Across-subject estimation of 3-back task performance using EEG signals

Jinsoo Kim, Min Ki Kim, Christian Wallraven, Sung Phil Kim

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

    Abstract

    This study was aimed at estimating subjects' 3-back working memory task error rate using electroencephalogram (EEG) signals. Firstly, spatio-temporal band power features were selected based on statistical significance of across-subject correlation with the task error rate. Method-wise, ensemble network model was adopted where multiple artificial neural networks were trained independently and produced separate estimates to be later on aggregated to form a single estimated value. The task error rate of all subjects were estimated in a leave-one-out cross-validation scheme. While a simple linear method underperformed, the proposed model successfully obtained highly accurate estimates despite being restrained by very small sample size.

    Original languageEnglish
    Title of host publicationIEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIBCI 2014
    Subtitle of host publication2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages5-9
    Number of pages5
    ISBN (Electronic)9781479945443
    DOIs
    Publication statusPublished - 2015 Jan 12
    Event2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, CIBCI 2014 - Orlando, United States
    Duration: 2014 Dec 92014 Dec 12

    Publication series

    NameIEEE SSCI 2014 - 2014 IEEE Symposium Series on Computational Intelligence - CIBCI 2014: 2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, Proceedings

    Other

    Other2014 IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, CIBCI 2014
    Country/TerritoryUnited States
    CityOrlando
    Period14/12/914/12/12

    Bibliographical note

    Publisher Copyright:
    © 2014 IEEE.

    Keywords

    • Artificial neural network
    • Committee of machines
    • EEG
    • N-back task
    • Network ensemble

    ASJC Scopus subject areas

    • Computational Theory and Mathematics
    • Artificial Intelligence
    • Computer Science Applications

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