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Application of the continuous wavelet transform for the analysis of pathological severity degree of electromyograms (EMGs) signals Cover

Application of the continuous wavelet transform for the analysis of pathological severity degree of electromyograms (EMGs) signals

Open Access
|Sep 2020

Abstract

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.

DOI: https://doi.org/10.2478/pjmpe-2020-0017 | Journal eISSN: 1898-0309 | Journal ISSN: 1425-4689
Language: English
Page range: 149 - 154
Submitted on: Mar 31, 2020
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Accepted on: Jun 6, 2020
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Published on: Sep 29, 2020
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2020 Aicha Mokdad, Sidi Mohammed El Amine Debbal, Fadia Meziani, published by Polish Society of Medical Physics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.