A Hybrid Algorithm for Removal of Eye Blinking Artifacts.pdf (579.29 kB)
A hybrid algorithm for removal of eye blinking artifacts from electroencephalograms
conference contribution
posted on 2009-12-08, 10:09 authored by Leor Shoker, Saeid Sanei, Jonathon ChambersA 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.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Citation
SHOKER, L., SANEI, S. and CHAMBERS, J.A., 2005. A hybrid algorithm for removal of eye blinking artifacts from electroencephalograms. IN: 2005 13th Workshop on Statistical Signal Processing (IEEE/SP 2005), Bordeaux, France, 17-20 July, pp. 1014-1017.Publisher
© IEEEVersion
- VoR (Version of Record)
Publication date
2005Notes
This is a conference paper [© IEEE]. It is also available at: http://ieeexplore.ieee.org/ Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Language
- en