The psychophysiology of driver fatigue/drowsiness : electroencephalography, electro-oculogram, electrocardiogram and psychological effects

Lal, SKL

The psychophysiology of driver fatigue/drowsiness : electroencephalography, electro-oculogram, electrocardiogram and psychological effects

Lal, SKL

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Publication Type:: Thesis
Issue Date:: 2001

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Field	Value	Language
dc.contributor.author	Lal, SKL
dc.date.accessioned	2010-03-31T04:27:54Z
dc.date.accessioned	2012-12-15T03:53:01Z
dc.date.available	2010-03-31T04:27:54Z
dc.date.available	2012-12-15T03:53:01Z
dc.date.issued	2001
dc.identifier.uri	http://hdl.handle.net/10453/20253
dc.description	University of Technology, Sydney. Faculty of Science.	en
dc.description.abstract	Driver fatigue is a major cause of road accidents and has implications for road safety. Investigating the psychophysiological links to fatigue can enhance our understanding and management of fatigue in the transport industry. A variety of psychophysiological parameters have been identified as indicators of fatigue, with electroencephalography (EEG) perhaps being the most promising. Therefore, monitoring EEG during driver fatigue may be a promising variable for use in fatigue countermeasure devices. However, most previous fatigue-based studies have suffered from methodological shortcomings such as insufficient sample numbers, lack of a controlled testing environment, inadequate study design and statistical analysis. Furthermore, a thorough psychophysiological assessment of fatigue was found to be lacking in the literature. Therefore, the aims of the present doctoral research were to: 1) Assess the EEG and electro-occulogram (EOG) changes during driver fatigue in a 'state of the art' experimentally controlled study. 2) Identify psychological associations with fatigue. 3) Assess the changes in autonomic nervous system activity during fatigue. 4) Investigate the differences in the physiological changes that occur during fatigue in professional versus non-professional drivers. 5) Identify the reproducibility of physiological changes that occur during fatigue. 6) Examine the changes in EEG coherence during fatigue. 7) Utilise the physiological findings in this research for the development of EEG based software to detect fatigue. The results showed significant increases in delta and theta during driver fatigue. The conventional high amplitude blinks during alertness was replaced with slow, low amplitude blinks during fatigue. Reduced Fatigue-Inertia and decreased VigourActivity (which are mood sub-scales) and increased anxiety levels were associated with fatigue. There was an increase in parasympathetic activity during fatigue. Nonprofessional drivers showed greater increases in the EEG of fatigue compared to professional drivers. The EEG changes associated with fatigue were shown to be reproducible. The changes in EEG coherence were not found to be significant during fatigue. The EEG changes during fatigue were used for the development of an algorithm for a fatigue-countermeasure device and was shown to reliably detect fatigue. In summary, this research has provided important information on the psychophysiology of driver fatigue clarifying some of the findings of prior research. Significant changes were found to occur in EEG, EOG and parasympathetic activity during fatigue. From this research it may also be suggested that psychological status of the driver may influence fatigue status. Furthermore, the EEG changes during fatigue are consistent and reliable, which can be utilised to detect fatigue in a EEG-based fatigue countermeasure device. The results are discussed in the light of direction for future driver fatigue studies and fatigue management.	en
dc.format	Thesis (PhD)	en
dc.language.iso	en	en
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/20253/10/02whole.pdf
dc.relation.replaces	http://hdl.handle.net/2100/1031
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	au.edu.uts.lib/ppc
dc.title	The psychophysiology of driver fatigue/drowsiness : electroencephalography, electro-oculogram, electrocardiogram and psychological effects	en
dc.type	Thesis
utslib.copyright.status	open_access

Abstract:

Driver fatigue is a major cause of road accidents and has implications for road safety. Investigating the psychophysiological links to fatigue can enhance our understanding and management of fatigue in the transport industry. A variety of psychophysiological parameters have been identified as indicators of fatigue, with electroencephalography (EEG) perhaps being the most promising. Therefore, monitoring EEG during driver fatigue may be a promising variable for use in fatigue countermeasure devices. However, most previous fatigue-based studies have suffered from methodological shortcomings such as insufficient sample numbers, lack of a controlled testing environment, inadequate study design and statistical analysis. Furthermore, a thorough psychophysiological assessment of fatigue was found to be lacking in the literature. Therefore, the aims of the present doctoral research were to: 1) Assess the EEG and electro-occulogram (EOG) changes during driver fatigue in a 'state of the art' experimentally controlled study. 2) Identify psychological associations with fatigue. 3) Assess the changes in autonomic nervous system activity during fatigue. 4) Investigate the differences in the physiological changes that occur during fatigue in professional versus non-professional drivers. 5) Identify the reproducibility of physiological changes that occur during fatigue. 6) Examine the changes in EEG coherence during fatigue. 7) Utilise the physiological findings in this research for the development of EEG based software to detect fatigue. The results showed significant increases in delta and theta during driver fatigue. The conventional high amplitude blinks during alertness was replaced with slow, low amplitude blinks during fatigue. Reduced Fatigue-Inertia and decreased VigourActivity (which are mood sub-scales) and increased anxiety levels were associated with fatigue. There was an increase in parasympathetic activity during fatigue. Nonprofessional drivers showed greater increases in the EEG of fatigue compared to professional drivers. The EEG changes associated with fatigue were shown to be reproducible. The changes in EEG coherence were not found to be significant during fatigue. The EEG changes during fatigue were used for the development of an algorithm for a fatigue-countermeasure device and was shown to reliably detect fatigue. In summary, this research has provided important information on the psychophysiology of driver fatigue clarifying some of the findings of prior research. Significant changes were found to occur in EEG, EOG and parasympathetic activity during fatigue. From this research it may also be suggested that psychological status of the driver may influence fatigue status. Furthermore, the EEG changes during fatigue are consistent and reliable, which can be utilised to detect fatigue in a EEG-based fatigue countermeasure device. The results are discussed in the light of direction for future driver fatigue studies and fatigue management.

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