Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task
This paper proposes a technique to automatically categorize work levels categories to improve the conventional functional capacity evaluation's core lifting task. Surface EMG signals were collected from biceps brachii and erector spinae muscles. Spectrogram was used as a pre-processing approach...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2018
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| Online Access: | http://psasir.upm.edu.my/id/eprint/36594/ http://psasir.upm.edu.my/id/eprint/36594/1/Implementation%20of%20spectrogram%20for%20an%20improved%20EMG-based%20functional%20capacity%20evaluation%27s%20core-lifting%20task.pdf |
| _version_ | 1848848376590761984 |
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| author | Shair, Ezreen Farina Ahmad, Siti Anom Marhaban, Mohammad Hamiruce Abdullah, Abdul Rahim Mohd Tamrin, Shamsul Bahri |
| author_facet | Shair, Ezreen Farina Ahmad, Siti Anom Marhaban, Mohammad Hamiruce Abdullah, Abdul Rahim Mohd Tamrin, Shamsul Bahri |
| author_sort | Shair, Ezreen Farina |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This paper proposes a technique to automatically categorize work levels categories to improve the conventional functional capacity evaluation's core lifting task. Surface EMG signals were collected from biceps brachii and erector spinae muscles. Spectrogram was used as a pre-processing approach for auto-segmentation of the EMG signal and for the feature extraction. This set of features was extracted to accurately differentiate between a medium work level and heavy work level. These features were then reduced using linear discriminant analysis and support vector machine acts as a classifier. The results showed that the proposed system offered excellent performance in classifying the work levels categories with high accuracy, sensitivity, specificity, and zero cross-validation error. |
| first_indexed | 2025-11-15T09:33:31Z |
| format | Conference or Workshop Item |
| id | upm-36594 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:33:31Z |
| publishDate | 2018 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-365942020-06-16T01:31:19Z http://psasir.upm.edu.my/id/eprint/36594/ Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task Shair, Ezreen Farina Ahmad, Siti Anom Marhaban, Mohammad Hamiruce Abdullah, Abdul Rahim Mohd Tamrin, Shamsul Bahri This paper proposes a technique to automatically categorize work levels categories to improve the conventional functional capacity evaluation's core lifting task. Surface EMG signals were collected from biceps brachii and erector spinae muscles. Spectrogram was used as a pre-processing approach for auto-segmentation of the EMG signal and for the feature extraction. This set of features was extracted to accurately differentiate between a medium work level and heavy work level. These features were then reduced using linear discriminant analysis and support vector machine acts as a classifier. The results showed that the proposed system offered excellent performance in classifying the work levels categories with high accuracy, sensitivity, specificity, and zero cross-validation error. IEEE 2018 Conference or Workshop Item PeerReviewed text en http://psasir.upm.edu.my/id/eprint/36594/1/Implementation%20of%20spectrogram%20for%20an%20improved%20EMG-based%20functional%20capacity%20evaluation%27s%20core-lifting%20task.pdf Shair, Ezreen Farina and Ahmad, Siti Anom and Marhaban, Mohammad Hamiruce and Abdullah, Abdul Rahim and Mohd Tamrin, Shamsul Bahri (2018) Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task. In: 2018 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), 3-6 Dec. 2018, Kuching, Sarawak, Malaysia. (pp. 13-17). 10.1109/IECBES.2018.8626612 |
| spellingShingle | Shair, Ezreen Farina Ahmad, Siti Anom Marhaban, Mohammad Hamiruce Abdullah, Abdul Rahim Mohd Tamrin, Shamsul Bahri Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task |
| title | Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task |
| title_full | Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task |
| title_fullStr | Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task |
| title_full_unstemmed | Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task |
| title_short | Implementation of spectrogram for an improved EMG-based functional capacity evaluation's core-lifting task |
| title_sort | implementation of spectrogram for an improved emg-based functional capacity evaluation's core-lifting task |
| url | http://psasir.upm.edu.my/id/eprint/36594/ http://psasir.upm.edu.my/id/eprint/36594/ http://psasir.upm.edu.my/id/eprint/36594/1/Implementation%20of%20spectrogram%20for%20an%20improved%20EMG-based%20functional%20capacity%20evaluation%27s%20core-lifting%20task.pdf |