High-precision EMG signal decomposition using communication techniques

Author

Gut, Richard ; Moschytz, George S.

Author_Institution

Univ. of Appl. Sci., Muttenz, Switzerland

Volume

48

Issue

9

fYear

2000

fDate

9/1/2000 12:00:00 AM

Firstpage

2487

Lastpage

2494

Abstract

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

Keywords

delays; electromyography; intersymbol interference; maximum likelihood estimation; medical signal processing; MAP estimation; MLE; artificially generated EMG signals; communication techniques; delayed finite-duration waveforms; different muscle fiber groups firing; electromyographic signals; firing pattern; high-precision EMG signal decomposition; intersymbol-interference; maximum a posteriori estimation; maximum-likelihood estimation; measured EMG signals; signaling system; sparse information sequence; Electrodes; Electromyography; Maximum likelihood estimation; Muscles; Needles; Optical fiber communication; Shape; Signal processing; Signal processing algorithms; Signal resolution;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.863051

Filename

863051