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© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

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 Θs and shoulder elbow human–machine closed-chain Θse configuration combinations were synthesized, and the configuration model with compatibility and reduced moment conduction attenuation was selected from them. Two configurations, 2Pa1P3Ra and 5Ra1P, 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 5Ra1P 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.

Details

Title
Configuration Design of an Upper Limb Rehabilitation Robot with a Generalized Shoulder Joint
Author
Yan, Hao 1 ; Wang, Hongbo 2 ; Chen, Peng 1 ; Niu, Jianye 3 ; Yuansheng Ning 1 ; Li, Shuangshuang 4 ; Wang, Xusheng 5 

 Parallel Robot and Mechatronic System Laboratory of Hebei Province, Yanshan University, Qinhuangdao 066000, China; [email protected] (H.Y.); [email protected] (P.C.); [email protected] (J.N.); [email protected] (Y.N.) 
 Parallel Robot and Mechatronic System Laboratory of Hebei Province, Yanshan University, Qinhuangdao 066000, China; [email protected] (H.Y.); [email protected] (P.C.); [email protected] (J.N.); [email protected] (Y.N.); Key Laboratory of Advanced Forging & Stamping Technology and Science of Ministry of Education, Yanshan University, Qinhuangdao 066000, China; [email protected]; Academy for Engineering & Technology, Fudan University, Shanghai 200433, China; [email protected] 
 Parallel Robot and Mechatronic System Laboratory of Hebei Province, Yanshan University, Qinhuangdao 066000, China; [email protected] (H.Y.); [email protected] (P.C.); [email protected] (J.N.); [email protected] (Y.N.); Langfang Ruilida Intelligent Machine Co., Ltd., Langfang 065000, China 
 Key Laboratory of Advanced Forging & Stamping Technology and Science of Ministry of Education, Yanshan University, Qinhuangdao 066000, China; [email protected] 
 Academy for Engineering & Technology, Fudan University, Shanghai 200433, China; [email protected]; Langfang Ruilida Intelligent Machine Co., Ltd., Langfang 065000, China 
First page
2080
Publication year
2021
Publication date
2021
Publisher
MDPI AG
e-ISSN
20763417
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2524471079
Copyright
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.