Time-Varying Factors Model with Different Time-Scales for Studying Cybersickness

摘要

We have investigated cybersickness in terms of image motion vectors, visual characteristics, and the autonomic nervous regulation. We obtained the RR interval, respiration, and blood pressure time-series and estimated the low-frequency (LF) and high-frequency (HF) power components to determine the some sensation intervals. Then, we traced the time-series of the LF component backwards to find out the local minimum as the onset. An experiment consisted of five consecutive expo0sure sessions of the same first-person-view video image. In the unpleasant group from fifteen healthy young subjects, the LF/HF increased with respect to the number of trials and a significant difference was confined between two groups. The trigger points concentrated around the specific segments. Within the unpleasant group, eyes did not follow the camera motion around the trigger points. Accordingly, it recommends to monitor image motion vectors as a trigger factor and autonomic nervous regulation as an accumulation factor for studying cybersickness.