Subjective and Objective Assessment of the Impact of Stress and Mental Workload on Cybersickness During Virtual Reality Training

Abstract: Cybersickness is an issue in immersive virtual reality (VR), akin to motion and simulator sickness, resulting in symptoms such as nausea, dizziness, and eye strain. Cybersickness has been shown to affect a significant portion of VR users. In training scenarios involving demanding tasks (e.g., for first responders' training), however, reports of cybersickness symptoms are higher than those for the average user. It is hypothesized that the stress and mental workload generated by these scenarios may be the cause for this increased propensity for cybersickness. In this study, we investigate the impact of stress alone, mental workload alone, and their combined impact on cybersickness levels. The levels of stress and mental workload are manipulated while participants perform a driving simulator task. In the high mental workload condition, the driver has to keep an eye on the road while driving from one location to another, as well as monitor and count the number of pedestrians wearing a certain colour shirt. In the high stress condition, traffic conditions become heavy, background noise increases, and sudden breaks are needed to avoid accidents (e.g., from a ball rolling into the road to a car suddenly changing lanes). Lastly, the combined condition contains all the elements of the previous two conditions. In all cases, a baseline driving period is present (without stress or workload) and is used for comparisons within each subject. Both self-report and neurophysiological measurements are used to gauge the impact of these three conditions on cybersickness. Self-report questionnaires are used to assess stress (DASS-21), mental workload (NASA-TLX), and cybersickness symptoms (SSQ) at several instances during the experiment. In turn, an instrumented Meta Quest 3 VR headset is used equipped with 16 electroencephalography (EEG) and electro-oculography (EOG) sensors, while wearable devices are used to monitor photoplethysmography (PPG), electrocardiography (ECG), and respiration signals. These neurophysiological signals are used to continuously extract measures of mental workload, stress, and other cognitive/affective states almost in real-time. In this paper, we describe the experimental setup, the instrumented headset, the EEG and biosignal metrics that are computed, and provide preliminary subjective and objective findings based on the first 12 participants (four per condition). The study is ongoing and aims to collect data from 60 participants (20 per condition). It is hoped that these preliminary insights will help the research community refine VR training protocols, making them more comfortable and effective for students.

Keywords: Cybersickness, virtual reality, stress, mental workload, VR training, electroencephalography, biosensors

DOI: 10.54941/ahfe1006348

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