Contributions and scope of processing techniques, classification and decomposition of electromyographic signals

Abstract:

Electromyographic (EMGs) signals can be used in several clinical and biomedical applications, such as instruments development and EMG acquisition systems with modern man-machine interfaces. For new EMGs signals interpretations and application developments, data acquisition systems required advanced and precise signal processing, decomposition and classification methods that allow improvement of the understanding and knowledge of the EMGs signal behaviour. Generally signal analysis are carried out by Fourier, Gabor and Wavelet analysis, beside artificial intelligence techniques. The purpose of this article is to show how traditional techniques have been used in the processing, decomposition and classification of the EMGs signals, along with some results obtained by using wavelet analysis to study their dynamical behaviour (multi-resolution analysis). This results as a contribution can be applied to different types biomedical signals. © Springer-Verlag Berlin Heidelberg 2007.

Año de publicación:

2008

Keywords:

Fuente:

scopus