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Is the Power Spectrum of Electromyography Signal a Feasible Tool to Estimate Muscle Fiber Composition in Patients with COPD?

A greater proportion of glycolytic muscle fibers is a manifestation of skeletal muscle dysfunction in Chronic Obstructive Pulmonary Disease (COPD). Here, we propose to use the spectral analysis of the electromyographic signal as a non-invasive approach to investigate the fiber muscle composition in...

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Autores principales: Casabona, Antonino, Valle, Maria Stella, Laudani, Luca, Crimi, Claudia, Russo, Cristina, Malaguarnera, Lucia, Crimi, Nunzio, Cioni, Matteo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8432104/
https://www.ncbi.nlm.nih.gov/pubmed/34501263
http://dx.doi.org/10.3390/jcm10173815
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author Casabona, Antonino
Valle, Maria Stella
Laudani, Luca
Crimi, Claudia
Russo, Cristina
Malaguarnera, Lucia
Crimi, Nunzio
Cioni, Matteo
author_facet Casabona, Antonino
Valle, Maria Stella
Laudani, Luca
Crimi, Claudia
Russo, Cristina
Malaguarnera, Lucia
Crimi, Nunzio
Cioni, Matteo
author_sort Casabona, Antonino
collection PubMed
description A greater proportion of glycolytic muscle fibers is a manifestation of skeletal muscle dysfunction in Chronic Obstructive Pulmonary Disease (COPD). Here, we propose to use the spectral analysis of the electromyographic signal as a non-invasive approach to investigate the fiber muscle composition in COPD. We recorded the electromyographic activity of Rectus Femoris (RF), Vastus Lateralis (VL), Vastus Medialis (VM) and Biceps Femoris (BF) muscles, in ten patients and ten healthy individuals, during non-fatiguing, flexion–extension leg movements. The mean (MNF) and median frequencies (MDF) were calculated, and the most common profiles of electromyographic power spectrum were characterized by using the principal component analysis. Frequency parameters showed higher values in patients with COPD than in the control group for the RF (+25% for MNF; +21% for MNF), VL (+16% for MNF; 16% for MNF) and VM (+22% for MNF; 22% for MNF) muscles during the extension movements and for the BF (+26% for MNF; 34% for MNF) muscle during flexion movements. Spectrum profiles of the COPD patients shifted towards the higher frequencies, and the changes in frequency parameters were correlated with the level of disease severity. This shift of frequencies may indicate an increase in glycolytic muscle fibers in patients with COPD. These results, along with the non-fatigable nature of the motor task and the adoption of a non-invasive method, encourage to use electromyographic spectral analysis for estimating muscle fiber composition in patients with COPD.
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spelling pubmed-84321042021-09-11 Is the Power Spectrum of Electromyography Signal a Feasible Tool to Estimate Muscle Fiber Composition in Patients with COPD? Casabona, Antonino Valle, Maria Stella Laudani, Luca Crimi, Claudia Russo, Cristina Malaguarnera, Lucia Crimi, Nunzio Cioni, Matteo J Clin Med Article A greater proportion of glycolytic muscle fibers is a manifestation of skeletal muscle dysfunction in Chronic Obstructive Pulmonary Disease (COPD). Here, we propose to use the spectral analysis of the electromyographic signal as a non-invasive approach to investigate the fiber muscle composition in COPD. We recorded the electromyographic activity of Rectus Femoris (RF), Vastus Lateralis (VL), Vastus Medialis (VM) and Biceps Femoris (BF) muscles, in ten patients and ten healthy individuals, during non-fatiguing, flexion–extension leg movements. The mean (MNF) and median frequencies (MDF) were calculated, and the most common profiles of electromyographic power spectrum were characterized by using the principal component analysis. Frequency parameters showed higher values in patients with COPD than in the control group for the RF (+25% for MNF; +21% for MNF), VL (+16% for MNF; 16% for MNF) and VM (+22% for MNF; 22% for MNF) muscles during the extension movements and for the BF (+26% for MNF; 34% for MNF) muscle during flexion movements. Spectrum profiles of the COPD patients shifted towards the higher frequencies, and the changes in frequency parameters were correlated with the level of disease severity. This shift of frequencies may indicate an increase in glycolytic muscle fibers in patients with COPD. These results, along with the non-fatigable nature of the motor task and the adoption of a non-invasive method, encourage to use electromyographic spectral analysis for estimating muscle fiber composition in patients with COPD. MDPI 2021-08-25 /pmc/articles/PMC8432104/ /pubmed/34501263 http://dx.doi.org/10.3390/jcm10173815 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Casabona, Antonino
Valle, Maria Stella
Laudani, Luca
Crimi, Claudia
Russo, Cristina
Malaguarnera, Lucia
Crimi, Nunzio
Cioni, Matteo
Is the Power Spectrum of Electromyography Signal a Feasible Tool to Estimate Muscle Fiber Composition in Patients with COPD?
title Is the Power Spectrum of Electromyography Signal a Feasible Tool to Estimate Muscle Fiber Composition in Patients with COPD?
title_full Is the Power Spectrum of Electromyography Signal a Feasible Tool to Estimate Muscle Fiber Composition in Patients with COPD?
title_fullStr Is the Power Spectrum of Electromyography Signal a Feasible Tool to Estimate Muscle Fiber Composition in Patients with COPD?
title_full_unstemmed Is the Power Spectrum of Electromyography Signal a Feasible Tool to Estimate Muscle Fiber Composition in Patients with COPD?
title_short Is the Power Spectrum of Electromyography Signal a Feasible Tool to Estimate Muscle Fiber Composition in Patients with COPD?
title_sort is the power spectrum of electromyography signal a feasible tool to estimate muscle fiber composition in patients with copd?
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8432104/
https://www.ncbi.nlm.nih.gov/pubmed/34501263
http://dx.doi.org/10.3390/jcm10173815
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