Novel BCI classification method using cross-channel-region CSP features

Yongkoo Park, Wonzoo Chung

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

    20 Citations (Scopus)

    Abstract

    In this paper, we explore locally generated cross-channel-region CSP features to improve motor imagery classification in EEG-based BCIs. We set several clustered sub-channel regions covering the entire measured channels and extract CSP features by cross-combining the sub-channel regions with each single channel. The features generated by this cross-channel-region combinations have regional information on sensor space for motor imagery and can be used to improve classification accuracy when fed to LS-SVM classifier. The performance improvement of the proposed algorithm is verified by simulations.

    Original languageEnglish
    Title of host publication2018 6th International Conference on Brain-Computer Interface, BCI 2018
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1-4
    Number of pages4
    ISBN (Electronic)9781538625743
    DOIs
    Publication statusPublished - 2018 Mar 9
    Event6th International Conference on Brain-Computer Interface, BCI 2018 - GangWon, Korea, Republic of
    Duration: 2018 Jan 152018 Jan 17

    Publication series

    Name2018 6th International Conference on Brain-Computer Interface, BCI 2018
    Volume2018-January

    Other

    Other6th International Conference on Brain-Computer Interface, BCI 2018
    Country/TerritoryKorea, Republic of
    CityGangWon
    Period18/1/1518/1/17

    Bibliographical note

    Funding Information:
    ACKNOWLEDGMENT This work was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (No. 2017-0-00451).

    Keywords

    • Brain-Computer Interfaces (BCIs)
    • Common Spatial Pattern (CSP)
    • cross-channel-region combinations
    • electroencephalography (EEG)

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Human-Computer Interaction
    • Behavioral Neuroscience

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