During drowsy periods, performance on tasks requiring continuous attention becomes intermittent. Previously, we have reported that during drowsy periods of intermittent performance, 7 of 10 participants performing an auditory detection task exhibited episodes of non-responding lasting about 18 s (Makeig & Jung, 1996). Further, the time patterns of these episodes were repeated precisely in subse...

In this paper, we propose a simple SVM, or support vector machine, classifier-based algorithm for determining whether eyes are open or closed in images. Due to its computational simplicity, it can be implemented on embedded systems, such as the Blackfin Low-Power Imaging Platform (BLIP) by Analog Devices, Inc. This design provides an inexpensive and practical solution to drowsiness detection fu...

Drowsiness and fatigue are serious problems in all transportation systems. One persistent issue is the lack of an agreed definition of these respective energetic states. Here we review the theoretical approaches (cognitive versus physiological) framing the driver fatigue problem. Known contributing factors to drowsiness include sleep debt, circadian rhythm, and shift work. However, we also sugg...

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This study takes a starting point in what drivers do to avoid drowsiness while driving instead of starting with what researchers know is efficient (Take a short nap). It is concluded that research is missing when it comes to how efficient common behavior countermeasures are and that there is a mismatch between research and how people actually behave. A three stage approach which includes identi...

Electroencephalographic (EEG) and neurocognitive measures were simultaneously acquired to quantify alertness from 24 participants during 44-hours of sleep deprivation. Performance on a three-choice vigilance task (3C-VT), pairedassociate learning/memory task (PAL) and modified Maintenance of Wakefulness Test (MWT), and sleep technicianobserved drowsiness (eye-closures, head-nods, EEG slowing) w...