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Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength

The need for developing a simple and effective assessment tool for muscle mass has been increasing in a rapidly aging society. This study aimed to evaluate the feasibility of the surface electromyography (sEMG) parameters for estimating muscle mass. Overall, 212 healthy volunteers participated in th...

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Autores principales: Sung, Joo Hye, Baek, Seol-Hee, Park, Jin-Woo, Rho, Jeong Hwa, Kim, Byung-Jo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10302141/
https://www.ncbi.nlm.nih.gov/pubmed/37420659
http://dx.doi.org/10.3390/s23125490
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author Sung, Joo Hye
Baek, Seol-Hee
Park, Jin-Woo
Rho, Jeong Hwa
Kim, Byung-Jo
author_facet Sung, Joo Hye
Baek, Seol-Hee
Park, Jin-Woo
Rho, Jeong Hwa
Kim, Byung-Jo
author_sort Sung, Joo Hye
collection PubMed
description The need for developing a simple and effective assessment tool for muscle mass has been increasing in a rapidly aging society. This study aimed to evaluate the feasibility of the surface electromyography (sEMG) parameters for estimating muscle mass. Overall, 212 healthy volunteers participated in this study. Maximal voluntary contraction (MVC) strength and root mean square (RMS) values of motor unit potentials from surface electrodes on each muscle (biceps brachii, triceps brachii, biceps femoris, rectus femoris) during isometric exercises of elbow flexion (EF), elbow extension (EE), knee flexion (KF), knee extension (KE) were acquired. New variables (MeanRMS, MaxRMS, and RatioRMS) were calculated from RMS values according to each exercise. Bioimpedance analysis (BIA) was performed to determine the segmental lean mass (SLM), segmental fat mass (SFM), and appendicular skeletal muscle mass (ASM). Muscle thicknesses were measured using ultrasonography (US). sEMG parameters showed positive correlations with MVC strength, SLM, ASM, and muscle thickness measured by US, but showed negative correlations with SFM. An equation was developed for ASM: ASM = −26.04 + 20.345 × Height + 0.178 × weight − 2.065 × (1, if female; 0, if male) + 0.327 × RatioRMS(KF) + 0.965 × MeanRMS(EE) (SEE = 1.167, adjusted R(2) = 0.934). sEMG parameters in controlled conditions may represent overall muscle strength and muscle mass in healthy individuals.
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spelling pubmed-103021412023-06-29 Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength Sung, Joo Hye Baek, Seol-Hee Park, Jin-Woo Rho, Jeong Hwa Kim, Byung-Jo Sensors (Basel) Article The need for developing a simple and effective assessment tool for muscle mass has been increasing in a rapidly aging society. This study aimed to evaluate the feasibility of the surface electromyography (sEMG) parameters for estimating muscle mass. Overall, 212 healthy volunteers participated in this study. Maximal voluntary contraction (MVC) strength and root mean square (RMS) values of motor unit potentials from surface electrodes on each muscle (biceps brachii, triceps brachii, biceps femoris, rectus femoris) during isometric exercises of elbow flexion (EF), elbow extension (EE), knee flexion (KF), knee extension (KE) were acquired. New variables (MeanRMS, MaxRMS, and RatioRMS) were calculated from RMS values according to each exercise. Bioimpedance analysis (BIA) was performed to determine the segmental lean mass (SLM), segmental fat mass (SFM), and appendicular skeletal muscle mass (ASM). Muscle thicknesses were measured using ultrasonography (US). sEMG parameters showed positive correlations with MVC strength, SLM, ASM, and muscle thickness measured by US, but showed negative correlations with SFM. An equation was developed for ASM: ASM = −26.04 + 20.345 × Height + 0.178 × weight − 2.065 × (1, if female; 0, if male) + 0.327 × RatioRMS(KF) + 0.965 × MeanRMS(EE) (SEE = 1.167, adjusted R(2) = 0.934). sEMG parameters in controlled conditions may represent overall muscle strength and muscle mass in healthy individuals. MDPI 2023-06-10 /pmc/articles/PMC10302141/ /pubmed/37420659 http://dx.doi.org/10.3390/s23125490 Text en © 2023 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
Sung, Joo Hye
Baek, Seol-Hee
Park, Jin-Woo
Rho, Jeong Hwa
Kim, Byung-Jo
Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength
title Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength
title_full Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength
title_fullStr Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength
title_full_unstemmed Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength
title_short Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength
title_sort surface electromyography-driven parameters for representing muscle mass and strength
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10302141/
https://www.ncbi.nlm.nih.gov/pubmed/37420659
http://dx.doi.org/10.3390/s23125490
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