Methodology and initial analysis results for development of non-invasive and hybrid driver drowsiness detection systems

Zilberg, E; Zheng, MX; Burton, D; Karrar, M; Lal, S

Methodology and initial analysis results for development of non-invasive and hybrid driver drowsiness detection systems

Zilberg, E Zheng, MX Burton, D Karrar, M Lal, S

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Publication Type:: Chapter
Citation:: 2007
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	Zilberg, E	en_US
dc.contributor.author	Zheng, MX	en_US
dc.contributor.author	Burton, D	en_US
dc.contributor.author	Karrar, M	en_US
dc.contributor.author	Lal, S https://orcid.org/0000-0002-0911-0850	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	2007	en_US
dc.identifier.isbn	0769528422	en_US
dc.identifier.isbn	9780769528427	en_US
dc.identifier.uri	http://hdl.handle.net/10453/8106
dc.description.abstract	Application of piezofilm movement sensors integrated into the car seat, seat belt and steering wheel was proposed for development of a non-invasive and hybrid systems for detecting driver drowsiness. A car simulator study was designed to collect physiological data for validation of this technology. Methodology for analysis of physiological data, independent assessment of driver drowsiness and development of drowsiness detection algorithm by means of sequential fitting and selection of regression models is presented. Statistical analysis shows that during the episodes of transitions to dangerous levels of drowsiness movement variations recorded by the seat sensors are decreasing. This finding indicates that the piezofilm movement sensors could be used as noninvasive devices for detecting the level of drowsiness on their own or in combination with other physiological signals. © 2007 IEEE.	en_US
dc.relation.isbasedon	10.1109/AUSWIRELESS.2007.44	en_US
dc.title	Methodology and initial analysis results for development of non-invasive and hybrid driver drowsiness detection systems	en_US
dc.type	Chapter
utslib.for	170205 Neurocognitive Patterns and Neural Networks	en_US
utslib.for	170107 Industrial and Organisational Psychology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Application of piezofilm movement sensors integrated into the car seat, seat belt and steering wheel was proposed for development of a non-invasive and hybrid systems for detecting driver drowsiness. A car simulator study was designed to collect physiological data for validation of this technology. Methodology for analysis of physiological data, independent assessment of driver drowsiness and development of drowsiness detection algorithm by means of sequential fitting and selection of regression models is presented. Statistical analysis shows that during the episodes of transitions to dangerous levels of drowsiness movement variations recorded by the seat sensors are decreasing. This finding indicates that the piezofilm movement sensors could be used as noninvasive devices for detecting the level of drowsiness on their own or in combination with other physiological signals. © 2007 IEEE.

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http://hdl.handle.net/10453/8106