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A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement
A real-time muscle fatigue monitoring system was developed to quantitatively detect the muscle fatigue of subjects during cycling movement, where a fatigue progression measure (FPM) was built-in. During the cycling movement, the electromyogram (EMG) signals of the vastus lateralis and gastrocnemius...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168434/ https://www.ncbi.nlm.nih.gov/pubmed/25014101 http://dx.doi.org/10.3390/s140712410 |
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author | Chen, Szi-Wen Liaw, Jiunn-Woei Chan, Hsiao-Lung Chang, Ya-Ju Ku, Chia-Hao |
author_facet | Chen, Szi-Wen Liaw, Jiunn-Woei Chan, Hsiao-Lung Chang, Ya-Ju Ku, Chia-Hao |
author_sort | Chen, Szi-Wen |
collection | PubMed |
description | A real-time muscle fatigue monitoring system was developed to quantitatively detect the muscle fatigue of subjects during cycling movement, where a fatigue progression measure (FPM) was built-in. During the cycling movement, the electromyogram (EMG) signals of the vastus lateralis and gastrocnemius muscles in one leg as well as cycling speed are synchronously measured in a real-time fashion. In addition, the heart rate (HR) and the Borg rating of perceived exertion scale value are recorded per minute. Using the EMG signals, the electrical activity and median frequency (MF) are calculated per cycle. Moreover, the updated FPM, based on the percentage of reduced MF counts during cycling movement, is calculated to measure the onset time and the progressive process of muscle fatigue. To demonstrate the performance of our system, five young healthy subjects were recruited. Each subject was asked to maintain a fixed speed of 60 RPM, as best he/she could, under a constant load during the pedaling. When the speed reached 20 RPM or the HR reached the maximal training HR, the experiment was then terminated immediately. The experimental results show that the proposed system may provide an on-line fatigue monitoring and analysis for the lower extremity muscles during cycling movement. |
format | Online Article Text |
id | pubmed-4168434 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-41684342014-09-19 A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement Chen, Szi-Wen Liaw, Jiunn-Woei Chan, Hsiao-Lung Chang, Ya-Ju Ku, Chia-Hao Sensors (Basel) Article A real-time muscle fatigue monitoring system was developed to quantitatively detect the muscle fatigue of subjects during cycling movement, where a fatigue progression measure (FPM) was built-in. During the cycling movement, the electromyogram (EMG) signals of the vastus lateralis and gastrocnemius muscles in one leg as well as cycling speed are synchronously measured in a real-time fashion. In addition, the heart rate (HR) and the Borg rating of perceived exertion scale value are recorded per minute. Using the EMG signals, the electrical activity and median frequency (MF) are calculated per cycle. Moreover, the updated FPM, based on the percentage of reduced MF counts during cycling movement, is calculated to measure the onset time and the progressive process of muscle fatigue. To demonstrate the performance of our system, five young healthy subjects were recruited. Each subject was asked to maintain a fixed speed of 60 RPM, as best he/she could, under a constant load during the pedaling. When the speed reached 20 RPM or the HR reached the maximal training HR, the experiment was then terminated immediately. The experimental results show that the proposed system may provide an on-line fatigue monitoring and analysis for the lower extremity muscles during cycling movement. MDPI 2014-07-10 /pmc/articles/PMC4168434/ /pubmed/25014101 http://dx.doi.org/10.3390/s140712410 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Chen, Szi-Wen Liaw, Jiunn-Woei Chan, Hsiao-Lung Chang, Ya-Ju Ku, Chia-Hao A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement |
title | A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement |
title_full | A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement |
title_fullStr | A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement |
title_full_unstemmed | A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement |
title_short | A Real-Time Fatigue Monitoring and Analysis System for Lower Extremity Muscles with Cycling Movement |
title_sort | real-time fatigue monitoring and analysis system for lower extremity muscles with cycling movement |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4168434/ https://www.ncbi.nlm.nih.gov/pubmed/25014101 http://dx.doi.org/10.3390/s140712410 |
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