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...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 48; no. 2; pp. 123 - 133 |
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| Autores principales: | , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Feb2010
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| Acceso en línea: | Ver este registro en EBSCOhost |