Research on the Motion Control Trajectory and Structure Design of a Lower Limb Standing Rehabilitation Training Device

2020 ◽  
Vol 15 (7) ◽  
pp. 810-818
Author(s):  
Yaochen Shi ◽  
Lingyangmeng ◽  
Daimin Chen ◽  
Guoping Chen ◽  
Zhongwei Zhao
Keyword(s):  
Human Body ◽  
Lower Limb ◽  
Control Method ◽  
Movement Control ◽  
Structure Design ◽  
Motor Dysfunction ◽  
Training Device ◽  
Healthy Human ◽  
Rehabilitation Training ◽  
Control Trajectory

Aiming at the problem of standing rehabilitation of lower limb motor dysfunction patient. Firstly, the standing movement process of human body is analyzed. Secondly, the exercise trajectory test and pressure distribution measurement test of healthy human body are studied. Thirdly, the structure of the lower limb standing rehabilitation training device is designed according to the collected joint trajectory. Finally, the movement control trajectory simulation of the lower limb standing rehabilitation training device is carried out according to the collected regional pressure. The simulation results of virtual prototype coincide with the test trajectory, which shows that the structure of the designed lower limb standing rehabilitation training device is reasonable, and the hybrid control method of force and position can realize the standing rehabilitation training for lower limb motor dysfunction patient in the light of the set exercise trajectory.

scholarly journals Comparison of a Novel Muscle Training Device with Conventional Rehabilitation Training in Motor Dysfunction of Lower Limb Patients: A Pilot Study

2020 ◽  
Vol Volume 15 ◽  
pp. 2209-2218
Author(s):  
Xin-ying Cai ◽  
Dong-qi Lin ◽  
Zhi-zhen Xiao ◽  
Dan-dan Zhang ◽  
Ying Lin ◽  
...  
Keyword(s):  
Pilot Study ◽  
Lower Limb ◽  
Motor Dysfunction ◽  
Training Device ◽  
Muscle Training ◽  
Rehabilitation Training

Self-Learning Control of PMA-Actuated Knee-Joint Rehabilitation Training Device Based on Fuzzy Neural Network

2011 ◽  
Vol 467-469 ◽  
pp. 1645-1650
Author(s):  
Xiao Li ◽  
Xia Hong ◽  
Ting Guan
Keyword(s):  
Neural Network ◽  
Knee Joint ◽  
Pid Controller ◽  
Fuzzy Neural Network ◽  
Control Method ◽  
Learning Control ◽  
Training Device ◽  
Rehabilitation Training ◽  
Fuzzy Neural ◽  
Self Learning

To solve the problem of the delay, nonlinearity and time-varying properties of PMA-actuated knee-joint rehabilitation training device, a self-learning control method based on fuzzy neural network is proposed in this paper. A self-learning controller was designed based on the combination of pid controller, feedforward controller, fuzzy neural network controller, and learning mechanism. It was applied to the isokinetic continuous passive motion control of the PMA-actuated knee-joint rehabilitation training device. The experiments proved that the self-learning controller has the properties of high control accuracy and unti-disturbance capability, comparing with pid controller. This control method provides the beneficial reference for improving the control performance of such system.

scholarly journals Robust adaptive PD-like control of lower limb rehabilitation robot based on human movement data

2021 ◽  
Vol 7 ◽  
pp. e394
Author(s):  
Ningning Hu ◽  
Aihui Wang ◽  
Yuanhang Wu
Keyword(s):  
Human Body ◽  
Lower Limb ◽  
Body Movement ◽  
Human Gait ◽  
Similarity Function ◽  
Rehabilitation Robot ◽  
Healthy Human ◽  
Robust Adaptive ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

The combination of biomedical engineering and robotics engineering brings hope of rehabilitation to patients with lower limb movement disorders caused by diseases of the central nervous system. For the comfort during passive training, anti-interference and the convergence speed of tracking the desired trajectory, this paper analyzes human body movement mechanism and proposes a robust adaptive PD-like control of the lower limb exoskeleton robot based on healthy human gait data. In the case of bounded error perturbation, MATLAB simulation verifies that the proposed method can ensure the global stability by introducing an S-curve function to make the design robust adaptive PD-like control. This control strategy allows the lower limb rehabilitation robot to track the human gait trajectory obtained through the motion capture system more quickly, and avoids excessive initial output torque. Finally, the angle similarity function is used to objectively evaluate the human body for wearing the robot comfortably.

