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 Automatic removal of high-amplitude artefacts from single-channnel electroencephalograms
Please use this identifier to cite or link to this item http://hdl.handle.net/10773/5828

title: Automatic removal of high-amplitude artefacts from single-channnel electroencephalograms
authors: Teixeira, A. R.
Tomé, A. M.
Lang, E. W.
Gruber, P.
Silva, A. Martins da
keywords: Singular spectrum analysis (SSA)
Principal component analysis
Electrooculogram (EOG)
Electroencephalogram (EEG)
issue date: Jul-2006
publisher: Elsevier
abstract: In this work, we present a method to extract high-amplitude artefacts from single channel electroencephalogram (EEG) signals. The method is called local singular spectrum analysis (local SSA). It is based on a principal component analysis (PCA) applied to clusters of the multidimensional signals obtained after embedding the signals in their time-delayed coordinates. The decomposition of the multidimensional signals in each cluster is achieved by relating the largest eigenvalues with the large amplitude artefact component of the embedded signal. Then by reverting the clustering and embedding processes, the high-amplitude artefact can be extracted. Subtracting it from the original signal a corrected EEG signal results. The algorithm is applied to segments of real EEG recordings containing paroxysmal epileptiform activity contaminated by large EOG artefacts. We will show that the method can be applied also in parallel to correct all channels that present high-amplitude artefacts like ocular movement interferences or high-amplitude low frequency baseline drifts. The extracted artefacts as well as the corrected EEG will be presented.
URI: http://hdl.handle.net/10773/5828
ISSN: 0169-2607
publisher version/DOI: http://dx.doi.org/10.1016/j.cmpb.2006.06.003
source: Computer Methods and Programs in Biomedicine
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