Electromyogram-based motion compensation control for the upper limb rehabilitation robot in active training

IF 1 4区 工程技术 Q4 ENGINEERING, MECHANICAL Mechanical Sciences Pub Date : 2022-08-03 DOI:10.5194/ms-13-675-2022
Qiaoling Meng, Yiming Yue, Sujiao Li, Hongliu Yu
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引用次数: 1

Abstract

Abstract. Active participation in training is very important for improving the rehabilitation effect for patients with upper limb dysfunction. However, traditional upper limb rehabilitation robots cannot drive the patients' arms by following their varying motion intents during active training. This control strategy can weaken the patients' active participation. This paper proposes a novel center-driven upper limb rehabilitation robot and an electromyogram (EMG)-based motion compensation control method for the upper limb rehabilitation robot in active training in order to improve the patients' active participation. In addition, the trajectory planning equations for the proposed robot manipulator are analyzed and built in order to provide the reference trajectory in active training. In the end, two experiments are carried out to verify the proposed control method. The EMG compensation experiments show that the maximum error between the theoretical and experimental motor rotating speeds is no more than 1.3 %. The active training control experiment results show that the proposed robot can implement the reference trajectory in real time. The control method can implement the positive relationship between the rotating speed and the intensity of EMG emerging during upper limb training. It shows that the proposed rehabilitation robot can provide auxiliary force according to the patients' motion intents. The proposed rehabilitation robot can guide the patients in implementing the reference task in active training.
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基于肌电图的上肢康复机器人主动训练运动补偿控制
摘要积极参与训练对提高上肢功能障碍患者的康复效果非常重要。然而,传统的上肢康复机器人在主动训练过程中无法根据患者的不同运动意图来驱动患者的手臂。这种控制策略会削弱患者的积极参与。本文提出了一种新型的中心驱动上肢康复机器人和基于肌电图的上肢康复机器人主动训练运动补偿控制方法,以提高患者的主动参与能力。此外,分析并建立了该机器人的轨迹规划方程,为主动训练提供了参考轨迹。最后,通过两个实验验证了所提出的控制方法。肌电补偿实验表明,理论转速与实验转速之间的最大误差不超过1.3%。主动训练控制实验结果表明,所提出的机器人能够实时实现参考轨迹。该控制方法可以实现上肢训练中出现的肌电信号强度与转速之间的正相关关系。结果表明,所设计的康复机器人能够根据患者的运动意图提供辅助力。所提出的康复机器人可以指导患者在主动训练中完成参考任务。
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来源期刊
Mechanical Sciences
Mechanical Sciences ENGINEERING, MECHANICAL-
CiteScore
2.20
自引率
7.10%
发文量
74
审稿时长
29 weeks
期刊介绍: The journal Mechanical Sciences (MS) is an international forum for the dissemination of original contributions in the field of theoretical and applied mechanics. Its main ambition is to provide a platform for young researchers to build up a portfolio of high-quality peer-reviewed journal articles. To this end we employ an open-access publication model with moderate page charges, aiming for fast publication and great citation opportunities. A large board of reputable editors makes this possible. The journal will also publish special issues dealing with the current state of the art and future research directions in mechanical sciences. While in-depth research articles are preferred, review articles and short communications will also be considered. We intend and believe to provide a means of publication which complements established journals in the field.
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