Teixeira, A. R. and Tome, A. M. and Lang, Elmar W. and Gruber, P. and da Silva, A. Martins (2006) Automatic removal of high-amplitude artefacts from single-channel electroencephalograms. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 83 (2). pp. 125-138. ISSN 0169-2607, 1872-7565
Full text not available from this repository. (Request a copy)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. (c) 2006 Elsevier Ireland Ltd. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | INDEPENDENT COMPONENT ANALYSIS; SINGULAR-SPECTRUM ANALYSIS; BLIND SOURCE SEPARATION; OCULAR ARTIFACTS; EYE-MOVEMENT; EEG; singular spectrum analysis (SSA); embedding; principal component analysis; electrooculogram (EOG); electroencephalogram (EEG) |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 08 Feb 2021 09:38 |
| Last Modified: | 08 Feb 2021 09:38 |
| URI: | https://pred.uni-regensburg.de/id/eprint/34196 |
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