Towards pre-emptive physiological error classification within airborne environments
McGuire, Niall and Greene, Jacob and Moshfeghi, Yashar; Oliver, Nuria and Shamma, David A. and Candello, Heloisa and Cesar, Pablo and Lopes, Pedro and Artizzu, Valentino and Draxler, Fiona and Lopez, Gustavo and Reinschluessel, Anke V. and Tong, Xin and Toups Dugas, Phoebe O., eds. (2026) Towards pre-emptive physiological error classification within airborne environments. In: CHI EA '26: Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery (ACM), ESP. ISBN 9798400722813 (https://doi.org/10.1145/3772363.3798722)
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Abstract
Human error contributes to 70-80% of aviation accidents despite technological advances, yet current safety systems remain reactive. We present the first empirical validation that neurophysiological signals can predict pilot errors up to 10 seconds in advance during operational flight. Through trials with nine commercial pilots, we collected synchronised EEG and eye-tracking data across laboratory, straight-and-level flight, and 2G manoeuvre conditions whilst participants performed multitasking scenarios. EEG-based classifiers achieved peak F1 scores of 88.7% in controlled environments and 82.0% during flight operations, with eye-tracking providing complementary predictive patterns. Results demonstrate that physiological error precursors remain detectable despite motion artefacts, electromagnetic interference, and gravitational stress. These findings establish the feasibility of pre-emptive error monitoring in operational aviation environments, providing a foundation for cognitive-aware cockpit systems that could enable proactive safety interventions before errors occur.
ORCID iDs
McGuire, Niall
ORCID: https://orcid.org/0009-0005-9738-047X, Greene, Jacob and Moshfeghi, Yashar
ORCID: https://orcid.org/0000-0003-4186-1088;
Oliver, Nuria, Shamma, David A., Candello, Heloisa, Cesar, Pablo, Lopes, Pedro, Artizzu, Valentino, Draxler, Fiona, Lopez, Gustavo, Reinschluessel, Anke V., Tong, Xin and Toups Dugas, Phoebe O.
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Item type: Book Section ID code: 96079 Dates: DateEvent13 April 2026Published12 January 2026AcceptedSubjects: Science > Mathematics > Electronic computers. Computer science Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 23 Apr 2026 09:13 Last modified: 01 Jun 2026 16:32 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/96079
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