Lightweight Cybersickness Detection based on User-Specific Eye and Head Tracking Data in Virtual Reality
The occurrence of cybersickness in virtual reality (VR) significantly impairs users' perception and sense of immersion. Therefore, timely detection of cybersickness and the application of appropriate intervention strategies are crucial for enhancing the user experience. However, existing cybersickness detection methods often suffer from issues such as poor detection reliability across different levels of cybersickness and unnecessary model complexity. Furthermore, while cybersickness exhibits significant inter-user variability, most existing approaches aggregate all data from users and lack user-specific solutions. In this paper, we investigate a lightweight approach for cybersickness det...
| Authors | Yijun Wang, Mihai Bâce, Maria Torres Vega |
|---|---|
| Primary category | cs.HC |
| Published | 18 April 2026 |
| Last updated at source | 18 April 2026 |
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