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Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals
Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entr...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5610701/ https://www.ncbi.nlm.nih.gov/pubmed/28974932 http://dx.doi.org/10.3389/fphys.2017.00679 |
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author | Hodson-Tole, Emma F. Wakeling, James M. |
author_facet | Hodson-Tole, Emma F. Wakeling, James M. |
author_sort | Hodson-Tole, Emma F. |
collection | PubMed |
description | Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity ([Formula: see text]) and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity. |
format | Online Article Text |
id | pubmed-5610701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-56107012017-10-03 Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals Hodson-Tole, Emma F. Wakeling, James M. Front Physiol Physiology Appropriate neuromuscular functioning is essential for survival and features underpinning motor control are present in myoelectric signals recorded from skeletal muscles. One approach to quantify control processes related to function is to assess signal variability using measures such as Sample Entropy. Here we developed a theoretical framework to simulate the effect of variability in burst duration, activation duty cycle, and intensity on the Entropic Half-Life (EnHL) in myoelectric signals. EnHLs were predicted to be <40 ms, and to vary with fluctuations in myoelectric signal amplitude and activation duty cycle. Comparison with myoelectic data from rats walking and running at a range of speeds and inclines confirmed the range of EnHLs, however, the direction of EnHL change in response to altered locomotor demand was not correctly predicted. The discrepancy reflected different associations between the ratio of the standard deviation and mean signal intensity ([Formula: see text]) and duty factor in simulated and physiological data, likely reflecting additional information in the signals from the physiological data (e.g., quiescent phase content; variation in action potential shapes). EnHL could have significant value as a novel marker of neuromuscular responses to alterations in perceived locomotor task complexity and intensity. Frontiers Media S.A. 2017-09-19 /pmc/articles/PMC5610701/ /pubmed/28974932 http://dx.doi.org/10.3389/fphys.2017.00679 Text en Copyright © 2017 Hodson-Tole and Wakeling. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor 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 | Physiology Hodson-Tole, Emma F. Wakeling, James M. Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
title | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
title_full | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
title_fullStr | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
title_full_unstemmed | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
title_short | Movement Complexity and Neuromechanical Factors Affect the Entropic Half-Life of Myoelectric Signals |
title_sort | movement complexity and neuromechanical factors affect the entropic half-life of myoelectric signals |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5610701/ https://www.ncbi.nlm.nih.gov/pubmed/28974932 http://dx.doi.org/10.3389/fphys.2017.00679 |
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