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Configuration Design of an Upper Limb Rehabilitation Robot with a Generalized Shoulder Joint.

Authors :
Yan, Hao
Wang, Hongbo
Chen, Peng
Niu, Jianye
Ning, Yuansheng
Li, Shuangshuang
Wang, Xusheng
Faglia, Rodolfo
Source :
Applied Sciences (2076-3417); Mar2021, Vol. 11 Issue 5, p2080, 20p
Publication Year :
2021

Abstract

For stroke patients with upper limb motor dysfunction, rehabilitation training with the help of rehabilitation robots is a social development trend. Existing upper limb rehabilitation robots have difficulty fully fitting the complex motion of the human shoulder joint and have poor human–robot compatibility. In this paper, based on the anatomical structure of the human upper limb, an equivalent mechanism model of the human upper limb is established. The configuration synthesis of the upper limb rehabilitation mechanism was carried out, a variety of shoulder joint man–machine closed-chain Θ<subscript>s</subscript> and shoulder elbow human–machine closed-chain Θ<subscript>se</subscript> configuration combinations were synthesized, and the configuration model with compatibility and reduced moment conduction attenuation was selected from them. Two configurations, 2P<subscript>a</subscript>1P3R<subscript>a</subscript> and 5R<subscript>a</subscript>1P, are proposed for the generalized shoulder joint mechanism of the robot. The closed-chain kinematic models of the two configurations are established, and the velocity Jacobian matrix is obtained. Motion performance analysis, condition reciprocal analysis and operability ellipsoid analysis of different configuration design schemes were carried out in different operation planes. The results show that in the normal upper limb posture of the human body, the 5R<subscript>a</subscript>1P configuration of the shoulder joint has better kinematic performance. Finally, on this basis, an upper limb rehabilitation robot prototype with good human–computer compatibility is developed, and its moving space was verified. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
11
Issue :
5
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
149728186
Full Text :
https://doi.org/10.3390/app11052080