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JRM Vol.33 No.4 pp. 851-857
doi: 10.20965/jrm.2021.p0851
(2021)

Paper:

Facilitative Exercise for Surface Myoelectric Activity Using Robot Arm Control System – Training Scheme with Gradually Increasing Difficulty Level –

Ryota Hayashi*, Naoki Shimoda**, Tetsuya Kinugasa*, and Koji Yoshida*

*Department of Mechanical Systems Engineering, Okayama University of Science
1-1 Ridai-cho, Kita-ku, Okayama 700-0005, Japan

**Graduate School of Engineering, Okayama University of Science
1-1 Ridai-cho, Kita-ku, Okayama 700-0005, Japan

Received:
January 20, 2021
Accepted:
May 18, 2021
Published:
August 20, 2021
Keywords:
myoelectric signal, facilitative exercise, rehabilitation, robot arm, manipulation
Abstract
Facilitative Exercise for Surface Myoelectric Activity Using Robot Arm Control System – Training Scheme with Gradually Increasing Difficulty Level –

Configuration of training system

Various control systems for robot arms using surface myoelectric signals have been developed. Abundant pattern-recognition techniques have been proposed to predict human motion intent based on these signals. However, it is laborious for users to train the voluntary control of myoelectric signals using those systems. In this research, we aim to develop a rehabilitation support system for hemiplegic upper limbs with a robot arm controlled by surface myoelectric signals. In this study, we construct a simple one-link robot arm that is controlled by estimating the wrist motion from the surface myoelectric signals on the forearm. We propose a training scheme with gradually increasing difficulty level for robot arm manipulation to evoke surface myoelectric signals. Subsequently, we investigate the possibility of facilitative exercise for the voluntary surface myoelectric activity of the desired muscles through trial experiments.

Cite this article as:
Ryota Hayashi, Naoki Shimoda, Tetsuya Kinugasa, and Koji Yoshida, “Facilitative Exercise for Surface Myoelectric Activity Using Robot Arm Control System – Training Scheme with Gradually Increasing Difficulty Level –,” J. Robot. Mechatron., Vol.33, No.4, pp. 851-857, 2021.
Data files:
References
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Last updated on Oct. 22, 2021