Design of Mechanical Structure & Control System of a Lower Limb Rehabilitative Robot

2014 ◽  
Vol 716-717 ◽  
pp. 1461-1464
Author(s):  
Xiao Hua Shi ◽  
Yun Shan Lu ◽  
Hao Lu ◽  
Hong Bo Wang
Keyword(s):  
Control System ◽  
Lower Limb ◽  
Rehabilitation Robot ◽  
Passive Mode ◽  
Semg Signal ◽  
Mechanical Structure

The rehabilitation robot which consists of two mechanical legs and an automatic seat was produced according to ergonomics. Each mechanical leg has three DOF. It can train patients combined with sEMG signal and FES. The rehabilitation robot has three train modes: passive mode, assistant mode and impedance mode, and it suits patients with different rehabilitation phases.

Control System of the Lower Limb Rehabilitation Robot

2012 ◽  
pp. 478-488 ◽  
Author(s):  
Andrzej Michnik ◽  
Jacek Brandt ◽  
Zbigniew Szczurek ◽  
Michał Bachorz ◽  
Zbigniew Paszenda ◽  
...  
Keyword(s):  
Control System ◽  
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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