VR sickness measurement with EEG using DNN algorithm

Recently, VR technology is rapidly developing and attracting public attention. However, VR Sickness is a problem that is still not solved in the VR experience. The VR sickness is presumed to be caused by crosstalk between sensory and cognitive systems [1]. However, since there is no objective way to measure sensory and cognitive systems, it is difficult to measure VR sickness. In this paper, we collect EEG data while participants experience VR videos. We propose a Deep Neural Network (DNN) deep learning algorithm by measuring VR sickness through electroencephalogram (EEG) data. Experiments have been conducted to search for an appropriate EEG data preprocessing method and DNN structure suitable for the deep learning, and the accuracy of 99.12% is obtained in our study.