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

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...

Полное описание

Библиографические подробности
Главные авторы: Malik M. Naeem Mannan, Shinjung Kim, Myung Yung Jeong, M. Ahmad Kamran
Формат: Статья
Язык:English
Опубликовано: MDPI AG 2016-02-01
Серии:Sensors
Предметы:
electroencephalogram
eye tracker
ocular artifacts
independent component analysis
auto-regressive exogenous model
affine projection algorithm
composite multi-scale entropy
median absolute deviation
Online-ссылка:http://www.mdpi.com/1424-8220/16/2/241

Internet

http://www.mdpi.com/1424-8220/16/2/241

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