Detection and analysis of fatigue flight features using the fusion of pilot motion behavior and EEG information

This study addresses a gap in current research by integrating physiological and behavioral data for fatigue classification, demonstrating that the fusion of multi-source information significantly enhances detection accuracy and stability compared to single-feature methods. The findings contribute to improved pilot performance and enhanced flight safety by increasing the reliability of fatigue monitoring systems.