An Effective Training Strategy for Upper-limb Rehabilitation Robots Based on Visual-haptic Feedback Using Potential Field

IF 1.5 Q3 AUTOMATION & CONTROL SYSTEMS IET Cybersystems and Robotics Pub Date : 2022-07-27 DOI:10.1109/CYBER55403.2022.9907062
Guang Feng, Jiaji Zhang, G. Chai, Maoqin Li, Guokun Zuo, Lei Yang
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Abstract

Visual and haptic feedback are crucial to enhance the effectiveness of robot-assisted rehabilitation. To improve the performance of clinical rehabilitation training for patients with motor dysfunction, we propose an effective training strategy based on visual and haptic feedback. Haptic feedback is generated by a designed artificial potential field, which allows patients to perceive the correct training direction. The effectiveness of the proposed training strategy is initially verified, by recruiting three healthy subjects to perform circle drawing tasks on an upper limb rehabilitation robot. Experimental results showed that higher training accuracies were obtained using visual-haptic feedback compared to those with unimodal feedback. The proposed strategy can enhance the users' perception of the training process and corrects the incorrect movements in real-time, simultaneously. The current training strategy can be applied to commercial rehabilitation robots and meet the rehabilitation training needs of the users with impaired vision or the vision is unavailable.
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基于势场视觉-触觉反馈的上肢康复机器人有效训练策略
视觉和触觉反馈是提高机器人辅助康复效果的关键。为了提高运动功能障碍患者的临床康复训练效果,我们提出了一种基于视觉和触觉反馈的有效训练策略。触觉反馈由设计的人工电位场产生,使患者感知到正确的训练方向。通过招募三名健康受试者在上肢康复机器人上完成画圆任务,初步验证了所提训练策略的有效性。实验结果表明,视觉-触觉反馈比单模态反馈具有更高的训练精度。所提出的策略可以增强用户对训练过程的感知,同时实时纠正不正确的动作。目前的训练策略可以应用于商用康复机器人,满足视力受损或视力缺失用户的康复训练需求。
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来源期刊
IET Cybersystems and Robotics
IET Cybersystems and Robotics Computer Science-Information Systems
CiteScore
3.70
自引率
0.00%
发文量
31
审稿时长
34 weeks
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