AI & ML
Slide to Report: Continuous Reporting Symptom-Specific Cybersickness in VR
arXiv cs.HC0 views
arXiv:2611.07345v1 Announce Type: new Abstract: Cybersickness is often assessed during VR exposure through discrete overall sickness, which cannot capture specific symptoms or their changes over time. Post-exposure questionnaires such as the Simulator Sickness Questionnaire provide symptom-specific measures but cannot be collected during immersion. We investigate whether separating cybersickness into three symptom-specific dimensions -- nausea, oculomotor discomfort, and disorientation -- during immersion provides more informative continuous measurements. We conducted a between-subjects study with 52 participants in a VR-rollercoaster, comparing a three-slider interface with a single-slider interface. Concurrently, participants also completed an auditory Simon task to measure attention. We additionally collected multimodal set of physiological signals, including GSR, ECG, PPG, eye and head tracking. Results show that each slider correlated most strongly with its corresponding SSQ subscale, whereas the single slider correlated with all SSQ subscales. Using three sliders did not significantly affect usability, workload, or attention. We publicly release the multimodal dataset to support future cybersickness research.
Source:https://arxiv.org/abs/2611.07345PreviousVector alignment in matrix Lie groupsNextBreaking the Modality Barrier: Multimodal Fusion With Missing Modalities for Cybersickness Prediction
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