Chang Li

An open-set learning framework for EEG-based sleep stage classification

Objective. Existing sleep stage classification methods generally rely on a closed set assumption. They assume all sleep categories are predefined, which overlooks unknown sleep patterns encountered in real world electroencephalogram (EEG) analysis. This study overcomes this constraint by identifying both known and unkn...