The objective of the present research was to investigate an electroencephalography (EEG) brain-computer interface (BCI) for monitoring realistic variations in mental workload during virtual reality (VR) flight simulation. Many aviation accidents are related to pilot cognition and a mismatch between task demands and cognitive resources. Real-time neurophysiological monitoring offers an approach to identifying high-workload mental states by obtaining continuous, objective measurements without adding to the workload of the pilot. Workload was manipulated by varying navigational difficulty and communication tasks during VR flight simulation. EEG data collected during simulated flight was analyzed to evaluate performance of passive BCI for classification of workload level. BCI approaches were guided by EEG workload literature. A classification rate of 75.9% was obtained, with Alpha and Beta frequency bands being most informative. The results indicate that a passive EEG-BCI may be an effective strategy for monitoring workload and enhancing flight safety.
Benthem, K. V.,
& Herdman, C. M.
(2021). A Passive Electroencephalography Brain-Computer Interface Predicts Mental Workload During Flight Simulation. 43rd International Symposium on Aviation Psychology, 438-443.