Do not disturb: Psychophysiological correlates of boredom, flow and frustration during VR gaming

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Abstract

Since the technology behind virtual reality (VR) is evolving rapidly and the number of VR applications is growing every year, research on the user’s experience of being in the virtual environment itself and the methodologies to measure these experiences becomes highly important. In this study, we apply the methodology of measuring attentional allocation by means of a dual-task paradigm to the topic of VR gaming. The idea is to ask participants to react to oddball sounds (secondary task), pulling attention away from the primary task (the game). The behavioral (reaction time and accuracy) and neural response (P300 component) to these oddball sounds then tells us something about indirect attentional allocation to the game and possibly the experience of flow. In order to check the latter, we created experiences of boredom, flow and frustration by manipulating the mechanics of the game. In addition, we were interested in other psychophysiological correlates like brain oscillations and average heart rate and whether these differed between gaming with a regular and a VR set-up. Although we were not able to accurately induce feelings of boredom, flow and frustration and could not replicate previous studies showing increased reaction times for oddball sounds during flow, we did find a decreased P300 and more high-frequency brain oscillations in VR compared to regular gaming (indicating more attention to the game). Together, this suggests that psychophysiological measures are promising tools to quantify attentional allocation in VR, but more research is needed to clarify whether and how this translates to flow.

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Bombeke, K., Van Dongen, A., Durnez, W., Anzolin, A., Almgren, H., All, A., … Núñez Castellar, E. P. (2018). Do not disturb: Psychophysiological correlates of boredom, flow and frustration during VR gaming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10915 LNAI, pp. 101–119). Springer Verlag. https://doi.org/10.1007/978-3-319-91470-1_10

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