A chord-angle-based approach with expandable solution space to 1-degree-of-freedom (DOF) rehabilitation mechanism synthesis

Rehabilitation robots have been proven to be an effective tool for patient motor recovery in clinical medicine. Recently, few degrees of freedom (DOFs), especially 1-DOF, rehabilitation robots have drawn increasing attention as the complexity and cost of the control system would be significantly red...

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Bibliographic Details
Main Authors: Chen, P. (Author), Li, X. (Author), Shu, X. (Author), Wei, W. (Author)
Format: Article
Language:English
Published: Copernicus GmbH 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02743nam a2200397Ia 4500
001 10.5194-ms-13-341-2022
008 220510s2022 CNT 000 0 und d
020 |a 21919151 (ISSN) 
245 1 0 |a A chord-angle-based approach with expandable solution space to 1-degree-of-freedom (DOF) rehabilitation mechanism synthesis 
260 0 |b Copernicus GmbH  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.5194/ms-13-341-2022 
520 3 |a Rehabilitation robots have been proven to be an effective tool for patient motor recovery in clinical medicine. Recently, few degrees of freedom (DOFs), especially 1-DOF, rehabilitation robots have drawn increasing attention as the complexity and cost of the control system would be significantly reduced. In this paper, the mechanism synthesis problem of 1-DOF rehabilitation robots is studied. Traditional synthesis methods usually aim at minimizing the trajectory error to generate a mathematically optimal solution, which may not be a practically feasible solution in terms of engineering constraints. Therefore, we propose a novel mechanism synthesis approach based on chord angle descriptor (CAD) and error tolerance expansion to generate a pool of mechanism solutions from which mathematically and practically optimal solutions can be selected. CAD is utilized for its capability to represent the same-shaped trajectories of different mechanisms in a unified way, and it is robust to the noise in the rehabilitation trajectory acquired by motion capture systems. Then a library of mechanism trajectories is established with compressed representations of CAD via an auto-encoder algorithm to speed up the matching between mechanism and rehabilitation trajectory where the matching error tolerance can be adjusted according to practical rehabilitation specifications. Finally, a design example of a 1-DOF rehabilitation robot for upper-limb training is provided to demonstrate the efficacy of our novel approach. © Copyright: 
650 0 4 |a 1 Degree of freedom 
650 0 4 |a Clinical medicine 
650 0 4 |a Computer aided design 
650 0 4 |a Degrees of freedom (mechanics) 
650 0 4 |a Descriptors 
650 0 4 |a Effective tool 
650 0 4 |a Errors 
650 0 4 |a Errors tolerance 
650 0 4 |a Machine design 
650 0 4 |a Mechanism synthesis 
650 0 4 |a Medicine 
650 0 4 |a Motor recovery 
650 0 4 |a Neuromuscular rehabilitation 
650 0 4 |a Optimal solutions 
650 0 4 |a Optimal systems 
650 0 4 |a Rehabilitation robot 
650 0 4 |a Robots 
650 0 4 |a Solution space 
650 0 4 |a Trajectories 
700 1 |a Chen, P.  |e author 
700 1 |a Li, X.  |e author 
700 1 |a Shu, X.  |e author 
700 1 |a Wei, W.  |e author 
773 |t Mechanical Sciences