Adaptive Automation triggered by EEG-based mental workload index: a passive Brain-Computer Interface application in realistic Air Traffic Control environment

Adaptive Automation triggered by EEG-based mental workload index: a passive Brain-Computer Interface application in realistic Air Traffic Control environment

Adaptive Automation (AA) is a promising approach to keep the task workload demand within appropriate levels in order to avoid both the under- and overload conditions, hence enhancing the overall performance and safety of the human-machine system. The main issue on the use of AA is how to trigger the...

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Bibliographic Details
Main Authors: Pietro Aricò, Gianluca Borghini, Gianluca Di Flumeri, Alfredo Colosimo, Stefano Bonelli, Alessia Golfetti, Simone Pozzi, Jean Paul Imbert, Géraud Granger, Railane Benhacene, Fabio Babiloni
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-10-01
Series:Frontiers in Human Neuroscience
Subjects:
machine learning
human factors
electroencephalogram (EEG)
Mental Workload
human machine interaction
Air traffic management (ATM)
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnhum.2016.00539/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fnhum.2016.00539/full

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