Blink To Win: Blink Patterns of Video Game Players Are Connected to Expertise

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    Abstract

    In this study, we analyzed the blinking behavior of players in a
    video game tournament. Our aim was to test whether spontaneous
    blink patterns differ across levels of expertise. We used blink rate,
    blink duration, blink frequency, and eyelid movements represented
    by the Eye Aspect Ratio (EAR) to train a machine learning classifier to discriminate between different levels of expertise. Classifier
    performance was highly influenced by features such as the mean,
    standard deviation and median EAR. Moreover, further analysis
    suggests that blinking rate and blink duration are likely to increase
    along with the level of expertise. We speculate this may be indicative of a reduction in cognitive load and lowered stress of expert
    players. In general, our results suggest that EAR and blink patterns
    can be used to identify different levels of expertise of video game
    players.
    Original languageEnglish
    Title of host publication17th International Conference on the Foundations of Digital Games (FDG)
    Place of PublicationAthens
    PublisherACM
    Number of pages7
    Edition17th
    DOIs
    Publication statusPublished - 2022

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