Iterative Subspace Decomposition for Ocular Artifact Removal from EEG Recordings

Authors:
Cédric Gouy-Pailler;Reza Sameni;Marco Congedo;Christian Jutten
Affiliations:
GIPSA-lab, DIS/CNRS/INPG-UJF-Stendhal Domaine Universitaire, Saint Martin d'Hères Cedex, France 38402;College of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran;GIPSA-lab, DIS/CNRS/INPG-UJF-Stendhal Domaine Universitaire, Saint Martin d'Hères Cedex, France 38402;GIPSA-lab, DIS/CNRS/INPG-UJF-Stendhal Domaine Universitaire, Saint Martin d'Hères Cedex, France 38402
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

Citing 2
Cited 1

Matrix computations (3rd ed.)

Matrix computations (3rd ed.)
A comparative study of automatic techniques for ocular artifact reduction in spontaneous EEG signals based on clinical target variables: A simulation case

Computers in Biology and Medicine

A deflation procedure for subspace decomposition

IEEE Transactions on Signal Processing

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Abstract

In this study, we present a method to remove ocular artifacts from electroencephalographic (EEG) recordings. This method is based on the detection of the EOG activation periods from a reference EOG channel, definition of covariance matrices containing the nonstationary information of the EOG, and applying generalized eigenvalue decomposition (GEVD) onto these matrices to rank the components in order of resemblance with the EOG. An iterative procedure is further proposed to remove the EOG components in a deflation fashion.