Robust motion discrimination based on human forearm myoelectric potential by adaptive fuzzy inference considering muscle fatigue.
This paper describes a robust motion discrimination method based on the myoelectric potential of human forearm by the adaptive fuzzy inference considering the muscle fatigue. In the conventional studies, a motion discrimination based on the myoelectric potential of human forearm realizes the high discrimination precision. However, the characteristic of the myoelectric potential gradually changes for muscle fatigue. Therefore the motion discrimination considering muscle fatigue is required. The purpose of this study is to correspond to the change in the myoelectric potential by the muscle fatigue and keep the high discrimination precision. This study proposes the redesign method of the fuzzy inference adapting to the dynamic change of the myoelectric potential by the muscle fatigue. Some experiments on the myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.
Kiso
Atsushi
A
Electrical, Electronics and Computer Engineering, Chiba Institute of Technology, Chiba 275-0016, Japan. s0722015TW@it-chiba.ac.jp
Seki
Hirokazu
H
D000669:Amplifiers, Electronic; D001699:Biometry; D004576:Electromyography / Q000379:methods*; D004867:Equipment Design; D005542:Forearm / Q000502:physiology*; D017143:Fuzzy Logic; D006225:Hand / Q000502:physiology*; D006801:Humans; D015233:Models, Statistical; D009038:Motion; D018763:Muscle Fatigue; D009132:Muscles / Q000502:physiology; D011336:Probability; D013997:Time Factors