Prediction of eyestrain and motion sickness based on eye parameters during exposure to a visual flicker stimulus.
Abstract
This study investigates moving stimuli and the ensuing eye-movements in the genesis of motion sickness. When confronted with challenging visual stimulation, can oculomotor parameters reliably predict visually induced motion sickness (VIMS)? We used an eye-tracker and assessed subjective eyestrain to examine how these parameters vary as a function of specific characteristics of an abstract spatiotemporal flicker stimulus and whether they predict VIMS. Twenty-four participants viewed various flicker conditions presented on a desktop monitor, differing in frequency, spatial stimulus offset, and movement predictability. We recorded real-time self-reports of VIMS and eyestrain using a modified version of the Fast Motion Sickness Scale (FMS-Oculomotor). Higher flicker frequencies increased VIMS and eyestrain, whereas larger spatial offsets increased VIMS but not eyestrain. We applied linear mixed-effects models to the eye parameters to predict self-reported symptom severity. The models accounted for 69%-76% of variance in reported VIMS and eyestrain scores. Eye parameters varied in their ability to predict VIMS: fixation duration and number of saccades had predictive power in all conditions, whereas pupil diameter and number of fixations were only informative when stimulus motion was unpredictable. These findings highlight the potential of eye parameters as predictors of VIMS and eyestrain. We discuss implications for user interface design. Our findings emphasize that eye-tracking applications for VIMS detection must account for stimulus-specific calibration and individual baselines to achieve optimal predictive accuracy across varying visual environments.