Robustness of mutual information to inter-subject variability for automatic artefact removal from EEG

N. Nicolaou, S. J. Nasuto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The externally recorded electroencephalogram (EEG) is contaminated with signals that do not originate from the brain, collectively known as artefacts. Thus, EEG signals must be cleaned prior to any further analysis. In particular, if the EEG is to be used in online applications such as Brain-Computer Interfaces (BCIs) the removal of artefacts must be performed in an automatic manner. This paper investigates the robustness of Mutual Information based features to inter-subject variability for use in an automatic artefact removal system. The system is based on the separation of EEG recordings into independent components using a temporal ICA method, RADICAL, and the utilisation of a Support Vector Machine for classification of the components into EEG and artefact signals. High accuracy and robustness to inter-subject variability is achieved.

Original languageEnglish
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages5991-5994
Number of pages4
Volume7 VOLS
Publication statusPublished - 1 Dec 2005
Externally publishedYes
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: 1 Sep 20054 Sep 2005

Conference

Conference2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
CountryChina
CityShanghai
Period1/09/054/09/05

Keywords

  • Automatic artefact removal
  • EEG
  • RADICAL
  • SVM
  • TDSEP
  • Temporal ICA

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    Nicolaou, N., & Nasuto, S. J. (2005). Robustness of mutual information to inter-subject variability for automatic artefact removal from EEG. In Proceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 (Vol. 7 VOLS, pp. 5991-5994). [1615856]