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Category: Project

Description: Experiences of virtual reality (VR) can easily break if the method of evaluating subjective user states is intrusive. Behavioral measures are increasingly used to avoid this problem. One such measure is eye tracking, which recently became more standard in VR, and is often used for content-dependent analyses. This research is an endeavor to utilize content-independent eye metrics, such as pupil size and blinks, for identifying mental load in VR users. We generated mental load independently from visuals through auditory stimuli. We also took steps towards quantifying the phenomenon of not focusing exactly on (virtual) surfaces by proposing an eye metric called focus offset. In the experiment, VR-experienced participants listened to two native and two foreign language stimuli inside a virtual phone booth. The results show that with mental load, mean and variance of pupil size increased. To a lesser extent, mental load led to fewer fixations, less voluntary gazing at distracting content, and a larger focus offset as if looking through surfaces. These results are in agreement with previous studies. Overall, we encourage further research on content-independent eye metrics, hoping future hardware and algorithms to further increase tracking stability.