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 u...
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| Veröffentlicht in: | Нейрофизиология |
|---|---|
| Datum: | 2013 |
| Hauptverfasser: | , , , , , |
| Format: | Artikel |
| Sprache: | Englisch |
| Veröffentlicht: |
Інститут фізіології ім. О.О. Богомольця НАН України
2013
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| Online Zugang: | https://nasplib.isofts.kiev.ua/handle/123456789/148026 |
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| Назва журналу: | Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| Zitieren: | 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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