Using machine learning methods and EEG to discriminate aircraft pilot cognitive workload during flight.

ABSTRACT: Pilots of aircraft face varying degrees of cognitive workload even during normal flight operations. Periods of low cognitive workload may be followed by periods of high cognitive workload and vice versa. During such changing demands, there exists potential for increased error on behalf of the pilots due to periods of boredom or excessive cognitive task demand. To further understand cognitive workload in aviation, the present study involved collection of electroencephalogram (EEG) data from ten (10) collegiate aviation students in a live-flight environment in a single-engine aircraft. Each pilot possessed a Federal Aviation Administration (FAA) commercial pilot certificate and either FAA class I or class II medical certificate. Each pilot flew a standardized flight profile representing an a

SUBMITTER: Taheri Gorji H 

PROVIDER: S-EPMC9925430 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature