Estimating cybersickness from virtual reality applications

Abstract

Cybersickness is a known issue in virtual reality affecting a notable percentage of the populations. However, predicting the level and incidence of cybersickness in new systems is difficult. Past publications were analyzed for their factors and resulting cybersickness scores. These factors were then used to develop three predictive models using demographics, software, and hardware factors. Using demographic information alone explained 44.2% of the adjusted variance in a linear model. Using hardware and software factors alone explained 55.3% of the adjusted variance in a linear model. Using demographics, software, and hardware factors did not use a linear model, but rather had an average residual error of 1.03. This residual error is an estimate of how far the predicted cybersickness score is from the actual score.