Task difficulty and physiological measures of mental workload in air traffic control: a scoping review
DOI: 10.1080/00140139.2021.2016998
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Summary
This scoping review synthesizes empirical research on the relationship between task difficulty and physiological measures of mental workload (MWL) in air traffic control (ATC). The study was motivated by the increasing traffic density in aviation and the subsequent introduction of innovative technologies, which require accurate MWL assessment for validation. While performance and subjective measures are common, physiological measures offer continuous, high-temporal-resolution data suitable for analyzing dynamic cognitive states. The authors aimed to provide a systematic overview of how physiological indicators correlate with task difficulty, addressing a gap left by previous narrative reviews. The researchers conducted a systematic search following PRISMA-ScR guidelines, identifying 39 peer-reviewed publications reporting 41 studies. Eligibility criteria required empirical research involving ATC tasks (real-world or simulation), examination of varying task difficulty levels, and the use of at least one physiological measure. The final sample comprised seven field studies and 34 simulation studies. Data were charted to analyze variables used to manipulate or assess task difficulty, measures of performance and MWL, and the observed relationships between these factors. The review focused primarily on physiological measures, including brain activity (EEG, fNIR), heart rate, eye movements, and other autonomic indicators, while also noting subjective and objective performance metrics where reported. The review found that the number of aircraft was the predominant variable used to operationalize task difficulty, appearing in 32 of the 41 studies, often in isolation or combined with factors like communication volume or conflict frequency. Physiological measures were widely utilized, with brain measures (EEG and fNIR) and heart rate being the most common. Positive relations between task difficulty and physiological MWL measures were observed most frequently, indicating that these metrics effectively reflect increased workload. However, the authors identified significant methodological limitations, particularly poor descriptions of experimental settings. Many studies lacked detailed information regarding sector dimensions, aircraft types, and specific task actions, hindering comparability and the potential for dynamic, interactive analyses. Additionally, field studies rarely assessed direct ATC performance due to the infrequency of errors, whereas simulation studies frequently used performance metrics. The significance of this review lies in its confirmation that physiological measures, particularly EEG and heart rate, are valid indicators of MWL in ATC contexts. However, the findings highlight a critical need for standardized and precise reporting of experimental parameters. To advance the field toward more dynamic and interactive analyses, future research must provide detailed descriptions of task scenarios and operationalize task difficulty with greater nuance than simple aircraft counts. This improved rigor will facilitate better comparisons across studies and support the development of real-time MWL monitoring systems for evaluating new ATC technologies.
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-08-09 |
| archive | success | unpaywall | — | — | 2 | 2026-08-09 |
| extract | success | cached | — | — | 3 | 2026-08-10 |
| clean | success | clean | — | — | 1 | 2026-08-09 |
| chunk | success | chunk | — | — | 1 | 2026-08-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-08-09 |
| enrich | success | semantic_scholar | — | — | 1 | 2026-08-09 |
| promote | success | — | — | — | 1 | 2026-08-09 |
| summarize | success | llm | qwen3.6-27b-nvidia | summ-v5 | 2 | 2026-08-10 |
| tag | success | vector_similarity | — | — | 10 | 2026-08-11 |
| verify | success | — | — | — | 2 | 2026-08-10 |
Summary generated by qwen3.6-27b-nvidia on 2026-08-10; verification: verified.
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Information type
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- Empirical Findings: physiological data, self report data
- Theoretical Contribution: theory or model