Abstract
Cognitive workload discrimination of pilots during flights can contribute to flight safety by preventing mental overloading of the aircraft crew. Research has been conducted to study the cognitive workload of pilots in flight simulation task. The estimation of the cortical connectivity is a critical step in mental workload assessment. Therefore, we adopted a novel, parameter-free method of evaluating the cortical connectivity, named Generalized Measure of Association (GMA), to assess and discriminate the mental workload of pilots using the Multi-Attribute Task Battery (MATB) flight simulation platform. A modified version of GMA (Time Series GMA) is applied on the pre-processed EEG time series recorded from eight subjects during the MATB experiment. Frobenius Norm is used to calculate the Euclidean distances between different TGMA series in order to assess the discriminability of the cognitive workloads. The results have shown clear distinction between the mean values of the inter-task and intra-task Euclidean distance series of TGMA matrices, but statistical significance is still lacking due to the relatively large standard deviations.
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Dai, Z., PrÃncipe, J.C., Bezerianos, A., Thakor, N.V. (2015). Cognitive Workload Discrimination in Flight Simulation Task Using a Generalized Measure of Association. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9491. Springer, Cham. https://doi.org/10.1007/978-3-319-26555-1_78
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DOI: https://doi.org/10.1007/978-3-319-26555-1_78
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