Evaluating User Experience in a Selection Based Brain-Computer Interface Game: A Comparative Study

Hayrettin Gürkök, Gido Hakvoort, Mannes Poel

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    11 Citations (Scopus)


    In human-computer interaction, it is important to offer the users correct modalities for particular tasks and situations. Unless the user has the suitable modality for a task, neither task performance nor user experience can be optimised. The aim of this study is to assess the appropriateness of using a steady-state visually evoked potential based brain-computer interface (BCI) for selection tasks in a computer game. In an experiment participants evaluated a BCI control and a comparable automatic speech recogniser (ASR) control in terms of workload, usability and engagement. The results showed that although BCI was a satisfactory modality in completing selection tasks, its use in our game was not engaging for the player. In our particular setup, ASR control appeared to be a better alternative to BCI control.
    Original languageUndefined
    Title of host publicationProceedings of the 10th International Conference on Entertainment Computing (ICEC 2011)
    EditorsJunia Coutinho Anacleto, Sidney Fels, Nicholas Graham, Bill Kapralos, Magy Saif El-Nasr, Kevin Stanley
    Place of PublicationBerlin
    Number of pages12
    ISBN (Print)978-3-642-24499-5
    Publication statusPublished - Oct 2011
    Event10th International Conference on Entertainment Computing, ICEC 2011 - Vancouver, Canada
    Duration: 5 Oct 20118 Oct 2011
    Conference number: 10

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference10th International Conference on Entertainment Computing, ICEC 2011
    Abbreviated titleICEC


    • IR-78538
    • METIS-281569
    • Engagement
    • Games
    • Brain-Computer Interface
    • steady-state visually evoked potential
    • EWI-20813
    • Usability
    • Workload
    • HMI-SLT: Speech and Language Technology
    • HMI-CI: Computational Intelligence
    • User Experience

    Cite this