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...
Gespeichert in:
| Datum: | 2013 |
|---|---|
| Hauptverfasser: | Rong, Y., Hao, D., Han, X., Zhang, Y., Zhang, J., Zeng, Y. |
| Format: | Artikel |
| Sprache: | English |
| Veröffentlicht: |
Інститут фізіології ім. О.О. Богомольця НАН України
2013
|
| Schriftenreihe: | Нейрофизиология |
| 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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