A hybrid algorithm for removal of eye blinking artifacts from electroencephalograms

Shoker, L, Sanei, S and Chambers, J (2005) A hybrid algorithm for removal of eye blinking artifacts from electroencephalograms

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Abstract

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. © 2005 IEEE.

Item Type:	Conference or Workshop Item (UNSPECIFIED)
Divisions :	Surrey research (other units)
Authors :	Name Email ORCID Shoker, L Sanei, S Chambers, J j.a.chambers@surrey.ac.uk
Date :	1 December 2005
Depositing User :	Symplectic Elements
Date Deposited :	17 May 2017 13:26
Last Modified :	23 Jan 2020 18:36
URI:	http://epubs.surrey.ac.uk/id/eprint/839234

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