Drowsiness detection during different times of day using multiple features

Drowsiness detection during different times of day using multiple features

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Main Authors: Sahayadhas, Arun, Sundaraj, Kenneth, Prof. Dr., Murugappan, M
Other Authors: arurun@gmail.com
Format: Article
Language:English
Published: Springer Netherlands 2014
Subjects:
Driver drowsiness
ECG
EMG
Physiological measures
Subjective measures
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33328
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Institution: Universiti Malaysia Perlis
Language: English
id my.unimap-33328
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spelling my.unimap-333282014-04-01T08:52:45Z Drowsiness detection during different times of day using multiple features Sahayadhas, Arun Sundaraj, Kenneth, Prof. Dr. Murugappan, M arurun@gmail.com kenneth@unimap.edu.my murugappan@unimap.edu.my Driver drowsiness ECG EMG Physiological measures Subjective measures Link to publisher's homepage at http://link.springer.com/ Driver drowsiness has been one of the major causes of road accidents that lead to severe trauma, such as physical injury, death, and economic loss, which highlights the need to develop a system that can alert drivers of their drowsy state prior to accidents. Researchers have therefore attempted to develop systems that can determine driver drowsiness using the following four measures: (1) subjective ratings from drivers, (2) vehicle-based measures, (3) behavioral measures and (4) physiological measures. In this study, we analyzed the various factors that contribute towards drowsiness. A total of 15 male subjects were asked to drive for 2 h at three different times of the day (00:00–02:00, 03:00–05:00 and 15:00–17:00 h) when the circadian rhythm is low. The less intrusive physiological signal measurements, ECG and EMG, are analyzed during this driving task. Statistically significant differences in the features of ECG and sEMG signals were observed between the alert and drowsy states of the drivers during different times of day. In the future, these physiological measures can be fused with vision-based measures for the development of an efficient drowsiness detection system. 2014-04-01T08:52:45Z 2014-04-01T08:52:45Z 2013 Article Australasian Physical & Engineering Sciences in Medicine, vol. 36(2), 2013, pages 243-250 1879-5447 (Online) 0158-9938 (Print) http://dspace.unimap.edu.my:80/dspace/handle/123456789/33328 http://link.springer.com/article/10.1007%2Fs13246-013-0200-6 10.1007/s13246-013-0200-6 en Springer Netherlands
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Driver drowsiness
ECG
EMG
Physiological measures
Subjective measures
spellingShingle Driver drowsiness
ECG
EMG
Physiological measures
Subjective measures
Sahayadhas, Arun
Sundaraj, Kenneth, Prof. Dr.
Murugappan, M
Drowsiness detection during different times of day using multiple features
description Link to publisher's homepage at http://link.springer.com/
author2 arurun@gmail.com
author_facet arurun@gmail.com
Sahayadhas, Arun
Sundaraj, Kenneth, Prof. Dr.
Murugappan, M
format Article
author Sahayadhas, Arun
Sundaraj, Kenneth, Prof. Dr.
Murugappan, M
author_sort Sahayadhas, Arun
title Drowsiness detection during different times of day using multiple features
title_short Drowsiness detection during different times of day using multiple features
title_full Drowsiness detection during different times of day using multiple features
title_fullStr Drowsiness detection during different times of day using multiple features
title_full_unstemmed Drowsiness detection during different times of day using multiple features
title_sort drowsiness detection during different times of day using multiple features
publisher Springer Netherlands
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33328
_version_ 1643797138884263936

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