대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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- Pages.769-771
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- 2000
신경회로망을 이용한 근전도 신호의 특성분석 및 패턴 분류
Pattern Recognition of EMG Signal using Artificial Neural Network
- Yi, Seok-Joo (ISCRC, Korea Institute of Science and Technology) ;
- Lee, Sung-Hwan (Hyundai Heavy Industries) ;
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Cho, Young-Jo
(ISCRC, Korea Institute of Science and Technology)
- 발행 : 2000.11.25
초록
In this paper, pattern recognition scheme for EMG signal using artificial neural network is proposed. For manipulating ability, the movements of human arm are classified into several categories EMG signals of appropriate muscles are collected during arm movement. Patterns of EMG signals of each movement are recognized as follows: 1) The features of each EMG signal are extracted. 2) With these features, the neural network is trained by using feedforward error back-propagation (FFEBP) algorithm. The results show that the arm movements can be classified with EMG signals at high accuracy.
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