CyberSense: A Closed-Loop Framework to Detect Cybersickness Severity and Adaptively apply Reduction Techniques
Rifatul Islam, Samuel P. Ang, John Quarles · 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) · 2021
Researchers often collect subjective measurements before, after, and during the immersive experience to measure cybersickness severity. However, collecting data before and after the immersive experience does not provide a sufficiently granular understanding of cybersickness during the immersion. Thus, no preventive measures can be taken during immersion. This research presents CyberSense - an automated framework for cybersickness severity detection during immersion. The framework collects the users' physiological data at user-defined intervals. It uses a pre-trained neural network to detect cybersickness severity on the experience with a root mean square error of 2.61 and adaptively adjusts the cybersickness reduction techniques.