Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Detecting boredom from eye gaze and EEG
Department of Life Media, Ajou University.
Department of Computer Engineering, Ajou University.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0001-5966-992x
2018 (English)In: Biomedical Signal Processing and Control, ISSN 1746-8094, E-ISSN 1746-8108, Vol. 46, p. 302-313Article in journal (Refereed) Published
Abstract [en]

The recent proliferation of affordable physiological sensors has boosted research and development efforts of emotion-aware systems. Boredom has received relatively little attention as a target emotion, and we identified a lack of research on the relationship between eye gaze and electroencephalogram (EEG) when people feel bored. To investigate this matter, we first conducted a background study on boredom and its detection by physiological methods. Then, we designed and executed an experiment that uses a video stimulus – specifically designed for this experiment, yet general enough for other boredom research – with an eye tracker and EEG sensor to elicit and detect boredom. Moreover, a questionnaire was used to confirm the existence of boredom. The experiment was based on a hypothesis that participants may feel bored when their gaze deviates from an expected area of interest, thus indicating loss of attention. The results of the experiment indicated correlations between eye gaze data and EEG data with all participants (N = 13) when they felt bored. This study can be useful for researchers who have interest in developing boredom-aware systems.

Place, publisher, year, edition, pages
Elsevier, 2018. Vol. 46, p. 302-313
National Category
Human Computer Interaction Computer Sciences Media and Communication Technology
Research subject
Pervasive Mobile Computing
Identifiers
URN: urn:nbn:se:ltu:diva-70388DOI: 10.1016/j.bspc.2018.05.034ISI: 000447109800032Scopus ID: 2-s2.0-85051400618OAI: oai:DiVA.org:ltu-70388DiVA, id: diva2:1238900
Note

Validerad;2018;Nivå 2;2018-08-15 (andbra)

Available from: 2018-08-15 Created: 2018-08-15 Last updated: 2018-11-22Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Laine, Teemu H.

Search in DiVA

By author/editor
Laine, Teemu H.
By organisation
Computer Science
In the same journal
Biomedical Signal Processing and Control
Human Computer InteractionComputer SciencesMedia and Communication Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 185 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf