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Tech Papers 2018: This paper presents a machine-learning approach using physiological signals to automatically detect and predict VR sickness, showing promising results for continuous monitoring and mitigation.
Abstract
Virtual Reality (VR) sickness seems one of the main limitations to the large-scale adoption of VR technologies. This disturbance seems to induce physiological changes that affect the sympathetic and parasympathetic activities of the users. Thereby, it seems relevant to measure users’ physiological data in order to prevent and reduce VR sickness. This paper presents the results of an initial real-life experiment of VR sickness detection based on physiological data.
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