Application of the continuous wavelet transform for the analysis of pathological severity degree of electromyograms (EMGs) signals
Published Online: Sep 29, 2020
Page range: 149 - 154
Received: Mar 31, 2020
Accepted: Jun 06, 2020
DOI: https://doi.org/10.2478/pjmpe-2020-0017
Keywords
© 2020 Aicha Mokdad et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The aim of this work was twofold: first, to propose signal processing methods for assessing the temporal and spectral changes of parameters (mean absolute value, the energy and standard deviation as temporal parameters, total and mean power as frequency parameters) of the surface myoelectric signal of the various patient groups like normal, myopathic and neuropathic during muscles contraction of biceps. Secondly, to analyze this electrical manifestation of neuromuscular disorders by the implementation of time-frequency analysis using continuous wavelet that allows us to qualify this method to evaluate, appreciate the pathology and determine its degree of severity which was unable by extracting mentioned parameters. Our results showed that this approach presents satisfactory performances especially to follow patients with the least severe pathology.