Wavelet analysis of electroencephalographic and electro-oculographic changes during the sleep onset period

This study investigates the relationship between changes in the electroencephalogram (EEG) and slow eye movements (SEMs) in the electro-oculogram (EOG) at the wake-sleep transition. Analysis of EEG and EOG is performed by the discrete wavelet transform and utilizes energy functions built within the multiresolution framework. In particular, SEMs are detected automatically by a computerized system, previously developed and validated; core of the system is a function of EOG energies at different scales of decomposition, which defines SEMs in rigorous energetic terms. Changes in EEG rhythms are characterized by considering the relative energy of EEG signal at each scale of decomposition. The analysis has been applied to EEG and EOG signals acquired on fifteen healthy subjects during polysomnography. In all the examined subjects, falling asleep is systematically accompanied by EEG energy redistribution among the different scales and by SEMs occurrence. In particular, SEMs anticipate EEG modifications, preceding alpha blocking and theta intrusion even by several (10-20) minutes. This result suggests that EOG activity may be used to monitor sleepiness and sleep onset and to predict decrease in behavioral performances associated with drowsiness.