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Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training
An individual's long-term neuromuscular adaptation can be measured through time-domain analyses of surface electromyograms (EMG) in regular resistance-based training. The perceived changes in recruitment, such as those measured during muscle fatigue, can subsequently prolong the recovery time i...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9676259/ https://www.ncbi.nlm.nih.gov/pubmed/36419714 http://dx.doi.org/10.3389/fresc.2022.981990 |
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author | Stefanovic, Filip Ramanarayanan, Shilpa Karkera, Nidhi U. Mujumdar, Radhika Sivaswaamy Mohana, Preethi Hostler, David |
author_facet | Stefanovic, Filip Ramanarayanan, Shilpa Karkera, Nidhi U. Mujumdar, Radhika Sivaswaamy Mohana, Preethi Hostler, David |
author_sort | Stefanovic, Filip |
collection | PubMed |
description | An individual's long-term neuromuscular adaptation can be measured through time-domain analyses of surface electromyograms (EMG) in regular resistance-based training. The perceived changes in recruitment, such as those measured during muscle fatigue, can subsequently prolong the recovery time in rehabilitation applications. Thus, by developing quantifiable methods for measuring neuromuscular adaptation, adjuvant treatments applied during neurorehabilitation can be improved to reduce recovery times and to increase patient quality of care. This study demonstrates a novel time-domain analysis of long-term changes in EMG captured neuromuscular activity that we aim to use to develop a quantified performance metric for muscle-based intervention training and optimization of an individual. We measure EMG of endurance and hypertrophy-based resistance exercises of healthy participants over 100 days to identify trends in long-term neuromuscular adaptation. Particularly, we show that the rate of EMG amplitude increase (motor recruitment) is dependent on the training modality of an individual. Particularly, EMG decreases over time with repetitive training – but the rate of decrease is different in hypertrophy, endurance, and control exercises. We found that the EMG peak contraction decreases across all subjects, on average, by 8.23 dB during hypertrophy exercise and 10.09 dB for endurance exercises over 100 days of training, while control participants showed negligible change. This represents approximately 2 dB difference EMG activity when comparing endurance and hypertrophy exercises, and >8 dB change when comparing to our control cases. As such, we show that the slope of the long-term EMG activity is related to the resistance-based exercise. We believe this can be used to identify person-specific performance metrics, and to create optimized interventions using a measured performance baseline of an individual. |
format | Online Article Text |
id | pubmed-9676259 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96762592022-11-22 Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training Stefanovic, Filip Ramanarayanan, Shilpa Karkera, Nidhi U. Mujumdar, Radhika Sivaswaamy Mohana, Preethi Hostler, David Front Rehabil Sci Rehabilitation Sciences An individual's long-term neuromuscular adaptation can be measured through time-domain analyses of surface electromyograms (EMG) in regular resistance-based training. The perceived changes in recruitment, such as those measured during muscle fatigue, can subsequently prolong the recovery time in rehabilitation applications. Thus, by developing quantifiable methods for measuring neuromuscular adaptation, adjuvant treatments applied during neurorehabilitation can be improved to reduce recovery times and to increase patient quality of care. This study demonstrates a novel time-domain analysis of long-term changes in EMG captured neuromuscular activity that we aim to use to develop a quantified performance metric for muscle-based intervention training and optimization of an individual. We measure EMG of endurance and hypertrophy-based resistance exercises of healthy participants over 100 days to identify trends in long-term neuromuscular adaptation. Particularly, we show that the rate of EMG amplitude increase (motor recruitment) is dependent on the training modality of an individual. Particularly, EMG decreases over time with repetitive training – but the rate of decrease is different in hypertrophy, endurance, and control exercises. We found that the EMG peak contraction decreases across all subjects, on average, by 8.23 dB during hypertrophy exercise and 10.09 dB for endurance exercises over 100 days of training, while control participants showed negligible change. This represents approximately 2 dB difference EMG activity when comparing endurance and hypertrophy exercises, and >8 dB change when comparing to our control cases. As such, we show that the slope of the long-term EMG activity is related to the resistance-based exercise. We believe this can be used to identify person-specific performance metrics, and to create optimized interventions using a measured performance baseline of an individual. Frontiers Media S.A. 2022-11-07 /pmc/articles/PMC9676259/ /pubmed/36419714 http://dx.doi.org/10.3389/fresc.2022.981990 Text en © 2022 Stefanovic, Ramanarayanan, Karkera, Mujumdar, Sivaswaamy Mohana and Hostler. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Rehabilitation Sciences Stefanovic, Filip Ramanarayanan, Shilpa Karkera, Nidhi U. Mujumdar, Radhika Sivaswaamy Mohana, Preethi Hostler, David Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training |
title | Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training |
title_full | Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training |
title_fullStr | Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training |
title_full_unstemmed | Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training |
title_short | Rate of change in longitudinal EMG indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training |
title_sort | rate of change in longitudinal emg indicates time course of an individual's neuromuscular adaptation in resistance-based muscle training |
topic | Rehabilitation Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9676259/ https://www.ncbi.nlm.nih.gov/pubmed/36419714 http://dx.doi.org/10.3389/fresc.2022.981990 |
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