Insights into user personality and learning styles through cross subject fNIRS classification

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

Abstract

There is limited literature on classifying user personality/learning style and other cross subject traits using brain activity patterns. In this paper we describe an experiment to classify a computer user's' personality type and learning style using their brain data acquired while they were conducting spatial/verbal tasks in front of a computer. The brain activity in the left and right hemispheres were measured by an fNIRS device and the resulting data was analyzed using the participant's personality/learning style as the label (Obtained through established survey instruments). We obtained promising results for all of the traits we strived to classify providing paths for future research into this area.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages181-189
Number of pages9
Volume8534 LNAI
ISBN (Print)9783319075266
DOIs
StatePublished - 2014
Event8th International Conference on Augmented Cognition, AC 2014 - Held as Part of 16th International Conference on Human-Computer Interaction, HCI International 2014 - Heraklion, Crete, Greece
Duration: Jun 22 2014Jun 27 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8534 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th International Conference on Augmented Cognition, AC 2014 - Held as Part of 16th International Conference on Human-Computer Interaction, HCI International 2014
CountryGreece
CityHeraklion, Crete
Period6/22/146/27/14

Keywords

  • Cross subject Classification
  • fNIRS
  • Learning styles
  • Personality
  • Visual/Verbal tasks

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Bandara, D., Hirshfield, L. M., & Velipasalar, S. (2014). Insights into user personality and learning styles through cross subject fNIRS classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8534 LNAI, pp. 181-189). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8534 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-07527-3_17