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Updated: Jan 13, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019
Aircrew rostering workload patterns and associated fatigue and sleepiness scores in short and medium haul flights in
Tulio E Rodrigues1,2, Eduardo Furlan3, André F Helene4
1Experimental Physics Department, Physics Institute, University of São Paulo, P. O. Box 66318, CEP 05315-970, São Paulo, Brazil. tulio@if.usp.br.
Abstract:
Relationships between workload and fatigue or sleepiness are investigated through the analysis of rosters and responses to questionnaires from Brazilian aircrews, taken from Fadigômetro database. The approach includes temporal markers-coinciding with Samn-Perelli (SP) and Karolinska Sleepiness Scale (KSS) responses-where SAFTE-FAST software outcomes are calculated. The latter results follow the increase of fatigue and sleepiness perceptions during the dawn (0h00 to 05h59), but underestimate self-rated scores during the evening (18h00 to 23h59). Importantly, the KSS scores and the inverse of SAFTE-FAST effectiveness fit the relative risk of pilot errors, representing interesting proxies for risk assessment. Linear relationships obtained between workload metrics, computed within 168-h prior to the responses, and self-rated SP and KSS scores provide a consistent method to estimate accumulated fatigue and sleepiness. Considering 7149 rosters of 2023, the duty time (DT), the number of flight sectors ([Formula: see text]) and the sum of flight sectors with sit periods longer than one hour ([Formula: see text]) are associated with 70.1%/60.6% of the highest predicted scores of SP/KSS. Applying the mitigations [Formula: see text], [Formula: see text] and [Formula: see text] for every 168-h interval yields a significant decrease in higher values of SP/KSS with minimal impact on roster coverage.
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