Recognising situation awareness associated with different workloads using EEG and eye-tracking features in air traffic control tasks

Qinbiao Li, Kam K. H. Ng, Simon C. M. Yu, Cho Yin Yiu, Mengtao Lyu

Abstract: Highlights•A two-phase EEG-ET-based SA classification method is proposed.•A two-level hierarchical low SA recognition is established with workload consideration.•Unsupervised and supervised methods are used to extract EEG-ET features.•The SA-related neuro-physiological patterns with different workloads were revealed.•The optimal classifier accuracy under different classification levels is all acceptable.