Investigating effects of different artefact types on motor imagery BCI

Laura Frolich, Irene Winkler, Klaus Robert Muller, Wojciech Samek

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

    18 Citations (Scopus)

    Abstract

    Artefacts in recordings of the electroencephalogram (EEG) are a common problem in Brain-Computer Interfaces (BCIs). Artefacts make it difficult to calibrate from training sessions, resulting in low test performance, or lead to artificially high performance when unintentionally used for BCI control. We investigate different artefacts' effects on motor-imagery based BCI relying on Common Spatial Patterns (CSP). Data stem from an 80-subject BCI study. We use the recently developed classifier IC-MARC to classify independent components of EEG data into neural and five classes of artefacts. We find that muscle, but not ocular, artefacts adversely affect BCI performance when all 119 EEG channels are used. Artefacts have little influence when using 48 centrally located EEG channels in a configuration previously found to be optimal.

    Original languageEnglish
    Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1942-1945
    Number of pages4
    ISBN (Electronic)9781424492718
    DOIs
    Publication statusPublished - 2015 Nov 4
    Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
    Duration: 2015 Aug 252015 Aug 29

    Publication series

    NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    Volume2015-November
    ISSN (Print)1557-170X

    Other

    Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
    Country/TerritoryItaly
    CityMilan
    Period15/8/2515/8/29

    Bibliographical note

    Publisher Copyright:
    © 2015 IEEE.

    ASJC Scopus subject areas

    • Signal Processing
    • Biomedical Engineering
    • Computer Vision and Pattern Recognition
    • Health Informatics

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