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Excessive sleepiness in drivers greatly increases the risk of traffic accidents. A compact, a three-dimensional system for analyzing visual information from a face photogram using an infrared CCD camera was recently designed to monitor drivers. The present study aimed to examine whether temporal changes in autonomic activity as determined by spectral analysis of electrocardiogram heart rate variability (HRV) and blinking duration obtained with this camera system could predict sleep onset in a driving simulation. Ten healthy adults (mean age, 21.8 ± 0.64 yrs) were enrolled in the study. The subjects sat upright in the driver’s seat while we performed standard polysomnography (PSG). HRV was assessed through a spectral analysis of RR intervals of the PSG electrocardiogram. Blinking duration was evaluated by an eyelid movement tracking system within the infrared CCD camera. Blinking duration was significantly prolonged during the 10 seconds before sleep onset compared with that during wakefulness (0.64 ± 0.13 vs. 0.34 ± 0.06 sec, p=0.0004). Subsequently, the high-frequency power of HRV was significantly greater at sleep onset (1201 ± 994.6 vs. 906.9 ± 766.2 ms2, p=0.001). We conclude that simultaneous measurement of HRV and blinking duration can be utilized to predict sleep onset in an automobile driving simulation.