Browse > Article

A Study on the Low Force Estimation of Skeletal Muscle by using ICA and Neuro-transmission Model  

Yoo, Sae-Keun (와이더댄(주) 구축팀)
Youm, Doo-Ho (서울시립대 전자전기컴퓨터공학부)
Lee, Ho-Yong (서울시립대 전자전기컴퓨터공학부)
Kim, Sung-Hwan (서울시립대 전자전기컴퓨터공학부)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.56, no.3, 2007 , pp. 632-640 More about this Journal
Abstract
The low force estimation method of skeletal muscle was proposed by using ICA(independent component analysis) and neuro-transmission model. An EMG decomposition is the procedure by which the signal is classified into its constituent MUAP(motor unit action potential). The force index of electromyography was due to the generation of MUAP. To estimate low force, current analysis technique, such as RMS(root mean square) and MAV(mean absolute value), have not been shown to provide direct measures of the number and timing of motoneurons firing or their firing frequencies, but are used due to lack of other options. In this paper, the method based on ICA and chemical signal transmission mechanism from neuron to muscle was proposed. The force generation model consists of two linear, first-order low pass filters separated by a static non-linearity. The model takes a modulated IPI(inter pulse interval) as input and produces isometric force as output. Both the step and random train were applied to the neuro-transmission model. As a results, the ICA has shown remarkable enhancement by finding a hidden MAUP from the original superimposed EMG signal and estimating accurate IPI. And the proposed estimation technique shows good agreements with the low force measured comparing with RMS and MAV method to the input patterns.
Keywords
EMG; Low Force; ICA; Neuro-Transmission Model; IPI;
Citations & Related Records

Times Cited By SCOPUS : 0
연도 인용수 순위
  • Reference
1 E.A Clancy and N. Hogan, 'Theoretic and experimental comparison of root-mean-square and mean-absolute-value electromyogram amplitude detectors,' in proc. of 19th int conf. of IEEE in Medicine and Biology Society, pp.1267-1270, Oct., 1997
2 J. Bobet and R. B. Stein, 'A Simple Model of Force Generation by Skeletal Muscle During Dynamic Isometric Contraction'. IEEE Trans. on Biomedical Eng., Vol. 45, No.8, pp. 1010-1016, August 1998   DOI   ScienceOn
3 A. Hyvarine, J. Karhunen and E. Oja, Independent Component Analysis, Wiley Interscience 2001
4 E. Shwedyk, R. Balasubramanian and R.N. Scott, 'A nonstationary model for the electromyogram,' IEEE Trans. on Biomed. Eng., vol. 24, no. 5, pp. 417-424, Aug. 1977   DOI   ScienceOn
5 A. Cichocki and S.I. Amari., Adaptive Blind Signal and Image Processing, Wiley, 2002
6 P.A.M. Griep, K.L. Boon and D.F. Stegeman, 'A study of the motor unit action potential by means of computer simulation,' Bio. Cybernetics, vol. 30, pp. 221-230, 1978   DOI
7 E.A. Clancy, S. Bouchard and D. Rancourt, 'Estimation and application of EMG amplitude during dynamic contractions,' IEEE Eng. in Medicine and Biology, pp. 47-54, Nov./lDec., 2001
8 J.V. Basmajian and C.J. DE Luca, Muscle alive, London: Williams & Wilkins, 1985
9 P. Zhou, W. Z. Rymer, N. Suresh and L. Zhang, 'A Study of suface motor unit action potential in first dorsal interosseous (fdi) muscle,' 23rd Annual EMBS International Conf., pp. 1074-1077, 2001
10 D. L. Donoho, 'Denoising by Soft Thresholding,' IEEE Tans. on Info. Theory vol. 41, pp. 613-627, 1995   DOI   ScienceOn
11 A. Hyvarine, J. Karhunen and E. Oja, Independent Component Analysis, Wiley Interscience 2001