Ind. Robot | 2021

Development of a soft cable-driven hand exoskeleton for assisted rehabilitation training

 
 
 

Abstract


Purpose Hand motor dysfunction has seriously reduced people’s quality of life. The purpose of this paper is to solve this problem; different soft exoskeleton robots have been developed because of their good application prospects in assistance. In this paper, a new soft hand exoskeleton is designed to help people conduct rehabilitation training. Design/methodology/approach The proposed soft exoskeleton is an under-actuated cable-driven mechanism, which optimizes the force transmission path and many local structures. Specifically, the path of force transmission is optimized and cables are wound around cam-shaped spools to prevent cables lose during fingers movement. Besides, a pre-tightening system is presented to adjust the preload force of the cable-tube. Moreover, a passive brake mechanism is proposed to prevent the cables from falling off the spools when the remote side is relaxed. Findings Finally, three control strategies are proposed to assist in rehabilitation training. Results show that the average correlation coefficient of trajectory tracking is 90.99% and this exoskeleton could provide steady clamping force up to 35 N, which could meet the demands of activities in daily living. Surface electromyography (sEMG)-based intention recognition method is presented to complete assistance and experiments are conducted to prove the effectiveness of the assisted grasping method by monitoring muscle activation, finger angle and interactive force. Research limitations/implications However, the system should be further optimized in terms of hardware and control to reduce delays. In addition, more clinical trials should be conducted to evaluate the effect of the proposed rehabilitation strategies. Social implications May improve the ability of hemiplegic patients to live independently. Originality/value A novel under-actuated soft hand exoskeleton structure is proposed, and an sEMG-based auxiliary grasping control strategy is presented to help hemiplegic patients conduct rehabilitation training.

Volume 48
Pages 189-198
DOI 10.1108/ir-06-2020-0127
Language English
Journal Ind. Robot

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