Applying neural network analysis on heart rate variability data to assess driver fatigue

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Show simple item record Patel, M Lal, SKL Kavanagh, D Rossiter, P 2012-02-02T04:03:16Z 2011-06
dc.identifier.citation Expert Systems with Applications, 2011, 38 (6), pp. 7235 - 7242
dc.identifier.issn 0957-4174
dc.identifier.other C1 en_US
dc.description.abstract Long duration driving is a significant cause of fatigue related accidents on motorways. Fatigue caused by driving for extended hours can acutely impair driver's alertness and performance. This papers presents an artificial intelligence based system which could detect early onset of fatigue in drivers using heart rate variability (HRV) as the human physiological measure. The detection performance of neural network was tested using a set of electrocardiogram (ECG) data recorded under laboratory conditions. The neural network gave an accuracy of 90%. This HRV based fatigue detection technique can be used as a fatigue countermeasure. © 2010 Elsevier Ltd. All rights reserved.
dc.language eng
dc.relation.isbasedon 10.1016/j.eswa.2010.12.028
dc.title Applying neural network analysis on heart rate variability data to assess driver fatigue
dc.type Journal Article
dc.description.version Published
dc.parent Expert Systems with Applications
dc.journal.volume 6
dc.journal.volume 38
dc.journal.number 6 en_US
dc.publocation Netherlands en_US
dc.identifier.startpage 7235 en_US
dc.identifier.endpage 7242 en_US SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 0102 Applied Mathematics
dc.personcode 010322
dc.personcode 104938
dc.personcode 10499604
dc.percentage 100 en_US Applied Mathematics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US en_US
dc.location.activity en_US
dc.description.keywords Driver fatigue
dc.description.keywords Heart rate variability
dc.description.keywords Neural network
dc.description.keywords Spectral analysis
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group /University of Technology Sydney/Faculty of Science
pubs.organisational-group /University of Technology Sydney/Strength - Health Technologies
pubs.organisational-group /University of Technology Sydney/Students
utslib.copyright.status Closed Access 2015-04-15 12:17:09.805752+10
pubs.consider-herdc true
utslib.collection.history School of Medical and Molecular Sciences (ID: 341)
utslib.collection.history Closed (ID: 3)

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