Anfis-based P300 rhythm detection using wavelet feature extraction on blind source separated Eeg signals

Juan Manuel Ramirez-Cortes, Vicente Alarcon-Aquino, Gerardo Rosas-Cholula, Pilar Gomez-Gil, Jorge Escamilla-Ambrosio

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

6 Citas (Scopus)

Resumen

An experiment on the detection of a P-300 rhythm for potential applications on brain computer interfaces (BCI) using an Adaptive Neuro Fuzzy algorithm (ANFIS) is presented. P300 evoked potential is an electroencephalographic (EEG) signal obtained at the central-parietal region of the brain in response to rare or unexpected events. The P300 evoked potential is obtained from visual stimuli followed by a motor response from the subject. The EEG signals are obtained with a 14 electrodes Emotiv EPOC headset. Preprocessing of the signals includes denoising and blind source separation using an Independent Component Analysis algorithm. The P300 rhythm is detected using the discrete wavelet transform (DWT) applied on the preprocessed signal as a feature extractor, and further entered to the ANFIS system. Experimental results are presented.

Idioma originalInglés
Título de la publicación alojadaIntelligent Automation and Systems Engineering
Páginas353-365
Número de páginas13
DOI
EstadoPublicada - 2011
EventoInternational Conference on Advances in Intelligent Automation and Systems Engineering - Berkeley, CA, Estados Unidos
Duración: 20 oct. 201022 oct. 2010

Serie de la publicación

NombreLecture Notes in Electrical Engineering
Volumen103 LNEE
ISSN (versión impresa)1876-1100
ISSN (versión digital)1876-1119

Conferencia

ConferenciaInternational Conference on Advances in Intelligent Automation and Systems Engineering
País/TerritorioEstados Unidos
CiudadBerkeley, CA
Período20/10/1022/10/10

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