Abstract
The user base of the virtual reality (VR) medium is growing, and many of these users will experience cybersickness. Accounting for the vast interindividual variability in cybersickness forms a pivotal step in solving the issue. Most studies of cybersickness focus on a single factor (e.g., balance, sex, or vection), while other contributors are overlooked. Here, we characterize the complex relationship between cybersickness and several measures of sensorimotor processing. In a single session, we conducted a battery of tests of balance control, vection responses, and vestibular sensitivity to self-motion. Following this, we measured cybersickness after VR exposure. We constructed a principal components regression model using the measures of sensorimotor processing. The model significantly predicted 37% of the variability in cybersickness measures, with 16% of this variance being accounted for by a principal component that represented balance control measures. The strongest predictor was participants’ sway path length during vection, which was inversely related to cybersickness [r(28) = −0.53, P = 0.002] and uniquely accounted for 7.5% of the variance in cybersickness scores across participants. Vection strength reports and measures of vestibular sensitivity were not significant predictors of cybersickness. We discuss the possible role of sensory reweighting in cybersickness that is suggested by these results, and we identify other factors that may account for the remaining variance in cybersickness. The results reiterate that the relationship between balance control and cybersickness is anything but straightforward.NEW & NOTEWORTHY The advent of consumer virtual reality provides a pressing need for interventions that combat sickness in simulated environments (cybersickness). This research builds on multiple theories of cybersickness etiology to develop a predictive model that distinguishes between individuals who are/are not likely to experience cybersickness. In the future this approach can be adapted to provide virtual reality users with curated content recommendations based on more efficient measurements of sensorimotor processing.
Highlights
Virtual reality (VR) technology allows a user to experience a simulated environment through an array of sensory stimulation apparatuses (Hale and Stanney 2014)
The ability to predict susceptibility to CS based on a minimal set of measurements will enable the development of individualized recommendations for VR use, helping to prevent the nausea and discomfort that can occur rapidly and persist for several hours after VR use
The results indicate that the more a participant swayed in response to vection stimuli, the less CS they were likely to experience
Summary
Virtual reality (VR) technology allows a user to experience a simulated environment through an array of sensory stimulation apparatuses (Hale and Stanney 2014) Such arrays typically consist of electronic visual displays and sound devices, which can be updated in real time based on the input of manual controllers, inertial motion units, and (depending on the hardware) eye tracking. CS can be avoided entirely by terminating a VR session, some individuals experience severe and long-lasting nausea and discomfort following even brief exposures (Robillard and Bouchard 2007). This is an undesirable way for an individual to learn that they are susceptible to CS. There are significant challenges involved in falsifying these theories of motion sickness etiology, and experimental evidence often supports multiple theories (as discussed by, e.g., Ketelaar and Ellis 2000; Nooij et al 2017; Stoffregen and Riccio 1991; Weech et al 2018)
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