Evaluation of muscle fatigue identification based on EMG feature
The aim of this study was to identify muscle fatigue during sub-maximal contraction on biceps brachii and triceps muscle on upper limb muscle through EMG feature. The relationship between muscle fatigues with EMG feature was evaluated by conducting on six volunteers on their upper limb muscle. The r...
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| Format: | Undergraduates Project Papers |
| Language: | English |
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2016
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| Online Access: | http://umpir.ump.edu.my/id/eprint/16299/ http://umpir.ump.edu.my/id/eprint/16299/1/Evaluation%20of%20muscle%20fatigue%20identification%20based%20on%20EMG%20feature.pdf |
| _version_ | 1848820157648994304 |
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| author | Nur Amelia Izzati, Mohd Amin |
| author_facet | Nur Amelia Izzati, Mohd Amin |
| author_sort | Nur Amelia Izzati, Mohd Amin |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The aim of this study was to identify muscle fatigue during sub-maximal contraction on biceps brachii and triceps muscle on upper limb muscle through EMG feature. The relationship between muscle fatigues with EMG feature was evaluated by conducting on six volunteers on their upper limb muscle. The raw EMG signal was recorded from biceps brachii muscle and triceps muscle in static posture at 30%, 50% and 70% of their maximum voluntary contraction (MVC). Band pass Butterworth filter (20-1000 Hz) and 1000 Hz of sampling frequency was applied during the experiments. The subjects was instructed to grip the hand dynamometer and the sEMG activity of the biceps brachii muscle and triceps muscle was recorded. Root mean square feature was calculated as EMG amplitude which have been computed in the filtered EMG signal recorded. Regression analysis and analysis of variance (ANOVA) were implemented to determine the significant of the feature with the muscle force. The result shows that muscle fatigue was performed at 70% of MVC at both of muscle. The relationship between 30% and 70% of force was most significant value which was 0.000 (P<0.05) on biceps brachii muscle while most significant value was 0.035 (P<0.05) resulted between 30% and 70% of force on triceps muscle. |
| first_indexed | 2025-11-15T02:04:59Z |
| format | Undergraduates Project Papers |
| id | ump-16299 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:04:59Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-162992023-11-22T01:42:25Z http://umpir.ump.edu.my/id/eprint/16299/ Evaluation of muscle fatigue identification based on EMG feature Nur Amelia Izzati, Mohd Amin Q Science (General) TS Manufactures The aim of this study was to identify muscle fatigue during sub-maximal contraction on biceps brachii and triceps muscle on upper limb muscle through EMG feature. The relationship between muscle fatigues with EMG feature was evaluated by conducting on six volunteers on their upper limb muscle. The raw EMG signal was recorded from biceps brachii muscle and triceps muscle in static posture at 30%, 50% and 70% of their maximum voluntary contraction (MVC). Band pass Butterworth filter (20-1000 Hz) and 1000 Hz of sampling frequency was applied during the experiments. The subjects was instructed to grip the hand dynamometer and the sEMG activity of the biceps brachii muscle and triceps muscle was recorded. Root mean square feature was calculated as EMG amplitude which have been computed in the filtered EMG signal recorded. Regression analysis and analysis of variance (ANOVA) were implemented to determine the significant of the feature with the muscle force. The result shows that muscle fatigue was performed at 70% of MVC at both of muscle. The relationship between 30% and 70% of force was most significant value which was 0.000 (P<0.05) on biceps brachii muscle while most significant value was 0.035 (P<0.05) resulted between 30% and 70% of force on triceps muscle. 2016-06 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/16299/1/Evaluation%20of%20muscle%20fatigue%20identification%20based%20on%20EMG%20feature.pdf Nur Amelia Izzati, Mohd Amin (2016) Evaluation of muscle fatigue identification based on EMG feature. Faculty of Manufacturing Engineering, Universiti Malaysia Pahang. |
| spellingShingle | Q Science (General) TS Manufactures Nur Amelia Izzati, Mohd Amin Evaluation of muscle fatigue identification based on EMG feature |
| title | Evaluation of muscle fatigue identification based on EMG feature |
| title_full | Evaluation of muscle fatigue identification based on EMG feature |
| title_fullStr | Evaluation of muscle fatigue identification based on EMG feature |
| title_full_unstemmed | Evaluation of muscle fatigue identification based on EMG feature |
| title_short | Evaluation of muscle fatigue identification based on EMG feature |
| title_sort | evaluation of muscle fatigue identification based on emg feature |
| topic | Q Science (General) TS Manufactures |
| url | http://umpir.ump.edu.my/id/eprint/16299/ http://umpir.ump.edu.my/id/eprint/16299/1/Evaluation%20of%20muscle%20fatigue%20identification%20based%20on%20EMG%20feature.pdf |