1. Quentin Massoz. Non-invasive, automatic, and real-time characterization of drowsiness based on eye closure dynamics. PhD thesis, University of Liège, Belgium, April 2019. Keyword(s): Drowsiness, Driver monitoring, Face, Eye closure, Pyschomotor vigilance test, Reaction time, CNN, Deep learning. [bibtex-entry]

1. Anaïs Halin, Jacques G. Verly, and Marc Van Droogenbroeck. Survey and synthesis of state of the art in driver monitoring. Sensors, 21(16):1-49, August 2021. Keyword(s): Driver monitoring, Driver state, Survey, Sensor, Indicator, Drowsiness, Mental workload, Distraction, Emotion, Under the influence. [bibtex-entry]



2. Quentin Massoz, Jacques Verly, and Marc Van Droogenbroeck. Multi-timescale drowsiness characterization based on a video of a driver's face. Sensors, 18(9):1-17, August 2018. Keyword(s): Drowsiness, Driver monitoring, Face, Eye closure, Pyschomotor vigilance test, Reaction time, CNN, Deep learning. [bibtex-entry]



3. Philippe Latour and Marc Van Droogenbroeck. The LNQ25 and ELN PVT Metrics Exhibit a Good Sensitivity to Sleep Deprivation and are Independent from the Subject. Sleep Medicine, 40:178-179, December 2017. Keyword(s): PVT metrics, Metrics, Drowsiness, Automatic alertness monitoring, Fatigue management. [bibtex-entry]

1. Philippe Latour and Marc Van Droogenbroeck. New PVT Metrics with Improved Sensitivity to Sleep Loss: Analysis from Short to Long Time Intervals. In Managing Fatigue, San Diego, California, USA, March 2017. Keyword(s): PVT metrics, Fatigue, Sleep, Sleep deprivation, Drowsiness, Sleepiness. [bibtex-entry]

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