Mechanical Design and Simulation on Bionic Lower Extremity Rehabilitation Robot

Continuous Passive Motion (CPM) has been confirmed as an effective clinical therapy for finger neurological rehabilitation. In this study a finger rehabilitation training robot is designed based on CPM rehabilitation theory. This paper presents the design and simulation of the finger rehabilitation robot. Based on the finger structure and movement trajectory analysis, OPTOTRAK CERTUS motion capture system is used to acquire trajectory parameters of normal human finger movement. Atlas method is employed to accomplish mechanism dimensional synthesis of the finger rehabilitation training robot. The feasibility of the mechanism is verified using a modeling and simulation method with SIMULINK software.

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Design of the Lower Extremity Rehabilitation Robot Communication System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.330.644 ◽

2013 ◽

Vol 330 ◽

pp. 644-647

Author(s):

Qing Guo ◽

Dan Jiang ◽

Sa Sun

Keyword(s):

Lower Extremity ◽

Communication System ◽

Communication Systems ◽

Data Transfer ◽

Can Bus ◽

Protocol Design ◽

Rehabilitation Robot ◽

Data Transfer Rate ◽

Computing Power ◽

Robot Communication

According to this analysis, we designed a scenario on lower extremity rehabilitation robot communication system based on CAN bus and efficiently solved the problems of low signal processing, computing power and data transfer rate ability for the traditional means of communication of RS232 and RS485.The research deals with the characteristics of communication systems and topological structure, and specifically, with CAN bus protocol design and hardware and software implementation aspects of Communication System designing for some robot sensor.

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An adaptive seamless assist-as-needed control scheme for lower extremity rehabilitation robots

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/0959651820970720 ◽

2020 ◽

pp. 095965182097072

Author(s):

Xiaodong Zhang ◽

Gui Yin ◽

Hanzhe Li ◽

Runlin Dong ◽

Huosheng Hu

Keyword(s):

Lower Extremity ◽

Control Method ◽

Sliding Mode ◽

Rehabilitation Robot ◽

Robotic Assistance ◽

Forgetting Factor ◽

Rehabilitation Robots ◽

Normal Gait ◽

Participation Level ◽

Control Scheme

Most control methods deployed in lower extremity rehabilitation robots cannot automatically adjust to different gait cycle stages and different rehabilitation training modes for different impairment subjects. This article presents a continuous seamless assist-as-needed control method based on sliding mode adaptive control. A forgetting factor is introduced, and a small trajectory deviation from reference normal gait trajectory is used to learn the rehabilitation level of a human subject in real time. The assistance torque needed to complete the reference normal gait trajectory is learned through radial basis function neural networks, so that the rehabilitation robot can adaptively provide the assistance torque according to subject’s needs. The performance and efficiency of this adaptive seamless assist-as-needed control scheme are tested and validated by 12 volunteers on a rehabilitation robot prototype. The results show that the proposed control scheme could adaptively reduce the robotic assistance according to subject’s rehabilitation level, and the robotic assistance torque depends on the forgetting factor and the active participation level of subjects.

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