Abstract
The presence of electrooculographic (EOG) artifacts in the electroencephalographic (EEG) signal is a major problem in the study of brain potentials. A variety of algorithms have been proposed to reject these artifacts including methods based on regression and blind source separation (BSS) techniques. None of them has so far been established as the method of choice. In the present study, the performances of five widely used EOG artifact rejection techniques are compared. The compared methodologies include two fully automated regression methods, one based on Least Mean Square (LMS) for its optimization process, and the other on Recursive Least Square (RLS) algorithm, two BSS techniques which use respectively the Extended — Independent Component Analysis (ext — ICA) and the Second Order Blind Identification (SOBI), and finally a time-varying adaptive algorithm based on H ∞ principles (H ∞ — TV). Each algorithm was applied in real EEG data and then their performance quantified in the time domain. The performance of RLS and H ∞ — TV were poor in removing eye — blink artifacts. For the rest of the methods the results supported the use of LMS technique and suggested the need for further research examining the performance of various artifact rejection techniques in both time and frequency domain.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Berg B, Scherg M. (1991) Dipole models of eye movements and blinks. Electroencephalogr Clin Neurophysiol; 79:36–44.
Croft R.J., Barry R.J., (2000). Removal of ocular artifact from the EEG: a review. Neurophysiologie Clinique 30, 5–19.
Lins, O.G., Picton, T.W., Berg, P., Scherg, M., (1993). Ocular artefacts in recording EEGs and event-related potentials: II. Source dipoles and source components. Brain Topography 6(1), 65–78.
Jung T.P., Humphries C., Lee T.W., Makeig S., et al. (1998). Extended ICA Removes Artifacts from Electroencephalographic Recordings. Advances in Neural Information Processing Systems 10, M. Jordan et al. Eds., MIT Press, Cambridge USA
Garrick L. Wallstrom, Robert E. Kass, Anita Miller, Jeffrey F. Cohn, Nathan A. Fox (2004). Automatic correction of ocular artifacts in the EEG: a comparison of regression-based and component-based methods, International Journal of Psychophysiology 53 105–119
M. M. C. van den Berg-Lenssen, J. A. M. van Gisbergen and B. W. Jervis (1994), Comparison of two methods for correcting ocular artefacts in EEGs, Medical and Biological Engineering and Computing, 32: 501–511.
Rodney J. Croft, Jody S. Chandler, Robert J. Barry, Nicholas R. Cooper and Adam R. Clarke, (2004), EOG correction: A comparison of four methods, Psychophysiology 42:16–24.
Saeid Sanei and J.A. Chambers, (2007) EEG signal Processing, John Wiley & Sons, Ltd. UK.
P. He, G. Wilson, C. Russell, (2004) Removal of ocular artefacts from electroencephalogram by adaptive filtering, Med. Biol. Eng. Comput. 42 407–412.
Gomez-Herrero G., De Clercq W., Anwar H., et al. (2006). Automatic removal of ocular artifacts in the EEG without a reference EOG channel. In 7th Nordic Signal Processing Symposium NORSIG, Reykjavik, Iceland.
Puthusserypady S., Ratnarajah T., (2006) Robust adaptive techniques for minimization of EOG artefacts from EEG signals. Signal Processing 86 2351–2363
P. J. Lang, M. M. Bradley, and B. N. Cuthbert, (1999), International Affective Picture System (IAPS): Technical Manual and Affective Ratings, Center for Research in Psychophysiology, University of Florida, Gainsville, FL
A Delorme & S Makeig., (2004), EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics, Journal of Neuroscience Methods 134:9–21
Bell A. J., Sejnowski T. J. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7, 1129–1159.
Lee T.-W., Girolami M., Sejnowski T. J. (1999). Independent component analysis using an extended infomax algorithm for mixed sub-Gaussian and super Gaussian sources. Neural Computation, 11, 606–633.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Klados, M.A., Papadelis, C., Lithari, C.D., Bamidis, P.D. (2009). The Removal Of Ocular Artifacts From EEG Signals: A Comparison of Performances For Different Methods. In: Vander Sloten, J., Verdonck, P., Nyssen, M., Haueisen, J. (eds) 4th European Conference of the International Federation for Medical and Biological Engineering. IFMBE Proceedings, vol 22. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89208-3_300
Download citation
DOI: https://doi.org/10.1007/978-3-540-89208-3_300
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89207-6
Online ISBN: 978-3-540-89208-3
eBook Packages: EngineeringEngineering (R0)