Comparison of feature selection and classification methods for a brain-computer interface driven by non-motor imagery.

The aim of this study was to compare methods for feature extraction and classification of EEG signals for a brain-computer interface (BCI) driven by auditory and spatial navigation imagery. Features were extracted using autoregressive modeling and optimized discrete wavelet transform. The features w...

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Bibliographic Details

Published in:	Medical & Biological Engineering & Computing Vol. 48; no. 2; pp. 123 - 133
Main Authors:	Cabrera AF, Farina D, Dremstrup K, Cabrera, Alvaro Fuentes, Farina, Dario, Dremstrup, Kim
Format:	research Journal Article
Published:	Springer Nature Feb2010
Online Access:	View this record in EBSCOhost