Structure design and kinematics analysis of lower limb rehabilitation training robot
Authors: 
Ao Hu, Qiang Yin, Qian Li, Hongjun Yang, Yonglin ZhangAuthors Info & Claims
Ao Hu, Qiang Yin, Qian Li, Hongjun Yang, Yonglin ZhangAuthors Info & ClaimsPages 410 - 415
Abstract
In this article, a new type of lower limb rehabilitation training robot is designed and related rehabilitation training programs are proposed. The robot system uses a bionic lower limb movement mechanism to drive the hip and ankle joints of the human body, and is combined with a treadmill-type vertical vibration training device to simulate human walking for lower limb rehabilitation training. The overall structure is modeled in three dimensions. In addition, the simplified link mechanism model is used to analyze the robot's motion process by analytical methods, and the motion equations and motion parameters of each component are derived. Meanwhile, simulation software was used to simulate the motion speed of the thigh link and the calf link in the bionic lower limb motion mechanism, and the motion angle range of the hip and knee joints was also simulated. According to the simulation results, the rehabilitation training program is verified and revised to further optimize the design. It lays a theoretical foundation for the movement of the lower limb rehabilitation training robot in the future, and has certain research significance.
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- Structure design and kinematics analysis of lower limb rehabilitation training robot
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Published In
December 2020
718 pages
ISBN:9781450389099
DOI:10.1145/3453187
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- Guilin: Guilin University of Technology, Guilin, China
- International Engineering and Technology Institute, Hong Kong: International Engineering and Technology Institute, Hong Kong
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Association for Computing Machinery
New York, NY, United States
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Published: 24 March 2021
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EBIMCS 2020
EBIMCS 2020: 2020 3rd International Conference on E-Business, Information Management and Computer Science
December 5 - 6, 2020
Wuhan, China
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EBIMCS '20 Paper Acceptance Rate 112 of 566 submissions, 20%;
Overall Acceptance Rate 143 of 708 submissions, 20%
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