ArticleFrontiers in neuroscience2023
EEG-based analysis for pilots' at-risk cognitive competency identification using RF-CNN algorithm.
Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- CubicPat: Investigations on the Mental Performance and Stress Detection Using EEG Signals.Diagnostics (Basel, Switzerland) · 2025Article
- Recognizing the situation awareness of forklift operators based on EEG techniques in a field experiment.Frontiers in neuroscience · 2024Article
- The Use of Quantitative Electroencephalography (QEEG) to Assess Post-COVID-19 Concentration Disorders in Professional Pilots: An Initial Concept.Brain sciences · 2023Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cognitive competency is an essential complement to the existing ship pilot screening system that should be focused on. Situation awareness (SA), as the cognitive foundation of unsafe behaviors, is susceptible to influencing piloting performance. To address this issue, this paper develops an identification model based on random forest- convolutional neural network (RF-CNN) method for detecting at-risk cognitive competency (i.e., low SA level) using wearable EEG signal acquisition technology. In the poor visibility scene, the pilots' SA levels were correlated with EEG frequency metrics in frontal (F) and central (C) regions, including α/β (
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