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A review of physiological measures for mental workload assessment in aviation

A state-of-the-art review of mental workload physiological assessment methods in human-machine interaction analysis

Part of: The AJ Special Rotorcraft Collection

Published online by Cambridge University Press:  25 October 2023

G. Luzzani Open the ORCID record for G. Luzzani [Opens in a new window] ,
I. Buraioli Open the ORCID record for I. Buraioli [Opens in a new window] ,
D. Demarchi Open the ORCID record for D. Demarchi [Opens in a new window]  and
G. Guglieri Open the ORCID record for G. Guglieri [Opens in a new window]
G. Luzzani*
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
I. Buraioli
Affiliation:
Department of Electronics and Telecommunication, Politecnico di Torino, Turin, Italy
D. Demarchi
Affiliation:
Department of Electronics and Telecommunication, Politecnico di Torino, Turin, Italy
G. Guglieri
Affiliation:
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
*
Corresponding author: G. Luzzani; Email: gabriele.luzzani@polito.it
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Abstract

The relevant growth of human-machine interaction (HMI) systems in recent years is leading to the necessity of being constantly aware of the cognitive workload level of an operator, especially in a safety-critical context such as aviation. Since the confusion in the definition of this concept, this paper clarifies this terminology and also highlights its relationship with stress. Thus, we analysed the state-of-the-art of cognitive workload evaluations, showing three up-to-date methodologies: subjective, behavioural and physiological. In particular, the physiological approach is increasingly gaining attention in the literature due to today’s exponential growth of biomedical sensors. Therefore, a review of the most adopted physiological signals in the workload evaluation is provided, focusing on the aeronautical field. We conclude by highlighting the necessity of a multimodal approach for mental workload assessment as a result of this analysis.

Keywords

Human factorsmental workloadstressphysiological signalshuman-machine interaction

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Type
Survey Paper
Information
The Aeronautical Journal , Volume 128 , Issue 1323 , May 2024 , pp. 928 - 949
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Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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