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arXiv · 2502.03419

Dynamic Cybersickness Mitigation via Adaptive FFR and FoV adjustments

Ananth N. Ramaseri-Chandra·Hassan Reza
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Abstract

This paper presents a novel adaptive Virtual Reality (VR) system that aims to mitigate cybersickness in immersive environments through dynamic, real-time adjustments. The system predicts cybersickness levels in real-time using a machine learning (ML) model trained on head tracking and kinematic data. The adaptive system adjusts foveated rendering (FFR) strength and field of view (FOV) to enhance user comfort. With a goal to balance usability with system performance, we believe our approach will optimize both user experience and performance. Adapting responsively to user needs, our work explores the potential of a machine learning-based feedback loop for user experience management, contributing to a user-centric VR system design.

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Ananth N. Ramaseri-Chandra, Hassan Reza. 2025-02-05. Dynamic Cybersickness Mitigation via Adaptive FFR and FoV adjustments. https://arxiv.org/abs/2502.03419

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