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Reseach Article

Drowsiness Detection in Drivers: A Review

Published on February 2015 by Pooja C. Rane, Manjusha Deshmukh
International Conference on Advances in Science and Technology
Foundation of Computer Science USA
ICAST2014 - Number 2
February 2015
Authors: Pooja C. Rane, Manjusha Deshmukh

Pooja C. Rane, Manjusha Deshmukh . Drowsiness Detection in Drivers: A Review. International Conference on Advances in Science and Technology. ICAST2014, 2 (February 2015), 27-29.

author = { Pooja C. Rane, Manjusha Deshmukh },
title = { Drowsiness Detection in Drivers: A Review },
journal = { International Conference on Advances in Science and Technology },
issue_date = { February 2015 },
volume = { ICAST2014 },
number = { 2 },
month = { February },
year = { 2015 },
issn = 0975-8887,
pages = { 27-29 },
numpages = 3,
url = { /proceedings/icast2014/number2/19480-5026/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Proceeding Article
%1 International Conference on Advances in Science and Technology
%A Pooja C. Rane
%A Manjusha Deshmukh
%T Drowsiness Detection in Drivers: A Review
%J International Conference on Advances in Science and Technology
%@ 0975-8887
%V ICAST2014
%N 2
%P 27-29
%D 2015
%I International Journal of Computer Applications

Inattentiveness in drivers is the major contributing factor in road crashes. Inattention can be caused by several reasons and one amongst them is fatigue. Fatigue is the subjective feeling of tiredness which is distinct from weakness. Fatigue can be defined as the state of impairment that can include physical, mental or both the elements associated with lower alertness and reduced performance. Thus performing a physical activity becomes difficult with the increasing fatigue level. Fatigue can have physical or mental causes. Alertness of a person is typically characterized by the various visual cues like eyelid movement, gaze movement, head movement and facial expressions. They can also be deduced from the driver's behaviour with the vehicle like distance maintained between vehicles, lane deviation, steering wheel control, breaking and gearing of the vehicle. Mental state of the driver can best be determined from the Electroencephalogram signals. This paper gives a brief review of the various visual and non-visual cues to detect the inattentiveness in drivers and in turn helps in reducing the probabilities of mishaps caused due to the fatigue

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Index Terms

Computer Science
Information Sciences


Fatigue Electroencephalogram Perclos Template Matching.