Is It Possible to Measure Real-Time VR Motion Sickness with EDA Wavelet Features?

Virtual reality (VR) has emerged as a more commercial mainstream, and the number of users complaining of VR motion sickness is increasing rapidly. As a result, many methods, physiological indicators: electrogastrography (EGG), heart rate (HR), temperature, electrodermal activity (EDA), subjective measurement methods, simulator sickness questionnaire (SSQ), virtual reality symptom questionnaire (VRSQ), fast motion sickness score (FMS), have been studied to quantify VR motion sickness. Consequently, this study attempted to track motion sickness using EDA (sweat). The study group consisted of ten female and ten male participants who have access to VR (average age: 21.2 years; standard deviation: 2.07 years) with no physical or visual health problems. The VR environment was designed by wearing a head-mounted display (HMD) through a simple operation method. Subjects wore an EDA sensor (Empatica E4) in a VR environment and were asked to respond to SSQ, VRSQ, and FMS questionnaires. For all items of FMS and SSQ (nausea, oculomotor, disorientation, and total) and Total of VRSQ, the coefficient of determination was high in the order of 1st trial > 2nd trial > Rest. Overall, the motion sickness score was rated the lowest during the rest period. The coefficient of determination of EDA (sweat) in rest was low in all except Disorientation in VRSQ. And VR motion sickness may have different symptoms complaining to the user depending on the VR environment. Hence, this study suggests that the EDA (sweat) signal may be suitable depending on the user’s immersion interval and the symptoms.