ICA for Surface Electromyogram

Ganesh R. Naik, Dinesh K. Kumar, Sridhar P. Arjunan, M. Palaniswami


Surface electromyogram (SEMG) is an indicator of the underlying muscle activity and can be useful for human control interface. One difficulty in the use of SEMG for identifying complex movements is the mixing of muscle activity from other muscles, referred to cross-talk. Similarity in frequency and time domain makes the separation of muscle activity from different muscles extremely difficult. Independent Component Analysis (ICA) is a useful technique for blind source separation. This paper reports investigations to test the effectiveness of using ICA for such applications. It determines the impact of different conditions on the reliability of the separation. The paper reports the evaluation of issues related to the properties of the signals and number of sources. The pa- per also tests Zibulevsky’s method of temporal plotting to identify number of independent sources in SEMG recordings. The results demonstrate that ICA is suitable for SEMG signals when the numbers of sources are not greater than the number of recordings. The inability of the system to identify the correct order and magnitude of the signals is also discussed. It is observed that even when muscle contraction is minimal, and signal is filtered using wavelets and band pass filters, Zibulevsky’s sparse decomposition technique does not identify number of independent sources.


  1. Hideo, Nakamura., Masaki, Yoshida., Manabu, Kotani., Kenzo, Akazawa., Toshio, Moritani. : The application of independent component analysis to the multi-channel surface electromyographic signals for separation of motor unit action potential trains, Vol. 14. Journal of Electromyography and Kinesiology, (2004) 423 - 432
  2. Yong, Hu., Li, X. H., Xie, X. B., Pang, L. Y., Yuzhen, Cao., Luk, K. D. K. : Applying Independent Component Analysis on ECG Cancellation Technique for the Surface Recording of Trunk Electromyography, IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai (2005)
  3. Greco, A., Costantino, D., Morabito, F. C., Versaci, M. A. : A Morlet wavelet classification technique for ICA filtered SEMG experimental data, Vol. 1. Neural Networks Proceedings of the International Joint Conference, (2003) 66 - 71
  4. Zibulevsky, M., Pearlmutter, B. A., Bofill, P., Kisilev, P. : Blind source separation by sparse decomposition in a signal dictionary, In: Roberts, S. J. and Everson, R. M.(eds): Independent Components Analysis: Principles and Practice, Cambridge University Press (2000)
  5. Gupta, V., Reddy, N. P. : Surface electromyogram for the control of anthropomorphic teleoperator fingers, Vol. 29. Student Health Technology Information, (1996) 482 - 487
  6. Moritani, T., Muro, M. : Motor unit activity and EMG power spectrum during increasing force contraction, Vol. 56. Eur. J. Appl. Physio. Occup. (1987) 260 - 265
  7. Hyvarinen, A., Karhunen, J., Oja, E. :Independent Component Analysis, John Wiley, New York (2001)
  8. Mallat, S. :A wavelet tour of signal processing, Cambridge University Press (2000)
  9. Chen, S., Donoho, D.L. :Atomic decomposition by basis pursuit,Vol. 20. C, SIAM J. Sci. Comput. (1999) 33 - 61
  10. Olshausen, B.A., Millman, K.J. :Learning sparse codes with a mixture-of-Gaussians prior,vol. 12. Advances in neural information processing systems, MIT Press (2000) 841 84

Paper Citation

in Harvard Style

R. Naik G., K. Kumar D., P. Arjunan S. and Palaniswami M. (2006). ICA for Surface Electromyogram . In Proceedings of the 2nd International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2006) ISBN 978-972-8865-67-2, pages 51-60. DOI: 10.5220/0001223200510060

in Bibtex Style

author={Ganesh R. Naik and Dinesh K. Kumar and Sridhar P. Arjunan and M. Palaniswami},
title={ICA for Surface Electromyogram},
booktitle={Proceedings of the 2nd International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2006)},

in EndNote Style

JO - Proceedings of the 2nd International Workshop on Biosignal Processing and Classification - Volume 1: BPC, (ICINCO 2006)
TI - ICA for Surface Electromyogram
SN - 978-972-8865-67-2
AU - R. Naik G.
AU - K. Kumar D.
AU - P. Arjunan S.
AU - Palaniswami M.
PY - 2006
SP - 51
EP - 60
DO - 10.5220/0001223200510060