From Micro to Meso: A Data-Driven Mesoscopic Region Division Method Based on Functional Connectivity for EEG-based Driver Fatigue Detection.

The integration of EEG signals and deep learning methods is emerging as an effective approach for brain fatigue detection, particularly utilizing Graph Neural Networks(GNNs) that excel in capturing complex electrode relationships. A significant challenge within GNNs is the construction of an effective adjacency matrix that enhances spatial information learning. Concurrently, electrode aggregation in EEG has emerged as a pivotal area of research.