2134/5614
Leor Shoker
Leor
Shoker
Saeid Sanei
Saeid
Sanei
Jonathon Chambers
Jonathon
Chambers
A hybrid algorithm for removal of eye blinking artifacts from electroencephalograms
Loughborough University
2009
Eye blinking artifact
Blind source separation
Support vector machines
Electroencephalogram and electroculogram
Mechanical Engineering not elsewhere classified
2009-12-08 10:09:01
Conference contribution
https://repository.lboro.ac.uk/articles/conference_contribution/A_hybrid_algorithm_for_removal_of_eye_blinking_artifacts_from_electroencephalograms/9554645
A robust method for removal of artifacts such as eye blinks and electrocardiogram (ECG) from the electroencephalograms (EEGs)
has been developed in this paper. The proposed hybrid method fuses
support vector machines (SVMs) based classification and blind source
separation (BSS) based on independent component analysis (ICA). The
carefully chosen features for the classifier mainly represent the data
higher order statistics. We use the second order blind identification
(SOBI) algorithm to separate the EEG into statistically independent
sources and SVMs to identify the artifact components and thereby to
remove such signals. The remaining independent components are remixed
to reproduce the artifact free EEGs. Objective and subjective results from
the simulation studies show that the algorithm outperforms previously
proposed algorithms.