DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS
Driver drowsiness is considered to be a very critical issue causing many fatal accidents, injuries and property damages. Therefore it has been an area of intensive research during recent years. In this study, a driver drowsiness detection system is proposed, that integrates Electrocardiogram (ECG...
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oai:utpedia.utp.edu.my:212142024-07-24T03:33:55Z http://utpedia.utp.edu.my/id/eprint/21214/ DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS ,, MUHAMMAD AWAIS TK Electrical engineering. Electronics Nuclear engineering Driver drowsiness is considered to be a very critical issue causing many fatal accidents, injuries and property damages. Therefore it has been an area of intensive research during recent years. In this study, a driver drowsiness detection system is proposed, that integrates Electrocardiogram (ECG) and Electroencephalogram (EEG) features to detect drowsiness. The proposed system is based upon the idea to observe the physiological variations that occurs from alert to drowsy state. For physiological data acquisition, a driving simulator based study was conducted in a monotonous driving environment to get the driver drowsy naturally. Twenty two healthy university students voluntarily participated in the experiment after strict inclusion criteria. Features extracted from the EEG signal were absolute power, relative power, and coherence in alert and drowsy state. 2014-07 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/id/eprint/21214/1/2014-ELECTRICAL%20AND%20ENGINEERING-DRIVER%20DROWNSINESS%20DETECTION%20USING%20PHYSIOLOGICAL%20SIGNALS-%20MUHAMMAD%20AWAIS-%20MASTER%20OF%20SCIENCE.pdf ,, MUHAMMAD AWAIS (2014) DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS. Masters thesis, Universiti Teknologi PETRONAS. |
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TK Electrical engineering. Electronics Nuclear engineering ,, MUHAMMAD AWAIS DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS |
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Driver drowsiness is considered to be a very critical issue causing many fatal
accidents, injuries and property damages. Therefore it has been an area of intensive
research during recent years. In this study, a driver drowsiness detection system is
proposed, that integrates Electrocardiogram (ECG) and Electroencephalogram (EEG)
features to detect drowsiness. The proposed system is based upon the idea to observe
the physiological variations that occurs from alert to drowsy state. For physiological
data acquisition, a driving simulator based study was conducted in a monotonous
driving environment to get the driver drowsy naturally. Twenty two healthy university
students voluntarily participated in the experiment after strict inclusion criteria.
Features extracted from the EEG signal were absolute power, relative power, and
coherence in alert and drowsy state. |
format |
Thesis |
author |
,, MUHAMMAD AWAIS |
author_facet |
,, MUHAMMAD AWAIS |
author_sort |
,, MUHAMMAD AWAIS |
title |
DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS |
title_short |
DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS |
title_full |
DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS |
title_fullStr |
DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS |
title_full_unstemmed |
DRIVER DROWSINESS DETECTION USING PHYSIOLOGICAL SIGNALS |
title_sort |
driver drowsiness detection using physiological signals |
publishDate |
2014 |
url |
http://utpedia.utp.edu.my/id/eprint/21214/1/2014-ELECTRICAL%20AND%20ENGINEERING-DRIVER%20DROWNSINESS%20DETECTION%20USING%20PHYSIOLOGICAL%20SIGNALS-%20MUHAMMAD%20AWAIS-%20MASTER%20OF%20SCIENCE.pdf http://utpedia.utp.edu.my/id/eprint/21214/ |
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1805891021324681216 |