Simple SOM Method for Pattern Classification of the EMG Signals

EMG 신호의 패턴 분류를 위한 간단한 SOM 방식

  • Published : 2001.08.31

Abstract

In this paper we propose a method of pattern classification of the hand movement using EMG signals through Self-organizing feature map. Self-organizing feature map is an artificial neural network which organizes its output neuron through learning and therefore it can classify input patterns. The raw EMG signals become direct input to the Self-organizing feature map. The simulation and experiment results showed the effectiveness of the classification of EMG signal using the Self-organizing feature map.

본 논문에서는 근육의 움직임에 의해 유발되는 전기적 선호인 근전도(EMG) 신호를 신경회로망을 통해 분류하여 인체의 움직임을 파악하는 방법을 제안한다. 신호분류를 위한 신경회로망으로 학습에 의해 스스로 출력뉴런을 구성하는 SOM을 사용하였으며, 기존의 방식과 다르게 전처리 과정 없이 신호자세를 SOM의 입력으로 사용하여 패턴을 분류하는 간단한 방식이다. 실험과 시뮬레이션을 통해 제안한 방식의 유용성을 확인하였다.

Keywords

References

  1. 김경성 '의용공학(Medical Engineering)' 청구문화사, 1993
  2. 이규진, 안상면, 권영철, 이명호 '인공팔의 제어를 위한 근전도 신호의 패턴분류' 의공학 회지, vol. 4, no. 1, 1983
  3. George N. Saridis el al 'EMG patternanalysis and classification for a prostheticarm' IEEE Trans on BME vol. 29, no. 6, pp. 403-412, 1982 https://doi.org/10.1109/TBME.1982.324954
  4. Lee. S. H, Saridis G,. N. 'The control of a prosthelic arm by EMG pattern recognition' IEEE Trans on AutomaticControl, vol. 29, no. 4, pp. 290-302. 1984
  5. Tony Khoshaba, Kambiz Badie et al 'EMG pattern classification based on Backpropagation neural network for prosthesiscontrol' IEEE Engineering in MBS. vol. 12, no. 3, 1990
  6. Gottlieb GL, Coreos DM. Agarwal GC. 'Organizing principles for single-joint movements' A speed-insensitive strategy. J Neurophysiol 62: 342-357. 1989
  7. Brown S, Cooke J. 'Movement relatedphasic muscle activation & Changes withtemporal profile of movement.' JNeurophysiol 63: 455-464. 1990
  8. Karst G M, Hasan Z 'Timing andmagnitude of electromyographic activity for two-joint arm movements in differentdirections' J Neurophysiol 66: 1594-1604. 1991
  9. Yasuharu Koike, Mitsuo Kawato 'Estimation of dynamic joint torque and trajectory formation from surface electromyography signals using a neural network model' Biological Cybernetics, Springer-Verlag. 1995 https://doi.org/10.1007/BF00199465
  10. Haganm Demuth Beale, 'Neural Network Design', PWS Publishing Company, 1995
  11. Yong-Zai Lu, 'Industrial Intelligent Control' Fundamentals and Applications, JOHN WILEY & SONS, 1996
  12. B. D. Ripley, 'Pattern Recognition and Neural Networks', CAMBRICGE UNIVERSITY PRESS, 1996
  13. N. K. Bose, P. Liang 'Neural Network Fundamentals With Graphs, Algorithms, and Appliocations', McGraw-Hill, 1996
  14. T. Kohonen, 'The self-organizing map' Proc. IEEE, vol. 78, pp. 1464-1480, 1990 https://doi.org/10.1109/5.58325