Title :
A Hybrid Algorithm for Removal of Eye Blinking Artifacts from Electroencephalograms
Author :
Shoker, L. ; Sanei, Saeid ; Chambers, Jonathon
Author_Institution :
Centre of Digital Signal Process., Cardiff Univ.
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
Keywords :
blind source separation; electrocardiography; electroencephalography; higher order statistics; independent component analysis; medical signal processing; signal classification; support vector machines; ECG; EEG; ICA; SVM; blind source separation; electrocardiogram; electroencephalograms; eye blinking artifacts removal; higher order statistics; hybrid algorithm; independent component analysis; second order blind identification; signal classification; support vector machines; Blind source separation; Electrocardiography; Electroencephalography; Fuses; Higher order statistics; Independent component analysis; Robustness; Source separation; Support vector machine classification; Support vector machines;
Conference_Titel :
Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on
Conference_Location :
Novosibirsk
Print_ISBN :
0-7803-9403-8
DOI :
10.1109/SSP.2005.1628743
