A multimodal visual fatigue assessment model based on back propagation neural network and XGBoost

Lixiu Jia, Lixin Jia, Jian Zhao, Lihang Feng, Xiaohua Huang

Abstract: Highlights•Subjective questionnaire, ophthalmological parameters, electroencephalogram (EEG) signals, electrocardiogram (ECG) signals, and eye-tracking parameters can distinguish visual fatigue caused by prolonged viewing 2D and 3D display.•A visual fatigue assessment model utilizing a backpropagation neural network (BPNN) and XGBoost was introduced.•The necessity of multimodal modeling by increasing multimodal parameters was verified.•Feature importance in assessing visual fatigue was analyzed.