Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps Curls
Muscle fatigue, a key concern in sports science, rehabilitation, and occupational health, influences performance, injury risk, and provides insights into muscle functionality and endurance. Surface electromyography (sEMG) has emerged as a vital tool for non-invasively tracking muscle electrical acti...
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MMU Press
2024-10-01
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| Series: | Journal of Informatics and Web Engineering |
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| Online Access: | https://journals.mmupress.com/index.php/jiwe/article/view/950 |
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| author | Tang Ming Ling Weay Ang Sellappan Palaniappan |
| author_facet | Tang Ming Ling Weay Ang Sellappan Palaniappan |
| author_sort | Tang Ming |
| collection | DOAJ |
| description | Muscle fatigue, a key concern in sports science, rehabilitation, and occupational health, influences performance, injury risk, and provides insights into muscle functionality and endurance. Surface electromyography (sEMG) has emerged as a vital tool for non-invasively tracking muscle electrical activity and gauging health. As its application for muscle fatigue assessment grows, identifying the most accurate analytical methods is essential. Current sEMG analyses employ both linear and nonlinear metrics to measure fatigue onset and progression, yet research is ongoing to determine which method is most effective in the context of dynamic contractions. The study was aimed to evaluate the efficacy of established linear and nonlinear methods in measuring muscle fatigue caused by dynamic contractions through surface electromyography (sEMG) signals. A group of twelve healthy individuals completed biceps curls at a consistent pace of one repetition per four seconds, which constituted 75% of their 10-repetition maximum. Concurrently, sEMG signals were captured from the biceps brachii muscle at 1000 Hz. To assess the sEMG signals during the initial, middle, and final sets of 10 repetitions, three linear metrics—mean frequency, median frequency, and spectral moment ratio (SMR)—along with two nonlinear approaches, namely sample entropy and detrended fluctuation analysis (DFA), were utilized. The study's outcomes indicated notable shifts in the SMR values and the two DFA-derived scaling exponents across the exercise sets. These results indicated that SMR, sample entropy, and DFA are effective in gauging muscle fatigue, with sample entropy and DFA demonstrating heightened sensitivity to the fatigue levels when compared to the linear metrics. |
| format | Article |
| id | doaj-art-3e8c7ea1dc74489a90b4ace254d214d5 |
| institution | Kabale University |
| issn | 2821-370X |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MMU Press |
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| series | Journal of Informatics and Web Engineering |
| spelling | doaj-art-3e8c7ea1dc74489a90b4ace254d214d52024-12-08T04:32:33ZengMMU PressJournal of Informatics and Web Engineering2821-370X2024-10-013312113210.33093/jiwe.2024.3.3.7950Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps CurlsTang Ming0https://orcid.org/0009-0000-4978-6663Ling Weay Ang1Sellappan Palaniappan2Malaysia University of Science and Technology, MalaysiaMalaysia University of Science and Technology, MalaysiaMalaysia University of Science and Technology, MalaysiaMuscle fatigue, a key concern in sports science, rehabilitation, and occupational health, influences performance, injury risk, and provides insights into muscle functionality and endurance. Surface electromyography (sEMG) has emerged as a vital tool for non-invasively tracking muscle electrical activity and gauging health. As its application for muscle fatigue assessment grows, identifying the most accurate analytical methods is essential. Current sEMG analyses employ both linear and nonlinear metrics to measure fatigue onset and progression, yet research is ongoing to determine which method is most effective in the context of dynamic contractions. The study was aimed to evaluate the efficacy of established linear and nonlinear methods in measuring muscle fatigue caused by dynamic contractions through surface electromyography (sEMG) signals. A group of twelve healthy individuals completed biceps curls at a consistent pace of one repetition per four seconds, which constituted 75% of their 10-repetition maximum. Concurrently, sEMG signals were captured from the biceps brachii muscle at 1000 Hz. To assess the sEMG signals during the initial, middle, and final sets of 10 repetitions, three linear metrics—mean frequency, median frequency, and spectral moment ratio (SMR)—along with two nonlinear approaches, namely sample entropy and detrended fluctuation analysis (DFA), were utilized. The study's outcomes indicated notable shifts in the SMR values and the two DFA-derived scaling exponents across the exercise sets. These results indicated that SMR, sample entropy, and DFA are effective in gauging muscle fatigue, with sample entropy and DFA demonstrating heightened sensitivity to the fatigue levels when compared to the linear metrics.https://journals.mmupress.com/index.php/jiwe/article/view/950muscle fatigue, surface electromyography (semg)dynamic contractionslinear and nonlinear metricsfatigue assessmentbiceps curl exercise |
| spellingShingle | Tang Ming Ling Weay Ang Sellappan Palaniappan Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps Curls Journal of Informatics and Web Engineering muscle fatigue , surface electromyography (semg) dynamic contractions linear and nonlinear metrics fatigue assessment biceps curl exercise |
| title | Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps Curls |
| title_full | Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps Curls |
| title_fullStr | Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps Curls |
| title_full_unstemmed | Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps Curls |
| title_short | Comparative Analysis of Linear and Nonlinear sEMG Methods for Detecting Muscle Fatigue During Dynamic Biceps Curls |
| title_sort | comparative analysis of linear and nonlinear semg methods for detecting muscle fatigue during dynamic biceps curls |
| topic | muscle fatigue , surface electromyography (semg) dynamic contractions linear and nonlinear metrics fatigue assessment biceps curl exercise |
| url | https://journals.mmupress.com/index.php/jiwe/article/view/950 |
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