As many as 30% of people who try VR experiences feel some form of discomfort or cybersickness. Addressing this problem is very important if VR is to be more widely used by the general population.
In this project we explore if the onset of cybersickness can be detected by considering multiple physiological signals simultaneously from users in VR. We are particularly interested in physiological cues that can be collected from the current generation of VR HMDs, such as eye-gaze, and heart rate. We are also interested in exploring other physiological cues that could be available in the near future in VR HMDs, such as GSR and EEG.
Our early research has found that brain activity, as monitored by EEG, can be an effective predictor of the onset of cybersickness. Gaze and heartbeat are also useful measures. These results could be used by future developers to create VR experiences that react when people are about to feel sick, and so make VR more comfortable to use.Project Video(s):
Chang, E., Billinghurst, M., & Yoo, B. (2023). Brain activity during cybersickness: a scoping review. Virtual Reality, 1-25.
Chang, E., Kim, H.T. & Yoo, B. Identifying physiological correlates of cybersickness using heartbeat-evoked potential analysis. Virtual Reality 26, 1193–1205 (2022). https://doi.org/10.1007/s10055-021-00622-2
Eunhee Chang and others, Predicting cybersickness based on user’s gaze behaviors in HMD-based virtual reality, Journal of Computational Design and Engineering, Volume 8, Issue 2, April 2021, Pages 728–739, https://doi.org/10.1093/jcde/qwab010