adjustment according to the optimal rehabilitation training parameters to start rehabilitation training.

[0024] The parameters of the human model include height, weight, joint width and bone length. The rehabilitation training parameters of the rehabilitation walker include handrail height, handrail width, left and right side heights of the rehabilitation walker, turning angle and travel speed.

[0025] The three-dimensional digital model of the rehabilitation walker includes the initial default rehabilitation training parameters. After the musculoskeletal motion analysis module obtains the human body model parameters, it loads and imports the three-dimensional digital model of the rehabilitation walker, analyzes the distribution of muscle force and bone force of the human body according to the initial default rehabilitation training parameters, and obtains the training effect of the rehabilitation walker on relevant parts of the human body under the initial default rehabilitation training parameters. The initial default rehabilitation training parameters are obtained based on machine learning training.

[0026] The musculoskeletal motion analysis module encodes the optimal rehabilitation training parameters corresponding to the optimal training effect according to different human bodies and sends them to the storage module for storage. The training database stores the optimal rehabilitation training parameters corresponding to different human bodies in a classified manner, obtains the optimal rehabilitation training parameters corresponding to human bodies with different diseases, and classifies and amends the initial default rehabilitation training parameters.

[0027] The parameterized digital model of the rehabilitation walker is imported into the musculoskeletal motion analysis module. The adjustable parameters of the rehabilitation walker are: handrail height and width, left and right side height, turning angle and travel speed; then the musculoskeletal motion analysis module loads the standard human body model and modifies the musculoskeletal motion analysis module according to the human body model parameters, and the human body model parameters are height, weight, width of each joint and length of each bone; then the musculoskeletal motion analysis module starts to run with the default rehabilitation training parameters, and continuously optimizes the rehabilitation training parameters of the rehabilitation walker according to the running results. After obtaining the optimal simulation training effect, the musculoskeletal motion analysis module sends the generated optimized rehabilitation training parameters of the rehabilitation walker to the real automatically adjustable rehabilitation walker through the wireless communication module; the rehabilitation walker automatically deforms and starts rehabilitation training with the obtained optimal rehabilitation training parameters.

[0028] The present invention is based on ergonomic factors. Different human body model parameters are generated in a musculoskeletal motion analysis module according to different patient conditions. Then, the rehabilitation movement conditions of the human body are simulated and compared by continuously improving the rehabilitation walker model in the musculoskeletal motion analysis module, and finally the optimal rehabilitation training parameters of the rehabilitation walker are obtained. After the simulation is completed, the musculoskeletal motion analysis module will wirelessly transmit the optimal rehabilitation training parameters to the real rehabilitation walker for training. The rehabilitation walker changes its height, speed and turning angle according to the optimal rehabilitation training parameters, so that the actual rehabilitation effect also complies with the simulated situation, reaches the optimal, improves the rehabilitation effect, and saves costs.

[0029] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A rehabilitation training system based on human factors engineering, characterized in that: It comprises a computer simulation system and an automatically adjustable rehabilitation walker, the computer simulation system is communicatively connected with the rehabilitation walker, the computer simulation system comprises a musculoskeletal motion analysis module and a parameterized three-dimensional digital model of the rehabilitation walker, the three-dimensional digital model of the rehabilitation walker is used to simulate the rehabilitation training parameters of the rehabilitation walker, the musculoskeletal motion analysis module is used to obtain human body model parameters, and load and import the three-dimensional digital model of the rehabilitation walker, analyze the distribution of muscle force and skeletal force of the human body, obtain the training effect of the rehabilitation walker on relevant parts of the human body under the current rehabilitation training parameters, and compare with the threshold value, adjust and optimize the current rehabilitation training parameters of the three-dimensional digital model of the rehabilitation walker, obtain the optimal rehabilitation training parameters corresponding to the optimal training effect, the musculoskeletal motion analysis module sends the optimal rehabilitation training parameters to the rehabilitation walker, and the rehabilitation walker performs adaptive adjustment according to the optimal rehabilitation training parameters; The human body model parameters include height, weight, joint width and bone length; The rehabilitation training parameters of the rehabilitation walker include handrail height, handrail width, left and right side heights of the rehabilitation walker, turning angle and travel speed.

2. The rehabilitation training system based on human factors engineering according to claim 1, characterized in that: The computer simulation system is communicatively connected with the rehabilitation walking vehicle via a wireless communication module.

3. A rehabilitation training method based on human factors engineering, characterized in that: A rehabilitation training system based on ergonomics as described in any one of claims 1 or 2, comprising: establishing a three-dimensional digital model of the rehabilitation walker according to the rehabilitation training parameters of the rehabilitation walker; the musculoskeletal movement analysis module obtains human body model parameters, and loads and imports the three-dimensional digital model of the rehabilitation walker, analyzes the distribution of muscle force and skeletal force of the human body, obtains the training effect of the rehabilitation walker on relevant parts of the human body under the current rehabilitation training parameters, and compares with the threshold value, adjusts and optimizes the current rehabilitation training parameters of the three-dimensional digital model of the rehabilitation walker, obtains the optimal rehabilitation training parameters corresponding to the optimal training effect, and the musculoskeletal movement analysis module sends the optimal rehabilitation training parameters to the rehabilitation walker, and the rehabilitation walker performs adaptive adjustment according to the optimal rehabilitation training parameters to start rehabilitation training; The human body model parameters include height, weight, joint width and bone length; The rehabilitation training parameters of the rehabilitation walker include handrail height, handrail width, left and right side heights of the rehabilitation walker, turning angle and travel speed.

4. The rehabilitation training method based on human factors engineering according to claim 3, characterized in that: The three-dimensional digital model of the rehabilitation walker includes initial default rehabilitation training parameters. After the musculoskeletal motion analysis module obtains the human body model parameters, it loads and imports the three-dimensional digital model of the rehabilitation walker, analyzes the distribution of human muscle force and skeletal force according to the initial default rehabilitation training parameters, and obtains the training effect of the rehabilitation walker on relevant parts of the human body under the initial default rehabilitation training parameters.

5. The rehabilitation training method based on human factors engineering according to claim 4, characterized in that: The initial default rehabilitation training parameters are obtained based on machine learning training.

6. A rehabilitation training method based on human factors engineering according to claim 4, characterized in that: The computer simulation system includes a storage module, and the musculoskeletal motion analysis module encodes the optimal rehabilitation training parameters corresponding to the optimal training effect according to different human bodies, and sends the codes to the storage module for storage.

7. A rehabilitation training method based on human factors engineering according to claim 6, characterized in that: The computer simulation system includes a training database, which stores optimal rehabilitation training parameters corresponding to different human bodies in a classified manner, obtains optimal rehabilitation training parameters corresponding to human bodies with different diseases, and classifies and amends initial default rehabilitation training parameters.

8. The rehabilitation training method based on human factors engineering according to claim 3, characterized in that: The musculoskeletal motion analysis module sends the optimal rehabilitation training parameters to the rehabilitation walking vehicle through the wireless communication module.

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