Nikhil Panwar

Combining Spatio-Temporal Networks and Graph Attention Architectures for EEG-Based Workload Classification

Estimation of cognitive workload from EEG signals is a key challenge in advancing neuroergonomic systems and brain-computer interfaces (BCIs). A hybrid approach is presented, combining EEGNet and Graph Attention Networks (GATs) to effectively capture the intricate spatial and temporal dynamics withi…