Abstract
AbstractThe user base of the virtual reality (VR) medium is growing, and many of these users will experience cybersickness. Accounting for the vast inter-individual variability in cybersickness forms a pivotal step in solving the issue. Most studies of cybersickness focus on a single factor (e.g., balance, sex, vection), while other contributors are overlooked. Here, we characterize the complex relationship between cybersickness and several indices of sensorimotor processing. In a single session, we conducted a battery of tests of balance control, vection responses, and vestibular sensitivity to self-motion. A principal components regression model, primarily composed of balance control measures during vection, significantly predicted 37% of the variability in cybersickness measures. We observed strong, inverse associations between measures of sway and cybersickness. The results reiterate that the relationship between balance control and cybersickness is anything but straightforward. We discuss other factors that may account for the remaining variance in cybersickness.
Publisher
Cold Spring Harbor Laboratory
Cited by
2 articles.
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1. Virtual reality sickness detection: an approach based on physiological signals and machine learning;2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR);2020-11
2. User experience problems in immersive virtual environments;Proceedings of the XX International Conference on Human Computer Interaction;2019-06-25