Towards activity recognition of learners by simple electroencephalographs

Hiromichi Abe, Kensuke Baba, Shigeru Takano, Kazuaki Murakami

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

    3 Citations (Scopus)

    Abstract

    Understanding the states of learners at a lecture is expected to be useful for improving the quality of the lecture. This paper investigates the possibility of use of a simple electroencephalograph MindTune for activity recognition of a learner. The authors considered three kinds of activities for detecting states of a learner, and collected electroencephalography data with the activities by MindTune. Then, they applied K-nearest neighbor algorithm to the collected data, and the accuracy of the activity recognition was 58.2%. The result indicates a possibility of using MindTune for the activity recognition of learners.

    Original languageEnglish
    Title of host publicationProceedings of International Conference on Information Systems and Design of Communication, ISDOC 2014
    PublisherAssociation for Computing Machinery
    Pages161-164
    Number of pages4
    ISBN (Print)9781450327138
    DOIs
    Publication statusPublished - Jan 1 2014
    EventInternational Conference on Information Systems and Design of Communication, ISDOC 2014 - Lisbon, Portugal
    Duration: May 16 2014May 17 2014

    Other

    OtherInternational Conference on Information Systems and Design of Communication, ISDOC 2014
    CountryPortugal
    CityLisbon
    Period5/16/145/17/14

    All Science Journal Classification (ASJC) codes

    • Software
    • Human-Computer Interaction
    • Computer Vision and Pattern Recognition
    • Computer Networks and Communications

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