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@article{149111,
        author = {SUMITHA A and SUBHA.R},
        title = {MICROSLEEP DETECTION TECHNIQUE},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {6},
        number = {11},
        pages = {242-248},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=149111},
        abstract = {In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries and deaths. On-road driver’s fatigue and drowsiness are contributing more than 30% of reported road accidents [1]. Statistics indicate the need for a reliable driver drowsiness detection system which could alert the driver before a mishap happens. Driver drowsiness can be estimated by monitoring vehicle-based measures, behavioral measures and physiological measures. The physiological measure includes eye-blinks, yawning, nodding of heads. The Blink and micro-sleep detection mechanisms are implemented by monitoring EAR. EAR is calculated by calculating Euclidean distance between measured eye coordinates. Blinks and drowsiness levels are displayed on the monitor screen with a micro-sleep detection audio warning.},
        keywords = {EAR, micro-sleep, Drowsiness},
        month = {},
        }