Self-paced training on motor imagery-based BCI for minimal calibration time

Seon Min Kim, Min Ho Lee, Seong Whan Lee

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

    3 Citations (Scopus)

    Abstract

    Motor imagery (MI)-based brain-computer interface (BCI) allows users to control external devices using the brain signal patterns induced by the imagination of movements. Since these patterns have high variability between subjects and sessions, the BCI system necessarily requires 20-30 minutes for the calibration process each time the system is used. This time-consuming process requires a high level of the user's concentration; most users experience uncomfortable feelings such as tiredness, exhaustion, and loss of attention, which are symptoms of mental fatigue. In this paper, we introduce a self-paced training that terminates the calibration process within a few minutes. In this training paradigm, users perform MI tasks continuously without an inter-stimulus-interval (ISI). Also, we propose a data selection method to extract the most prominent features from the short calibration data by assuming the data distribution probabilistically and using the prior knowledge of event-related desynchronization (ERD) patterns. The results from 19 subjects indicate that the proposed method gained a comparable classification performance to the conventional method but with a much shorter calibration period (12 min/73.8%, 30 min/76.1%, respectively). In this regard, the proposed method could be of great benefit for real-world BCI applications by providing a quicker calibration process.

    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages2297-2301
    Number of pages5
    ISBN (Electronic)9781538616451
    DOIs
    Publication statusPublished - 2017 Nov 27
    Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
    Duration: 2017 Oct 52017 Oct 8

    Publication series

    Name2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
    Volume2017-January

    Other

    Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
    Country/TerritoryCanada
    CityBanff
    Period17/10/517/10/8

    Bibliographical note

    Funding Information:
    This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the “SW Starlab” (IITP-2015-1107) supervised by the IITP(Institute for Information & communications Technology Promotion).

    Funding Information:
    ACKNOWLEDGMENT This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the “SW Starlab” (IITP-2015-1107) supervised by the IITP(Institute for Information & communications Technology Promotion).

    Publisher Copyright:
    © 2017 IEEE.

    Keywords

    • Brain-computer interface (BCI)
    • Calibration time
    • Electroencephalography (EEG)
    • Motor imagery (MI)
    • Self-paced training

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Science Applications
    • Human-Computer Interaction
    • Control and Optimization

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