147735 20260217205609.0 doi 10.1145/3687929 sideral 141176 ART-2024-141176 eng Tovar, David Identifying behavioral correlates to visual discomfort 2024 Access copy available to the general public Unrestricted Outside of self-report surveys, there are no proven, reliable methods to quantify visual discomfort or visually induced motion sickness symptoms when using head-mounted displays. While valuable tools, self-report surveys suffer from potential biases and low sensitivity due to variability in how respondents may assess and report their experience. Consequently, extreme visual-vestibular conflicts are generally used to induce discomfort symptoms large enough to measure reliably with surveys (e.g., stationary participants riding virtual roller coasters). An emerging area of research is the prediction of discomfort survey results from physiological and behavioral markers. However, the signals derived from experimental paradigms that are explicitly designed to be uncomfortable may not generalize to more naturalistic experiences where comfort is prioritized. In this work we introduce a custom VR headset designed to introduce significant near-eye optical distortion (i.e., pupil swim) to induce visual discomfort during more typical VR experiences. We evaluate visual comfort in our headset while users play the popular VR title Job Simulator and show that eye-tracked dynamic distortion correction improves visual comfort in a multi-session, within-subjects user study. We additionally use representational similarity analysis to highlight changes in head and gaze behavior that are potentially more sensitive to visual discomfort than surveys. info:eu-repo/grantAgreement/ES/AEI/PID2022-141539NB-I00 info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 9.5 2024 COMPUTER SCIENCE, SOFTWARE ENGINEERING 5 / 129 = 0.039 2024 Q1 T1 2.965 2024 Computer Graphics and Computer-Aided Design 2024 Q1 17.7 2024 info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Wilmott, James Wu, Xiuyun Martin, Daniel Universidad de Zaragoza (orcid)0000-0002-0073-6398 Proulx, Michael Lindberg, Dave Zhao, Yang Mercier, Olivier Guan, Phillip 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 43, 6 (2024), 1-10 ACM trans. graph. ACM TRANSACTIONS ON GRAPHICS 0730-0301 1671433 http://zaguan.unizar.es/record/147735/files/texto_completo.pdf Postprint 2436175 http://zaguan.unizar.es/record/147735/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:147735 articulos driver 2026-02-17-20:48:21 ARTICLE