Investigation of Relationship Between EEG Theta Power and Mental Workload in Air Traffic Control Simulation

Abstract

Introduction: Air traffic control is a very complex process, including multiple human-machine interactions. Human mental workload plays an important role in this process. Nowadays, electroencephalography indexes are considered as new indicators in the field of assessment of mental workload. The purpose of the present study was to investigate the relationship between EEG theta power and mental workload in air traffic control simulation. Material and Methods: Fourteen air traffic controllers participated in this study. Controllers carried out two scenarios, including low and high workload, based on task load factors in an air traffic control simulator. Mental workload was assessed in these two scenarios by the NASA-TLX questionnaire. EEG signals were continuously recorded during air traffic control tasks. Afterward, absolute theta power was extracted from participants’ EEG using Fast Fourier Transform (FFT) by the MATLAB software and was compared with each other in terms of high and low workload. Results: The results showed a significant relationship in absolute theta power during low and high workload scenarios in all regions of the brain (p < 0.05). Absolute theta power increased primarily in the frontal region during the high workload scenario. Also, there was a significant increase in the relationship between work experience and absolute theta power at the F3 region during the high workload scenario (P=0.021, r=0.607). Conclusion: Absolute theta power provides a good parameter to assess mental workload at different levels of air traffic control tasks. Therefore, it can be used as a tool for the design of human-machine complex systems.

Keywords

• mental workload
• electroencephalography (eeg)
• physiological measures
• absolute theta power
• air traffic control