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.

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.

A Study on an Evaluation Method of a Rehabilitation Robot Based on Fuzzy Comprehensive Evaluation

2014 ◽  
Vol 926-930 ◽  
pp. 1144-1147
Author(s):  
Lei Chen ◽  
Chang Niu Yang ◽  
Wen Quan Huang ◽  
Ze Gang Sun ◽  
Yu Cong Liu
Keyword(s):  
Lower Limb ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Actual State ◽  
Rehabilitation Robot ◽  
Rehabilitation Training ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

To solve the rehabilitation evaluation problem of rehabilitation training, a rehabilitation evaluation method based on fuzzy comprehensive evaluation was presented for 6-DOF wearable lower limb rehabilitation robot. Relative degradation degree was introduced to represent the transformation of the actual state of rehabilitation training and the very poor rehabilitation. On the basis, Rehabilitation evaluation model was built based on fuzzy comprehensive evaluation, each layer of which was evaluated respectively, and suggests rehabilitation evaluation results of a lower limb rehabilitation robot. The instance analysis shows that the method is reasonable and effective.

Force Control Based on Model Predictive for Lower Limb Rehabilitation Training

2015 ◽  
Vol 738-739 ◽  
pp. 991-994
Author(s):  
Fu Cheng Cao ◽  
Hong Wu Qin
Keyword(s):  
Force Control ◽  
Lower Limb ◽  
Control Method ◽  
Control Strategies ◽  
Industrial Robot ◽  
Control Law ◽  
Rehabilitation Robot ◽  
Patient Centered ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

Human as a varying dynamic system, the control strategies of human-robot interacts differ significantly from that of conventional industrial robot. Considered the patient-centered exercise regimens, a force control method based predict is presented to control a lower limb rehabilitation robot. The control law is introduced that optimises the the maintained force level and limits excessive forceto injury the subject's lower extremity joints. Simulation results show that the robot could guide thelower limb of subjects to move under predefined model of the external force.

Design and remote collaboration control of asymmetric rigid-flexible hybrid-driven lower limb rehabilitation robot

2021 ◽  
pp. 095440622110203
Author(s):  
Ke-yi Wang ◽  
Yan-lin Wang ◽  
Peng-cheng Yin
Keyword(s):  
Feedback Control ◽  
Lower Limb ◽  
Force Feedback ◽  
Control Method ◽  
Rehabilitation Robot ◽  
Mapping Model ◽  
Feedback Control Method ◽  
Simulation Results ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

A double-end lower limb rehabilitation robot is introduced in the paper, which can realize the rehabilitation training of the abduction and abduction, internal rotation and external rotation of human lower limb. The kinematics and dynamics of the robot are analyzed. Based on the motion trajectory planning of the lower limb rehabilitation robot, the motion state and dynamic state of the cable are analyzed. In order to realize the good remote cooperative control between the rehabilitation physician terminal and the patient rehabilitation terminal, the bilateral PD control method and the patient terminal force feedback control method based on the absolute stability theory are analyzed by using the dual-port network model. The simulation results show that the performance of the patient terminal force feedback control method is excellent when the force on the moving platform and the external interference force are changed suddenly. The mapping model of double-ended mechanism is established in the SimMechanics. The simulation results show that the mapping model of double-ended mechanism has a good position tracking ability and their workspaces can meet the requirements of trajectory mapping. The remote collaborative rehabilitation training experiment was done on the established experimental platform. The experimental result shows that the experiment system has a good tracking performance under the guidance of the patient terminal force feedback control method. The feasibility and operability of the remote rehabilitation cooperation technology are verified.

scholarly journals An Advanced Adaptive Control of Lower Limb Rehabilitation Robot

2018 ◽  
Vol 5 ◽  
Author(s):  
Yihao Du ◽  
Hao Wang ◽  
Shi Qiu ◽  
Wenxuan Yao ◽  
Ping Xie ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Lower Limb ◽  
Rehabilitation Robot ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

scholarly journals A Construction Method of Lower Limb Rehabilitation Robot with Remote Control System

2021 ◽  
Vol 11 (2) ◽  
pp. 867
Author(s):  
Mingda Miao ◽  
Xueshan Gao ◽  
Wei Zhu
Keyword(s):  
Control System ◽  
Remote Control ◽  
Lower Limb ◽  
Human Motion ◽  
Practical Training ◽  
Rehabilitation Robot ◽  
Stroke Patients ◽  
Rehabilitation Training ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

In response to the rehabilitation needs of stroke patients who are unable to benefit from conventional rehabilitation due to the COVID-19 epidemic, this paper designs a robot that combines on-site and telerehabilitation. The objective is to assist the patient in walking. We design the electromechanical system with a gantry mechanism, body-weight support system, information feedback system, and man-machine interactive control system. The proposed rehabilitation robot remote system is based on the client/server (C/S) network framework to realize the remote control of the robot state logic and the transmission of patient training data. Based on the proposed system, doctors can set or adjust the training modes and control the parameters of the robot and guide remote patient rehabilitation training through video communication. The robotic system can further store and manage the rehabilitation data of the patient during training. Experiments show the human-computer interaction system of the lower limb rehabilitation robot has good performance, can accurately recognize the information of human motion posture, and achieve the goal of actively the following motion. Experiments confirm the feasibility of the proposed design, the information management of stroke patients, and the efficiency of rehabilitation training. The proposed system can reduce the workload of the doctors in practical training.

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