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• W3048367647 abstract "This study presents the integration of a passive brain computer interface (pBCI) and cognitive modelling as a method to trace pilots’ perception and processing of auditory alerts and messages during operations. Missing alerts on the flight deck can result in out-of-the-loop problems that can lead to accidents. By tracing pilots’ perception and responses to alerts, cognitive assistance can be provided based on individual needs to ensure they maintain adequate situation awareness. Data from 24 participating aircrew in a simulated flight study that included multiple alerts and air traffic control messages in single pilot setup are presented. A classifier was trained to identify pilots’ neurophysiological reactions to alerts and messages from participants’ electroencephalogram (EEG). A neuroadaptive ACT-R model using EEG data was compared to a conventional normative model regarding accuracy in representing individual pilots. Results show that passive BCI can distinguish between alerts that are processed by the pilot as task-relevant or irrelevant in the cockpit based on the recorded EEG. The neuroadaptive model’s integration of this data resulted in significantly higher performance in representing individual pilots’ responses to alerts and messages. We conclude that neuroadaptive technology allows for implicit measurement and tracing of pilots’ perception and processing of alerts on the flight deck. Careful handling of uncertainties inherent to passive BCI and cognitive modeling shows how the representation of pilot cognitive states can be improved iteratively for providing assistance." @default.
• W3048367647 created "2020-08-18" @default.
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• W3048367647 date "2020-08-11" @default.
• W3048367647 modified "2023-10-02" @default.
• W3048367647 title "Tracing Pilots’ Situation Assessment by Neuroadaptive Cognitive Modeling" @default.
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• W3048367647 doi "https://doi.org/10.3389/fnins.2020.00795" @default.
• W3048367647 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7431601" @default.
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