A new method for mental workload classification with EEG connectivity maps
The classification of mental workload from electroencephalogram (EEG) signals is important for cognitive monitoring and adaptive human-machine interaction. In this work, we propose a new mental workload classification method that combines dDTF-derived EEG connectivity maps with a compact feature-learning pipeline. Mult...