Monitoring Pilot's Mental Workload Using ERPs and Spectral Power with a Six-Dry-Electrode EEG System in Real Flight Conditions.

Frédéric Dehais,Sébastien Scannella,Fabien Lotte,Sarah Blum,Nicolas Drougard,Alban Duprès,Raphaëlle Roy

doi:10.3390/s19061324

Abstract

Recent technological progress has allowed the development of low-cost and highly portable brain sensors such as pre-amplified dry-electrodes to measure cognitive activity out of the laboratory. This technology opens promising perspectives to monitor the “brain at work” in complex real-life situations such as while operating aircraft. However, there is a need to benchmark these sensors in real operational conditions. We therefore designed a scenario in which twenty-two pilots equipped with a six-dry-electrode EEG system had to perform one low load and one high load traffic pattern along with a passive auditory oddball. In the low load condition, the participants were monitoring the flight handled by a flight instructor, whereas they were flying the aircraft in the high load condition. At the group level, statistical analyses disclosed higher P300 amplitude for the auditory target (Pz, P4 and Oz electrodes) along with higher alpha band power (Pz electrode), and higher theta band power (Oz electrode) in the low load condition as compared to the high load one. Single trial classification accuracy using both event-related potentials and event-related frequency features at the same time did not exceed chance level to discriminate the two load conditions. However, when considering only the frequency features computed over the continuous signal, classification accuracy reached around 70% on average. This study demonstrates the potential of dry-EEG to monitor cognition in a highly ecological and noisy environment, but also reveals that hardware improvement is still needed before it can be used for everyday flight operations.

Highlights

Operating aircraft is a challenging activity that takes place under a dynamic and uncertain environment [1]
This effect was due to higher P300 amplitude for the target sound in the low load compared to the high load condition on Pz, P4, and Oz electrodes (p < 0.001)—see Figure 4)
The vertical grey bars indicate when the P300 amplitude on the auditory target was statistically higher in the low load compared to the high load condition (p < 0.001)

Summary

Introduction

Operating aircraft is a challenging activity that takes place under a dynamic and uncertain environment [1]. Pilots are required to perform multiple tasks such as controlling the aircraft trajectory, monitoring the flight parameters, performing check-lists, communicating with air traffic controllers, identifying potential threats (collision, failures and bad weather conditions) and potentially adapting the flight plan. The management of these multiple tasks can drastically increase workload [2,3,4] that in return may have a deleterious effect on their performance. Sensors 2019, 19, 1324 errors is to implement a passive brain computer interface (pBCI) [11,12,13] to continuously monitor mental workload [14] and to dynamically adapt pilot-cockpit interaction [15]. Other studies reported increased beta [19]

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