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Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis

This study investigated the complexity of the electromyography (EMG) of lower limb muscles when performing obstacle crossing tasks at different heights in poststroke subjects versus healthy controls. Five poststroke subjects and eight healthy controls were recruited to perform different obstacle cro...

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Autores principales: Chen, Ying, Hu, Huijing, Ma, Chenming, Zhan, Yinwei, Chen, Na, Li, Le, Song, Rong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857544/
https://www.ncbi.nlm.nih.gov/pubmed/29593632
http://dx.doi.org/10.3389/fneur.2018.00131
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author Chen, Ying
Hu, Huijing
Ma, Chenming
Zhan, Yinwei
Chen, Na
Li, Le
Song, Rong
author_facet Chen, Ying
Hu, Huijing
Ma, Chenming
Zhan, Yinwei
Chen, Na
Li, Le
Song, Rong
author_sort Chen, Ying
collection PubMed
description This study investigated the complexity of the electromyography (EMG) of lower limb muscles when performing obstacle crossing tasks at different heights in poststroke subjects versus healthy controls. Five poststroke subjects and eight healthy controls were recruited to perform different obstacle crossing tasks at various heights (randomly set at 10, 20, and 30% of the leg’s length). EMG signals were recorded from bilateral biceps femoris (BF), rectus femoris (RF), medial gastrocnemius, and tibialis anterior during obstacle crossing task. The fuzzy approximate entropy (fApEn) approach was used to analyze the complexity of the EMG signals. The fApEn values were significantly smaller in the RF of the trailing limb during the swing phase in poststroke subjects than healthy controls (p < 0.05), which may be an indication of smaller number and less frequent firing rates of the motor units. However, during the swing phase, there were non-significant increases in the fApEn values of BF and RF in the trailing limb of the stroke group compared with those of healthy controls, resulting in a coping strategy when facing challenging tasks. The fApEn values that increased with height were found in the BF of the leading limb during the stance phase and in the RF of the trailing limb during the swing phase (p < 0.05). The reason for this may have been a larger muscle activation associated with the increase in obstacle height. This study demonstrated a suitable and non-invasive method to evaluate muscle function after a stroke.
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spelling pubmed-58575442018-03-28 Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis Chen, Ying Hu, Huijing Ma, Chenming Zhan, Yinwei Chen, Na Li, Le Song, Rong Front Neurol Neuroscience This study investigated the complexity of the electromyography (EMG) of lower limb muscles when performing obstacle crossing tasks at different heights in poststroke subjects versus healthy controls. Five poststroke subjects and eight healthy controls were recruited to perform different obstacle crossing tasks at various heights (randomly set at 10, 20, and 30% of the leg’s length). EMG signals were recorded from bilateral biceps femoris (BF), rectus femoris (RF), medial gastrocnemius, and tibialis anterior during obstacle crossing task. The fuzzy approximate entropy (fApEn) approach was used to analyze the complexity of the EMG signals. The fApEn values were significantly smaller in the RF of the trailing limb during the swing phase in poststroke subjects than healthy controls (p < 0.05), which may be an indication of smaller number and less frequent firing rates of the motor units. However, during the swing phase, there were non-significant increases in the fApEn values of BF and RF in the trailing limb of the stroke group compared with those of healthy controls, resulting in a coping strategy when facing challenging tasks. The fApEn values that increased with height were found in the BF of the leading limb during the stance phase and in the RF of the trailing limb during the swing phase (p < 0.05). The reason for this may have been a larger muscle activation associated with the increase in obstacle height. This study demonstrated a suitable and non-invasive method to evaluate muscle function after a stroke. Frontiers Media S.A. 2018-03-12 /pmc/articles/PMC5857544/ /pubmed/29593632 http://dx.doi.org/10.3389/fneur.2018.00131 Text en Copyright © 2018 Chen, Hu, Ma, Zhan, Chen, Li and Song. 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) and the copyright owner 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 Neuroscience
Chen, Ying
Hu, Huijing
Ma, Chenming
Zhan, Yinwei
Chen, Na
Li, Le
Song, Rong
Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis
title Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis
title_full Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis
title_fullStr Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis
title_full_unstemmed Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis
title_short Stroke-Related Changes in the Complexity of Muscle Activation during Obstacle Crossing Using Fuzzy Approximate Entropy Analysis
title_sort stroke-related changes in the complexity of muscle activation during obstacle crossing using fuzzy approximate entropy analysis
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5857544/
https://www.ncbi.nlm.nih.gov/pubmed/29593632
http://dx.doi.org/10.3389/fneur.2018.00131
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