Research reading 072 / Actors / 2023
Using machine learning methods and EEG to discriminate aircraft pilot cognitive workload during flight
Source authors: Hamed Taheri Gorji; Nicholas Wilson; Jessica VanBree; Bradley Hoffmann; Thomas Petros; Kouhyar Tavakolian
Originally published in Scientific Reports · 2023
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Using machine learning methods and EEG to discriminate aircraft pilot cognitive workload during flight
Hamed Taheri Gorji; Nicholas Wilson; Jessica VanBree; Bradley Hoffmann; Thomas Petros; Kouhyar Tavakolian
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Open original source ↗ · CC BY 4.0
Original-text attribution: Hamed Taheri Gorji; Nicholas Wilson; Jessica VanBree; Bradley Hoffmann; Thomas Petros; Kouhyar Tavakolian. Verified full-text source · CC BY 4.0. Passages retain their wording. Original research authorship is unchanged.
A2 Workload and adaptive learning
Why read this for flight training?
Collects workload-related EEG during an instrument-training flight profile. Adds real-flight evidence to a literature otherwise dominated by simulators.
How to interpret the evidence
Ten pilots and model-validation choices constrain generalization to other pilots and aircraft.
Screening basis: Abstract screened. This annotation identifies relevance and limits; it does not replace appraisal of the original methods and findings.
Cite the original article
Hamed Taheri Gorji; Nicholas Wilson; Jessica VanBree; Bradley Hoffmann; Thomas Petros; Kouhyar Tavakolian (2023). Using machine learning methods and EEG to discriminate aircraft pilot cognitive workload during flight. Scientific Reports, 13(1), 2507. https://doi.org/10.1038/s41598-023-29647-0
Publication record
The original paper retains its published authors, venue and DOI. This journal’s reading guide was prepared with AI assistance under the editorial direction of Dr. Freedom Cheteni. The source authors are not credited as authors of this annotation. No new peer review or DOI is claimed for the guide.
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