Using spectral analysis to extract frequency components from electroencephalography: Application for fatigue countermeasure in train drivers

Jap, BT; Lal, S; Fischer, P; Bekiaris, E

Using spectral analysis to extract frequency components from electroencephalography: Application for fatigue countermeasure in train drivers

Jap, BT Lal, S

Fischer, P Bekiaris, E

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

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Field	Value	Language
dc.contributor.author	Jap, BT	en_US
dc.contributor.author	Lal, S https://orcid.org/0000-0002-0911-0850	en_US
dc.contributor.author	Fischer, P	en_US
dc.contributor.author	Bekiaris, E	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/10453/12764
dc.description.abstract	Train accidents can have a massive impact towards the surrounding area as well as the general community. Most train accidents can be attributed to fatigue, and hence, development of fatigue countermeasure devices that can warn drivers of fatigue status and prevent accidents can greatly benefit train drivers, passengers, society and general community. Electroencephalography (EEG) has been proven to be one of the most reliable indicators of fatigue. This study investigated the change of brain activity during fatigue-instigating monotonous driving session, by extracting the four frequency components (delta, theta, alpha, and beta) using FFT spectral analysis at different brain sites (frontal, central, temporal, parietal, and occipital). Results identified some statistically significant differences between early and later stages of driving in delta, theta and beta activities at different brain sites. The results of the current study may be used for future development of fatigue countermeasure by targeting specific frequency component and brain sites. © 2007 IEEE.	en_US
dc.relation	http://purl.org/au-research/grants/arc/LP0560886R1
dc.relation.isbasedon	10.1109/AUSWIRELESS.2007.83	en_US
dc.title	Using spectral analysis to extract frequency components from electroencephalography: Application for fatigue countermeasure in train drivers	en_US
dc.type	Chapter
utslib.for	1702 Cognitive Sciences	en_US
utslib.for	1701 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:

Train accidents can have a massive impact towards the surrounding area as well as the general community. Most train accidents can be attributed to fatigue, and hence, development of fatigue countermeasure devices that can warn drivers of fatigue status and prevent accidents can greatly benefit train drivers, passengers, society and general community. Electroencephalography (EEG) has been proven to be one of the most reliable indicators of fatigue. This study investigated the change of brain activity during fatigue-instigating monotonous driving session, by extracting the four frequency components (delta, theta, alpha, and beta) using FFT spectral analysis at different brain sites (frontal, central, temporal, parietal, and occipital). Results identified some statistically significant differences between early and later stages of driving in delta, theta and beta activities at different brain sites. The results of the current study may be used for future development of fatigue countermeasure by targeting specific frequency component and brain sites. © 2007 IEEE.

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http://hdl.handle.net/10453/12764