Abstract
Cybersickness is one of the notable discomforts associated with virtual reality(VR) applications. With the recent advancement of machine learning, we can train deep neural networks to detect cyber-sickness severity from the physiological and VR-image data. Prior researches found a correlation between physiological and VR-image data with cybersickness. In this study, I hypothesize to detect the onset severity of cybersickness. Finally, based on the severity level, automatically apply different cybersickness reduction techniques in real-time.