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采用非接触式主从控制策略的手指识别外骨骼系统

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

作者信息

Sun Zhenyu, Jing Xiaobei, Zhang Xinyu, Shan Biaofeng, Jiang Yinlai, Li Guanglin, Yokoi Hiroshi, Yong Xu

机构信息

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.

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

出版信息

Bioengineering (Basel). 2024 Jul 25;11(8):754. doi: 10.3390/bioengineering11080754.

DOI:10.3390/bioengineering11080754
PMID:39199712
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11352026/
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.

摘要

本文提出了一种新颖的手指个体化外骨骼系统，该系统采用非接触式主从控制策略，有效地将运动功能和个体适应性结合起来。我们的解决方案包括以下两个交互组件：主侧和从侧。主侧通过Leap Motion控制器在运动过程中处理来自健康手部的关节角度信息作为系统输入，由于采用非接触方式，提供了更灵活和主动的操作。然后，作为从侧，外骨骼根据输入被驱动以辅助用户的手部进行康复训练。外骨骼机构被设计为一个通用模块，可适应各种手指尺寸，重量仅为40克。此外，外骨骼的当前运动实时反馈到系统中，形成闭环以确保控制精度。最后，通过四个实验验证了所提出的外骨骼系统的设计有效性和运动性能。实验结果表明，我们的原型在弯曲时可为整个手部提供约16.5 N的平均力，在抓握任务中的成功率达到82.03%。重要的是，所提出的原型有望改善康复效果，为不同的中风阶段或应用场景提供多种选择。

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