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      Estimating the sensorimotor components of cybersickness

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          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.

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          Most cited references107

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          Measures of postural steadiness: differences between healthy young and elderly adults.

          Measures of postural steadiness are used to characterize the dynamics of the postural control system associated with maintaining balance during quiet standing. The objective of this study was to evaluate the relative sensitivity of center-of-pressure (COP)-based measures to changes in postural steadiness related to age. A variety of time and frequency domain measures of postural steadiness were compared between a group of twenty healthy young adults (21-35 years) and a group of twenty healthy elderly adults (66-70 years) under both eyes-open and eyes-closed conditions. The measures that identified differences between the eyes-open and eyes-closed conditions in the young adult group were different than those that identified differences between the eye conditions in the elderly adult group. Mean velocity of the COP was the only measure that identified age-related changes in both eye conditions, and differences between eye conditions in both groups. The results of this study will be useful to researchers and clinicians using COP-based measures to evaluate postural steadiness.
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            A discussion of cybersickness in virtual environments

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              An ecological Theory of Motion Sickness and Postural Instability

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                Author and article information

                Journal
                J Neurophysiol
                J. Neurophysiol
                jn
                J Neurophysiol
                JN
                Journal of Neurophysiology
                American Physiological Society (Bethesda, MD )
                0022-3077
                1522-1598
                1 November 2018
                25 July 2018
                25 July 2018
                : 120
                : 5
                : 2201-2217
                Affiliations
                [1]Department of Kinesiology, University of Waterloo , Waterloo, Ontario, Canada
                Author notes
                Address for reprint requests and other correspondence: S. Weech, Dept. of Kinesiology, Univ. of Waterloo, Waterloo, ON, Canada N2L 3G1 (e-mail: sweech@ 123456uwaterloo.ca ).
                Author information
                https://orcid.org/0000-0003-2333-3505
                Article
                JN-00477-2018 JN-00477-2018
                10.1152/jn.00477.2018
                6295542
                30044672
                44422264-6488-480f-9e92-81c9f277dfb8
                Copyright © 2018 the American Physiological Society

                Licensed under Creative Commons Attribution CC-BY 4.0: © the American Physiological Society.

                History
                : 13 July 2018
                : 17 July 2018
                Funding
                Funded by: Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada) 10.13039/501100000038
                Award ID: RGPIN-05435-2014
                Funded by: Ontario Research Fund and Canadian Foundation for Innovation's John R. Evans Leaders Fund
                Award ID: 32618
                Funded by: Oculus Research
                Categories
                Research Article
                Sensory Processing

                Neurology
                balance control,perception,self-motion,vection,virtual reality
                Neurology
                balance control, perception, self-motion, vection, virtual reality

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