Citation
Abstract
Electromyography EMG is a standout amongst the most regularly utilized tools to study human muscle condition. But due to the intricate attributes of the EMG itself, time-frequency distributions such as Gabor transform and spectrogram are more preferred than the simpler time distribution and frequency distribution. These techniques have been broadly utilized as it can provide both time and frequency information. However, both techniques have a fix window size for all frequency values, thus there exist a problem of determination of the window size, where excessively limit window and too wide window, will result in poor frequency resolution and time resolution, respectively. Along these lines, the point of this study is to choose the best window size so as to be utilized with Gabor transform to screen human muscle activity during core-lifting task. Four electrodes were placed on the right and left biceps brachii, and left and right erector spinae. In this study, the results of five acceptable window sizes (300, 400, 430, 450 and 520) were shown, despite the fact that other window sizes were also tested. Three criteria have been considered during the determination of the best window size, which are good time resolution, good frequency resolution, and high accuracy. Results demonstrate that window size of 450 is the best compared to others. As an additional analysis, the result is compared to a spectrogram and it can be seen that Gabor transform is better, as it has the flexibility in choosing the window size, thus affects the resolution and accuracy.
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Official URL or Download Paper: http://journal.uad.ac.id/index.php/TELKOMNIKA/arti...
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Engineering Faculty of Medicine and Health Science Malaysian Research Institute on Ageing |
DOI Number: | https://doi.org/10.12928/TELKOMNIKA.v16i4.9049 |
Publisher: | Universitas Ahmad Dahlan |
Keywords: | Electromyography; Time-frequency distribution; Gabor transform; Best window size; Lifting task |
Depositing User: | Nurul Ainie Mokhtar |
Date Deposited: | 19 Apr 2020 10:04 |
Last Modified: | 19 Apr 2020 10:04 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.12928/TELKOMNIKA.v16i4.9049 |
URI: | http://psasir.upm.edu.my/id/eprint/72223 |
Statistic Details: | View Download Statistic |
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