Intelligent Virtual Platform for Real-time Cybersickness Detection and Adaptation

Abstract

This paper is a novel research endeavor focused on addressing cybersickness in virtual reality (VR) experiences. Traditional approaches to cybersickness prediction and detection rely on generalized artificial intelligence models and extensive data collection. However, there has been a lack of research exploring user-specific intelligence. This paper introduces an intelligent platform designed to adapt to individual users in real-time for cybersickness detection. By dynamically adjusting its behavior and interactions, this platform aims to mitigate cybersickness and enhance the VR user experience. The platform’s effectiveness was evaluated using physiological data, including electrodermal activity (EDA) and eye movement signals. The results demonstrated the efficacy of our system in reducing cybersickness symptoms.