Optimum Spatio-Spectral Filtering Network for Brain-Computer Interface

This paper proposes a feature extraction method for motor imagery brain-computer interface (BCI) using electroencephalogram. We consider the primary neurophysiologic phenomenon of motor imagery, termed event-related desynchronization, and formulate the learning task for feature extraction as maximiz...

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Vydáno v:	IEEE transactions on neural networks Ročník 22; číslo 1; s. 52 - 63
Hlavní autoři:	Zhang, Haihong, Chin, Zheng Yang, Ang, Kai Keng, Guan, Cuntai, Wang, Chuanchu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY IEEE 01.01.2011 Institute of Electrical and Electronics Engineers
Témata:	Applied sciences Artificial intelligence Band pass filters Brain - physiology Brain-computer interface Computer science; control theory; systems Computer systems and distributed systems. User interface Electroencephalography Electroencephalography - methods Entropy Evoked Potentials, Motor - physiology Exact sciences and technology Feature extraction Humans Male motor imagery electroencephalography Mutual information Neural Networks (Computer) Optimization Pattern Recognition, Automated - standards Rhythm Software spatio-spectral filtering User-Computer Interface Brain Gradient Statistical analysis Filtering Electroencephalography Pattern recognition Network interfaces spatio-spectral filtering motor imagery electroencephalography Optimization Search algorithm Brain-computer interface User interface Classification Feature extraction Spatial filters Desynchronization Learning algorithm Artificial intelligence Pattern extraction Mutual information
ISSN:	1045-9227, 1941-0093, 1941-0093
On-line přístup:	Získat plný text
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