Towards activity recognition of learners by simple electroencephalographs

Hiromichi Abe, Kensuke Baba, Sigeru 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 - 2014
Externally publishedYes
EventInternational Conference on Information Systems and Design of Communication, ISDOC 2014 - Lisbon, Portugal
Duration: May 16 2014May 17 2014

Publication series

NameACM International Conference Proceeding Series

Conference

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

ASJC Scopus subject areas

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

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