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Using Biometric Data to Measure and Predict Emotional Engagement of Video Games

Vazquez, J.; Abdelrahman, S.; Wasden, C.; Jardine, S.; Judd, C.; Davis, M.; Facelli, J. C.

2022-03-02 bioinformatics
10.1101/2022.02.28.482337 bioRxiv
Show abstract

Measurement and prediction of engagement in video games are very important because these are indicators to guide the development of game applications. Existing methods to predict game engagement are mostly based on subjective evaluations. This paper presents results correlating subjective and biometric data to show the potential of using biometric measures for assessment and prediction of engagement. Using three different games, we measured the biometric responses of participants and analyzed the responses using statistical and data mining methods. We compared the results with those obtained using subjective evaluations. Our results show that biometric measurements do correlate with subjective measures and better predict the self-reported engagement of a game.

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