Analysis and Design of a Wearable Robot for Lower-Limb Rehabilitation Training

2011 ◽  
Vol 135-136 ◽  
pp. 256-260
Author(s):  
Yan Chu ◽  
Yan Shao ◽  
Liang Chen
Keyword(s):  
Lower Limb ◽  
Movement Control ◽  
Human Movement ◽  
Approximation Formula ◽  
Wearable Robot ◽  
Rehabilitation Training ◽  
Analysis And Design ◽  
Advantages And Disadvantages ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

After studying the advantages and disadvantages of existing wearable lower limb rehabilitation training robot product performance, by establishing human movement control model and the quadratic approximation formula, we designed a kind of control high-precision of lower limb rehabilitation training robots. The robot can simulate the normal actions as sitting, standing and walking for patients to take rehabilitation training. The structure of it is simple and reliable. And it is easily to be manufactured. The robot provides an ideal device for lower limb rehabilitation training

Implicit Generalized Predictive Control of Hip-Joint Rehabilitation Training Device Driven by Pneumatic Muscle Actuator

2011 ◽  
Vol 138-139 ◽  
pp. 273-278 ◽  
Author(s):  
Xiao Li ◽  
Fan He ◽  
Xia Hong ◽  
Ting Guan
Keyword(s):  
Hip Joint ◽  
Control Method ◽  
Continuous Passive Motion ◽  
Model Parameters ◽  
Training Device ◽  
Pneumatic Muscle ◽  
Rehabilitation Training ◽  
Predictive Controller ◽  
Pneumatic Muscle Actuator ◽  
High Control

To solve the problem of the time-delay, nonlinear and time-variable characteristics of hip-joint rehabilitation training device driven by pneumatic muscle actuator, an implicit generalized predictive controller was designed based on parameter model in this paper. It was applied to the isokinetic continuous passive motion control of the hip-joint rehabilitation training device. Experimental results proved that the controller has the property of high control accuracy, anti-disturbance capability and excellent adaptive abilities for the changes of system model parameters, compared with PID controller. This control method provides the beneficial reference for improving the control performance of such system.

A Treadmill Speed Adaptive Control Method for Lower Limb Rehabilitation Robot

2013 ◽  
Vol 655-657 ◽  
pp. 1158-1163
Author(s):  
Jing Wen Wu ◽  
Lin Yong Shen ◽  
Ya Nan Zhang ◽  
Jin Wu Qian
Keyword(s):  
Adaptive Control ◽  
Lower Limb ◽  
Control Method ◽  
Sagittal Plane ◽  
Force Measurement ◽  
Rehabilitation Robot ◽  
Rehabilitation Training ◽  
Treadmill Speed ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

Robot-assisted rehabilitation training on a treadmill is a popular research direction in recent years. And it will replace the artificial rehabilitation training to become a major rehabilitation training method for patients with lower limb action impairments. However, in the existing rehabilitation system, treadmill run in the constant speed. It has to change the speed manually rather than adjust according to the patients’ active consciousness. In the paper, we proposed a treadmill speed adaption control method for Lower Limb Rehabilitation Robot. A pull pressure sensor is used to detect human’s movement trends. The data are calculated through non-linear gain and then sent to the speed controller in the treadmill according to the characteristics that the hip of human body is fixed on the robot in the walking direction of the sagittal plane. Based on this principle, we designed a force measurement structure and verified the control method by experiment. The result shows that the control method can satisfy adaptive control of the treadmill speed.

scholarly journals A Multi-Information Fusion Method for Gait Phase Classification in Lower Limb Rehabilitation Exoskeleton

2021 ◽  
Vol 15 ◽  
Author(s):  
Yuepeng Zhang ◽  
Guangzhong Cao ◽  
Ziqin Ling ◽  
WenZhou Li ◽  
Haoran Cheng ◽  
...  
Keyword(s):  
Information Fusion ◽  
Lower Limb ◽  
Classification Accuracy ◽  
Motor Dysfunction ◽  
Fusion Method ◽  
Rehabilitation Training ◽  
Phase Classification ◽  
Gait Phase ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

Gait phase classification is important for rehabilitation training in patients with lower extremity motor dysfunction. Classification accuracy of the gait phase also directly affects the effect and rehabilitation training cycle. In this article, a multiple information (multi-information) fusion method for gait phase classification in lower limb rehabilitation exoskeleton is proposed to improve the classification accuracy. The advantage of this method is that a multi-information acquisition system is constructed, and a variety of information directly related to gait movement is synchronously collected. Multi-information includes the surface electromyography (sEMG) signals of the human lower limb during the gait movement, the angle information of the knee joints, and the plantar pressure information. The acquired multi-information is processed and input into a modified convolutional neural network (CNN) model to classify the gait phase. The experiment of gait phase classification with multi-information is carried out under different speed conditions, and the experiment is analyzed to obtain higher accuracy. At the same time, the gait phase classification results of multi-information and single information are compared. The experimental results verify the effectiveness of the multi-information fusion method. In addition, the delay time of each sensor and model classification time is measured, which shows that the system has tremendous real-time performance.

Impedance Control Based Sliding Mode for Lower Limb Rehabilitation Robot

2014 ◽  
Vol 672-674 ◽  
pp. 1770-1773 ◽  
Author(s):  
Fu Cheng Cao ◽  
Li Min Du
Keyword(s):  
Dynamic Response ◽  
Sliding Mode Control ◽  
Lower Limb ◽  
Control Method ◽  
Sliding Mode ◽  
Impedance Control ◽  
Rehabilitation Robot ◽  
Active Rehabilitation ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

Aimed at improving the dynamic response of the lower limb for patients, an impedance control method based on sliding mode was presented to implement an active rehabilitation. Impedance control can achieve a target-reaching training without the help of a therapist and sliding mode control has a robustness to system uncertainty and vary limb strength. Simulations demonstrate the efficacy of the proposed method for lower limb rehabilitation.

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