10 - Safety and Security
HRV BASED PILOTS WORKLOAD PREDICTION FOR AN INTELLIGENT COCKPIT WARNING SYSTEM
C.R. Vindigni¹, A. Esposito¹, C. Orlando¹, A. Alaimo¹; ¹University of Enna Kore, Italy
This study explores the integration of heterogeneous data to improve cognitive workload assessment. HRV features from 49 subjects (34 pilots, 15 students) who performed several tasks on a full-flight simulator are analyzed. Random Forest and AdaBoost models assess workload classification, aiming to boost statistical power through mixed-population datasets.
DOI: 10.71945/icas2026_0422