From Raw Data to Practical Application: EEG Parameters for Human Performance Studies in Air Traffic Control
María Zamarreño Suárez,
Juan Marín Martínez,
Francisco Pérez Moreno,
Raquel Delgado-Aguilera Jurado,
Patricia María López de Frutos,
Rosa María Arnaldo Valdés
Affiliations
María Zamarreño Suárez
Department of Aerospace Systems, Air Transport and Airports, School of Aerospace Engineering, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain
Juan Marín Martínez
Department of Aerospace Systems, Air Transport and Airports, School of Aerospace Engineering, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain
Francisco Pérez Moreno
Department of Aerospace Systems, Air Transport and Airports, School of Aerospace Engineering, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain
Raquel Delgado-Aguilera Jurado
Department of Aerospace Systems, Air Transport and Airports, School of Aerospace Engineering, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain
Patricia María López de Frutos
ATM Research and Development Reference Centre (CRIDA), 28022 Madrid, Spain
Rosa María Arnaldo Valdés
Department of Aerospace Systems, Air Transport and Airports, School of Aerospace Engineering, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain
The use of electroencephalography (EEG) techniques has many advantages in the study of human performance in air traffic control (ATC). At present, these are non-intrusive techniques that allow large volumes of data to be recorded on a continuous basis using wireless equipment. To achieve the most with these techniques, it is essential to establish appropriate EEG parameters with a clear understanding of the process followed to obtain them and their practical application. This study explains, step by step, the approach adopted to obtain six EEG parameters: excitement, stress, boredom, relaxation, engagement, and attention. It then explains all the steps involved in analysing the relationship between these parameters and two other parameters that characterise the state of the air traffic control sector during the development of real-time simulations (RTS): taskload and number of simultaneous aircraft. For this case study, the results showed the highest relationships for the engagement and attention parameters. In general, the results confirmed the potential of using these EEG parameters.