Hybrid EEG—Eye Tracker: Automatic Identification and Removal of Eye Movement and Blink Artifacts from Electroencephalographic Signal

Contamination of eye movement and blink artifacts in Electroencephalogram (EEG) recording makes the analysis of EEG data more difficult and could result in mislead findings. Efficient removal of these artifacts from EEG data is an essential step in improving classification accuracy to develop the br...

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Detalles Bibliográficos

Principais autores:	Malik M. Naeem Mannan, Shinjung Kim, Myung Yung Jeong, M. Ahmad Kamran
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2016-02-01
Series:	Sensors
Assuntos:	electroencephalogram eye tracker ocular artifacts independent component analysis auto-regressive exogenous model affine projection algorithm composite multi-scale entropy median absolute deviation
Acceso en liña:	http://www.mdpi.com/1424-8220/16/2/241
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