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Drowsiness detection has a significant importance in aviation industry. Electroencephalogram (EEG) has been extensively studied to characterize drowsiness; nevertheless, its behavior with respect to accurately annotated drowsy periods remains to be investigated. At present, Karolinska Sleepiness Scale and psychomotor vigilance task are widely used references for subjective drowsiness analysis. However, their practical application in real-time monitoring of alertness is limited. To address this limitation, we combined Seeing Machines driver monitoring system and electrooculogram (EOG) for localization of microsleep (MS) events and studied EEG spectral behavior during MS events. EEG, EOG, and facial behavior data were recorded simultaneously from 16 commercially rated pilots during simulated flight. Relative spectral power in delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), and beta (13-30 Hz) in frontal …