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High-precision EMG signal decomposition using communication techniques

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2 Author(s)
R. Gut ; Univ. of Appl. Sci., Muttenz, Switzerland ; G. S. Moschytz

This paper presents a new approach to the decomposition of electromyographic (EMG) signals. EMG signals consist of a superposition of delayed finite-duration waveforms that carry the information about the firing of different muscle fiber groups. The new approach is based on a communication technical interpretation of the EMG signal. The source is modeled as a signaling system with intersymbol-interference, which encodes a well defined sparse information sequence. This point of view allows a maximum-likelihood (ML) as well as a maximum a posteriori (MAP) estimation of the underlying firing pattern to be made. The high accuracy attainable with the proposed method is illustrated both with measured and artificially generated EMG signals

Published in:

IEEE Transactions on Signal Processing  (Volume:48 ,  Issue: 9 )