Classification of Surface EMG Using Wavelet Packet Energy Analysis and a Genetic Algorithm-Based Support Vector Machine
The aim of our study was to recognize results of surface electromyography (sEMG) recorded under conditions of a maximum voluntary contraction (MVС) and fatigue states using wavelet packet transform and energy analysis. The sEMG signals were recorded in 10 young men from the right upper limb with a...
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| Published in: | Нейрофизиология |
|---|---|
| Date: | 2013 |
| Main Authors: | Rong, Y., Hao, D., Han, X., Zhang, Y., Zhang, J., Zeng, Y. |
| Format: | Article |
| Language: | English |
| Published: |
Інститут фізіології ім. О.О. Богомольця НАН України
2013
|
| Online Access: | https://nasplib.isofts.kiev.ua/handle/123456789/148026 |
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| Journal Title: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Cite this: | Classification of Surface EMG Using Wavelet Packet Energy Analysis and a Genetic Algorithm-Based Support Vector Machine / Y. Rong, D. Hao, X. Han, Y. Zhang, J. Zhang, Y. Zeng // Нейрофизиология. — 2013. — Т. 45, № 1. — С. 44-54. — Бібліогр.: 30 назв. — англ. |
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