Investigation of independent components based EEG metrics for mental fatigue in simulated ATC task

Abstract

Changes in the cortical brain activity due to mental fatigue have to be assessed in task demanding operating environments for the purpose of safety. In this investigation, ten subjects performed a computer-simulated air traffic control (ATC) task, while electroencephalogram (EEG) data were collected. EEG data were decomposed into brain activity related independent components (ICs) using a group-level independent component analysis (gICA). Development of mental fatigue was examined at two different time windows by examining spectral powers from identified ICs and was evaluated against behavioral data. The present results suggest that, as the time on the task increases, significant changes in EEG spectral powers can be observed in identified ICs, which indicates the evolution of mental fatigue. Potential applications of such research include assessment of mental effectiveness of ATC operators who are involved in prolonged and demanding task assignments.