.png){kind=icon}
.png){kind=icon}
Return
Quantifying VR cybersickness using EEG
.png){kind=icon}
OA
AI
DOI：10.1007/s10055-021-00517-2.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Current techniques for characterizing cybersickness (visually induced motion sickness) in virtual environments rely on qualitative questionnaires. For interactive graphics to create visual experiences that enhance the illusion of presence while mitigating cybersickness, interactive measures are needed to characterize cybersickness. In this paper, we acquire EEG signals from participants as they experience vection-induced cybersickness and compare those signals to a baseline. Our study shows that there is a correlation between the participant-reported cybersickness (as measured by movements of a joystick) and brain EEG signals. Through independent component analysis, we separate those signals which are a result of cybersickness from other sources (such as eye blinks). Our user study finds that there is a highly correlative and statistically significant Delta- (1.0-4.0 Hz), Theta- (4.0-7.0 Hz), and Alpha-wave (7.0-13.0 Hz) increase associated with cybersickness in immersive virtual environments across participants. Establishing a strong correlation between cybersickness and EEG-measured brain activity provides us with the first step toward interactively characterizing and mitigating cybersickness in virtual environments.
Keywords:
Experimental methods
HMD
Visualization
Psychology
User-study
Perception
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.