Toward Adaptive VR Design: Physiological and Cognitive Predictors of Cybersickness in Serious Games
ABOUT
A study of cybersickness predictors in a VR fishery-management serious game built in Unreal Engine 5. We recorded HRV, GSR, and HR from 105 participants and collected post-session cognitive load and duration ratings. Hierarchical regression on 94 complete cases explained 35.8% of the cybersickness variance, with duration dominating (β = 0.87), then cognitive load (β = 0.52) and GSR (β = 0.54). The results point to duration, cognitive load, and GSR as candidate inputs for adaptive VR comfort systems in serious games.
PUBLICATION INFO
AUTHORS
F. Annisa Damastuti, K. Firmansyah, Y. M. Arif, R. Yuniar Hakkun, M. Hariadi
ABSTRACT
Multivariate cybersickness prediction in a free-play VR serious game (UE5 fishery-management sim) using physiological signals, cognitive load, and session duration.
RESULTS
R² = 0.358 on 94 cases. Duration (β = 0.87), cognitive load (β = 0.52), and GSR (β = 0.54) emerged as the strongest predictors — candidate inputs for adaptive VR comfort systems.