Cybernic robot hand-arm that realizes cooperative work as a new hand-arm for people with a single upper-limb dysfunction.

IF 2.9 Q2 ROBOTICS
Frontiers in Robotics and AI Pub Date : 2024-10-22 eCollection Date: 2024-01-01 DOI:10.3389/frobt.2024.1455582
Hiroaki Toyama, Hiroaki Kawamoto, Yoshiyuki Sankai
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引用次数: 0

Abstract

A robot hand-arm that can perform various tasks with the unaffected arm could ease the daily lives of patients with a single upper-limb dysfunction. A smooth interaction between robot and patient is desirable since their other arm functions normally. If the robot can move in response to the user's intentions and cooperate with the unaffected arm, even without detailed operation, it can effectively assist with daily tasks. This study aims to propose and develop a cybernic robot hand-arm with the following features: 1) input of user intention via bioelectrical signals from the paralyzed arm, the unaffected arm's motion, and voice; 2) autonomous control of support movements; 3) a control system that integrates voluntary and autonomous control by combining 1) and 2) to thus allow smooth work support in cooperation with the unaffected arm, reflecting intention as a part of the body; and 4) a learning function to provide work support across various tasks in daily use. We confirmed the feasibility and usefulness of the proposed system through a pilot study involving three patients. The system learned to support new tasks by working with the user through an operating function that does not require the involvement of the unaffected arm. The system divides the support actions into movement phases and learns the phase-shift conditions from the sensor information about the user's intention. After learning, the system autonomously performs learned support actions through voluntary phase shifts based on input about the user's intention via bioelectrical signals, the unaffected arm's motion, and by voice, enabling smooth collaborative movement with the unaffected arm. Experiments with patients demonstrated that the system could learn and provide smooth work support in cooperation with the unaffected arm to successfully complete tasks they find difficult. Additionally, the questionnaire subjectively confirmed that cooperative work according to the user's intention was achieved and that work time was within a feasible range for daily life. Furthermore, it was observed that participants who used bioelectrical signals from their paralyzed arm perceived the system as part of their body. We thus confirmed the feasibility and usefulness of various cooperative task supports using the proposed method.

实现协同工作的网络机器人手臂,作为单上肢功能障碍患者的新型手臂。
机器人手臂可以用未受影响的手臂执行各种任务,这可以缓解单上肢功能障碍患者的日常生活。由于患者的另一只手臂功能正常,因此机器人和患者之间最好能实现流畅的互动。如果机器人能根据用户的意图移动,并与未受影响的手臂合作,即使没有详细的操作,也能有效地协助完成日常任务。本研究旨在提出并开发一种具有以下特点的控制论机器人手臂:1) 通过来自瘫痪手臂的生物电信号、未受影响手臂的动作和声音输入用户意图;2) 自主控制支撑动作;3) 通过将 1) 和 2) 结合在一起,建立一个将自主控制和自愿控制融为一体的控制系统,从而能够与未受影响手臂合作提供流畅的工作支持,将意图反映为身体的一部分;以及 4) 具有学习功能,能够在日常使用中的各种任务中提供工作支持。我们通过一项涉及三名患者的试点研究,证实了拟议系统的可行性和实用性。该系统通过一种不需要未受影响手臂参与的操作功能与用户合作,学会支持新任务。该系统将支持动作划分为不同的运动阶段,并从有关用户意图的传感器信息中学习阶段转换条件。学习完成后,系统会根据用户通过生物电信号、未受影响手臂的运动和语音输入的意图,通过自愿相位转换自主执行学习到的支持动作,从而实现与未受影响手臂的流畅协作运动。对患者进行的实验表明,该系统可以学习并与非受影响手臂合作提供流畅的工作支持,从而成功完成他们认为困难的任务。此外,问卷调查还从主观上证实,系统能够按照用户的意图协同工作,并且工作时间在日常生活的可行范围内。此外,我们还观察到,使用瘫痪手臂发出的生物电信号的参与者将该系统视为自己身体的一部分。因此,我们证实了使用所提出的方法进行各种合作任务支持的可行性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.50
自引率
5.90%
发文量
355
审稿时长
14 weeks
期刊介绍: Frontiers in Robotics and AI publishes rigorously peer-reviewed research covering all theory and applications of robotics, technology, and artificial intelligence, from biomedical to space robotics.
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