Automatic removal of ocular artefacts using adaptive filtering and independent component analysis for electroencephalogram data
- 1 January 2012
- journal article
- research article
- Published by Institution of Engineering and Technology (IET) in IET Signal Processing
- Vol. 6 (2), 99-106
- https://doi.org/10.1049/iet-spr.2010.0135
Abstract
A new method for eye movement artefacts removal based on independent component analysis (ICA) and recursive least squares (RLS) is presented. The proposed algorithm combines the effective ICA capacity of separating artefacts from brain waves, together with the online interference cancellation achieved by adaptive filtering. Eye blink, saccades, eyes opening and closing produce changes of potentials at frontal areas. For this reason, the method uses as a reference the electrodes closest to the eyes Fp1, Fp2, F7 and F8, which register vertical and horizontal eye movements in the electroencephalogram (EEG) caused by these activities as an alternative of using extra dedicated electrooculogram (EOG) electrodes, which could not always be available and could be subject to larger variability. Both reference signals and EEG components are first projected into ICA domain and then the interference is estimated using the RLS algorithm. The component related to EOG artefact is automatically eliminated using channel localisations. Results from experimental data demonstrate that this approach is suitable for eliminating artefacts caused by eye movements, and the principles of this method can be extended to certain other artefacts as well, whenever a correlated reference signal is available.Keywords
This publication has 11 references indexed in Scilit:
- A comparative study of automatic techniques for ocular artifact reduction in spontaneous EEG signals based on clinical target variables: A simulation caseComputers in Biology and Medicine, 2008
- Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysisNeuroImage, 2006
- A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classificationClinical Neurophysiology, 2006
- Automatic removal of the eye blink artifact from EEG using an ICA-based template matching approachPhysiological Measurement, 2006
- Removal of ocular artifacts from electro-encephalogram by adaptive filteringMedical & Biological Engineering & Computing, 2004
- EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysisJournal of Neuroscience Methods, 2004
- Independent Component AnalysisPublished by MIT Press ,2004
- Automatic removal of eye movement and blink artifacts from EEG data using blind component separationPsychophysiology, 2003
- Independent Component Analysis as a Tool to Eliminate Artifacts in EEG: A Quantitative StudyJournal of Clinical Neurophysiology, 2003
- Blind signal separation: statistical principlesProceedings of the IEEE, 1998