Multi-view Fused Detection of Simulator Sickness Based on Deep Generalized Canonical Correlation Analysis
Yiquan Shang, Dongsu Wu, Dawei Chen, Jinwei Zhang · 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology (ICCASIT) · 2022
Simulator sickness is a general malaise induced by virtual reality equipment such as simulators. Its symptoms include visual fatigue, disorientation and nausea, which seriously affect the training effect of simulators and the experience of using virtual reality equipment. Current machine learning methods for assessing simulator sickness cannot reasonably utilize the potential correlation between data features. In this paper, we use deep generalized canonical correlation analysis (DGCCA) to fuse features from different physiological data, and classify the fused features using machine learning. It was validated on public datasets with good results.