Neurophysiological Vigilance Characterisation and Assessment: Laboratory and Realistic Validations Involving Professional Air Traffic Controllers
archive: archived pipeline: cataloged verified
Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)
Summary
This study addresses the critical safety issue of vigilance degradation in Air Traffic Controllers (ATCOs), particularly in high-automation environments where the "out-of-the-loop" (OOTL) phenomenon can lead to performance failures. The authors aimed to characterize and assess vigilance levels using electroencephalographic (EEG) measures, validating neurophysiological markers in both controlled laboratory settings and realistic operational environments. The research sought to determine if EEG features identified in the lab could accurately discriminate vigilance changes in professional ATCOs and to identify minimal electrode configurations for practical monitoring. The study employed a two-phase experimental design. Experiment 1 involved 13 healthy students in a laboratory setting performing the Psychomotor Vigilance Task (PVT), a standard protocol for inducing vigilance decrements. High-resolution EEG signals were recorded via 61 channels, and spectral analysis was conducted on individualized frequency bands (theta, alpha, beta, gamma) derived from each participant’s individual alpha frequency. Experiment 2 involved 10 professional ATCOs (selected from a pool of 14) operating in a realistic Air Traffic Management simulator using real traffic data from Munich Airport. ATCOs performed 45-minute scenarios under two conditions: a fully automated "Baseline" condition designed to induce monotony and vigilance loss, and an adaptive "Solution" condition where automation levels adjusted based on real-time EEG feedback. The results demonstrated a significant correlation between vigilance reduction and performance decrement in both settings. Crucially, the neurophysiological features identified in the laboratory were consistent with those observed in the realistic ATM environment, confirming the ecological validity of the findings. Machine learning models, specifically stepwise linear discriminant analysis, were able to classify vigilance states with high accuracy (up to 84%) using the full EEG channel configuration. Furthermore, the study successfully identified a reduced two-channel EEG configuration that maintained high classification accuracy with only a slight reduction in performance compared to the full setup. This indicates that robust vigilance monitoring can be achieved with minimal hardware intrusion. The significance of this work lies in its validation of EEG-based vigilance monitoring as a viable tool for preventing OOTL incidents in high-stakes operational contexts. By demonstrating that laboratory-derived biomarkers translate effectively to real-world professional settings, the study supports the development of non-invasive, real-time monitoring systems for ATCOs. The identification of a minimal two-channel configuration facilitates the practical implementation of such systems, offering a pathway to enhance safety in aviation and other automation-heavy industries by objectively detecting and mitigating vigilance failures before they result in critical errors.
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-10 |
| archive | success | openalex | — | — | 5 | 2026-06-25 |
| extract | success | cached | — | — | 2 | 2026-06-25 |
| clean | success | clean | — | — | 1 | 2026-06-11 |
| chunk | success | chunk | — | — | 1 | 2026-06-11 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-11 |
| promote | success | — | — | — | 1 | 2026-06-10 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-25 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-25; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.
Information type
What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).
- Empirical Findings: physiological data