User Adaptive Locomotion Adjustments to Mitigate Motion Sickness in Virtual Reality

Motion sickness of VR users significantly impacts the level of comfort and enjoyment. Although current VR locomotion techniques offer a wide range of potential ways to navigate virtual worlds, they fail to prevent motion sickness equally effectively among individuals. To address these limitations, this study presents a user-adaptive locomotion adjustment system that proposes personalized movement mechanics based on information obtained from individual users. In this study, discussion types of user-adaptive locomotion adjustments are possible and consider alternative methods for creating such adaptations physiologically (measurements), interactively (user feedback mechanisms) or through machine learning. The study also elucidates the necessity of user studies and validation experiments for proper adaptation of locomotion, which is specific to each VR application. The findings shows that more personalized and comfortable VR experiences, ultimately making VR accessible and enjoyable for a broader audience.