Examining physiological parameters of mental workload in the cockpit: a multimethod approach.

Overview

1. Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR), Institut für Flugführung, Braunschweig, Germany
2. German Air Force Centre of Aerospace Medicine, Research & Development, Cologne, Germany
3. Department of Occupational Medicine, Faculty of Medicine, Otto von Guericke University Magdeburg, Magdeburg, Germany

Abstract

With increasing automation in the cockpit and the focus on adaptive assistance systems that provide tailored assistance to the pilots, it becomes increasingly relevant to monitor the pilots’ state. While many different psychophysiological measurement methods have been utilized in previous studies, they each have drawbacks and limitations that need to be overcome to provide a valid and reliable operator state assessment. In the present study, we investigated the assessment of mental workload (MWL) using a multimethod approach and combination of different physiological measurements (including neurophysiological, central and peripheral measures as well as eye-tracking) during a simulated flight task. A 60-minute simplified flight task was conducted with 14 commercial airline pilots in four difficulty levels, while their physiological, performance and self-report data were collected. Our analyses reveal that especially neurophysiological measures (electroencephalography [EEG], functional near-infrared spectroscopy [fNIRS]) and measures of heart rate (HR) and heart rate variability (HRV, specifically avNN) were able to differentiate the induced levels of MWL, and that different measures performed better in low and others in high MWL levels. Thus, we argue for a combination of physiological measures to assess MWL for future cockpit applications.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• osf:yxrke — at OSF; found in “Data availability statement”

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: Data collected by DLR are publicly available here: https://doi.org/10.17605/OSF.IO/YXRKE. Data collected by the German Air Force cannot be shared publicly because of institutional guidelines and restrictions. Data are available upon request from Stefan Sammito () for researchers who meet the criteria for access to confidential data.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, pages, dates, 6 authors, 6 keywords, 69 references.

Cite

This paper

Hamann, A., Kneffel, R. J., Cyrol, D., Rankova, E., Sammito, S., & Carstengerdes, N. (2026). Examining physiological parameters of mental workload in the cockpit: a multimethod approach. Frontiers in physiology, 17, 1893570. https://doi.org/10.3389/fphys.2026.1893570

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