Classification of Imaginary Motor Task from Electroencephalographic Signals: A Comparison of Feature Selection Methods and Classification Algorithms.

In this work, a Brain Computer interface able to decode imagery motor task from EEG is presented. The method uses time-frequency representation of the brain signal recorded in different regions of the brain to extract important features. Principal Component Analysis and Sequential Forward Selection...

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Detalles Bibliográficos

Publicado en:	Revista Mexicana de Ingeniería Biomédica Vol. 39; no. 1; pp. 95 - 105
Autores principales:	Vélez-Lora, H. J., Méndez-Vásquez, D. J., Delgado-Saa, J. F.
Formato:	Artículo
Publicado:	Sociedad Mexicana de Ingenieria Biomedica, A.C. jan-apr2018
Materias:	Brain physiology Computer interfaces Electroencephalography Information retrieval Task performance
Acceso en línea:	Ver este registro en EBSCOhost