Finger-Individuating Exoskeleton System with Non-Contact Leader–Follower Control Strategy

Author:

Sun Zhenyu12ORCID,Jing Xiaobei1,Zhang Xinyu13,Shan Biaofeng4,Jiang Yinlai2ORCID,Li Guanglin15,Yokoi Hiroshi23ORCID,Yong Xu1

Affiliation:

1. CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institute of Advanced Technology (SIAT), Chinese Academy of Sciences (CAS), and the SIAT Branch, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen 518055, China

2. Department of Mechanical Engineering and Intelligent Systems, The University of Electro-Communications (UEC), Tokyo 182-8585, Japan

3. Joint Doctoral Program for Sustainability Research, The University of Electro-Communications (UEC), Tokyo 182-8585, Japan

4. Second People’s Hospital of Lanzhou City, and the First School of Clinical Medicine, Lanzhou University, Lanzhou 730000, China

5. Shandong Zhongke Advanced Technology Co., Ltd., Jinan 250000, China

Abstract

This paper proposes a novel finger-individuating exoskeleton system with a non-contact leader–follower control strategy that effectively combines motion functionality and individual adaptability. Our solution comprises the following two interactive components: the leader side and the follower side. The leader side processes joint angle information from the healthy hand during motion via a Leap Motion Controller as the system input, providing more flexible and active operations owing to the non-contact manner. Then, as the follower side, the exoskeleton is driven to assist the user’s hand for rehabilitation training according to the input. The exoskeleton mechanism is designed as a universal module that can adapt to various digit sizes and weighs only 40 g. Additionally, the current motion of the exoskeleton is fed back to the system in real time, forming a closed loop to ensure control accuracy. Finally, four experiments validate the design effectiveness and motion performance of the proposed exoskeleton system. The experimental results indicate that our prototype can provide an average force of about 16.5 N for the whole hand during flexing, and the success rate reaches 82.03% in grasping tasks. Importantly, the proposed prototype holds promise for improving rehabilitation outcomes, offering diverse options for different stroke stages or application scenarios.

Funder

National Key R&D Program of China

Shenzhen Science and Technology Program

Science and Technology Program of Guangdong Province

Taishan Industrial Experts Program

Japan Society for the Promotion of Science (JSPS) KAKENHI

Publisher

MDPI AG

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5. GBD 2019 Stroke Collaborators (2021). Global, regional, and national burden of stroke and its risk factors, 1990–2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet Neurol., 20, 795–820.

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