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Using Mean Pupil Diameter Change to Analyze Behavioral Performance in Multitasking Training Game.

He Qiao, Ayumi Tahara, Nonthaporn Nakphu

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |September 10, 2022
    PubMed
    Summary

    Virtual reality multitasking games reveal how pupil dilation indicates engagement. High performers process tasks actively, while low performers may ignore challenges, impacting training effectiveness.

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    Area of Science:

    • Cognitive Psychology
    • Human-Computer Interaction
    • Virtual Reality

    Background:

    • Multitasking performance is crucial in various domains.
    • Assessing cognitive load and engagement in training is challenging.
    • Virtual reality (VR) offers immersive environments for skill development.

    Purpose of the Study:

    • To investigate behavioral responses and cognitive effort in a VR multitasking game.
    • To correlate pupillary changes with task engagement and performance.
    • To evaluate the influence of game design on user behavior and training outcomes.

    Main Methods:

    • Designed a VR game with integrated Target-Tracking Task (TTT) and Color-Discrimination Task (CDT).
    • Recorded subjects' pupillary changes, specifically Mean Pupil Diameter Change (MPDC), during gameplay.

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  • Analyzed MPDC to differentiate between high and low performing groups.

    • Main Results:

    • High-performing groups exhibited pupil dilation in the post-event stage, indicating cognitive processing of the CDT.
    • Low-performing groups showed less pupil dilation, suggesting potential disengagement or ignoring of the CDT.
    • MPDC effectively mirrored behavioral differences in multitasking engagement.

    Conclusions:

    • Mean Pupil Diameter Change (MPDC) serves as a reliable indicator of cognitive effort and behavioral engagement in VR multitasking.
    • VR game design significantly influences user behavior and the potential effectiveness of training paradigms.
    • Understanding pupillary responses can optimize VR training game design for enhanced learning outcomes.