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Detecting Driver Drowsiness Based on Sensors: A Review
In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Molecular Diversity Preservation International (MDPI)
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571819/ https://www.ncbi.nlm.nih.gov/pubmed/23223151 http://dx.doi.org/10.3390/s121216937 |
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author | Sahayadhas, Arun Sundaraj, Kenneth Murugappan, Murugappan |
author_facet | Sahayadhas, Arun Sundaraj, Kenneth Murugappan, Murugappan |
author_sort | Sahayadhas, Arun |
collection | PubMed |
description | In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens. Researchers have attempted to determine driver drowsiness using the following measures: (1) vehicle-based measures; (2) behavioral measures and (3) physiological measures. A detailed review on these measures will provide insight on the present systems, issues associated with them and the enhancements that need to be done to make a robust system. In this paper, we review these three measures as to the sensors used and discuss the advantages and limitations of each. The various ways through which drowsiness has been experimentally manipulated is also discussed. We conclude that by designing a hybrid drowsiness detection system that combines non-intusive physiological measures with other measures one would accurately determine the drowsiness level of a driver. A number of road accidents might then be avoided if an alert is sent to a driver that is deemed drowsy. |
format | Online Article Text |
id | pubmed-3571819 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Molecular Diversity Preservation International (MDPI) |
record_format | MEDLINE/PubMed |
spelling | pubmed-35718192013-02-19 Detecting Driver Drowsiness Based on Sensors: A Review Sahayadhas, Arun Sundaraj, Kenneth Murugappan, Murugappan Sensors (Basel) Review In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses. Statistics indicate the need of a reliable driver drowsiness detection system which could alert the driver before a mishap happens. Researchers have attempted to determine driver drowsiness using the following measures: (1) vehicle-based measures; (2) behavioral measures and (3) physiological measures. A detailed review on these measures will provide insight on the present systems, issues associated with them and the enhancements that need to be done to make a robust system. In this paper, we review these three measures as to the sensors used and discuss the advantages and limitations of each. The various ways through which drowsiness has been experimentally manipulated is also discussed. We conclude that by designing a hybrid drowsiness detection system that combines non-intusive physiological measures with other measures one would accurately determine the drowsiness level of a driver. A number of road accidents might then be avoided if an alert is sent to a driver that is deemed drowsy. Molecular Diversity Preservation International (MDPI) 2012-12-07 /pmc/articles/PMC3571819/ /pubmed/23223151 http://dx.doi.org/10.3390/s121216937 Text en © 2012 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Review Sahayadhas, Arun Sundaraj, Kenneth Murugappan, Murugappan Detecting Driver Drowsiness Based on Sensors: A Review |
title | Detecting Driver Drowsiness Based on Sensors: A Review |
title_full | Detecting Driver Drowsiness Based on Sensors: A Review |
title_fullStr | Detecting Driver Drowsiness Based on Sensors: A Review |
title_full_unstemmed | Detecting Driver Drowsiness Based on Sensors: A Review |
title_short | Detecting Driver Drowsiness Based on Sensors: A Review |
title_sort | detecting driver drowsiness based on sensors: a review |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3571819/ https://www.ncbi.nlm.nih.gov/pubmed/23223151 http://dx.doi.org/10.3390/s121216937 |
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