Analysis of alertness status of subjects undergoing the cortical auditory evoked potential hearing test

Al-Ani, A; Van Dun, B; Dillon, H; Rabie, A

Analysis of alertness status of subjects undergoing the cortical auditory evoked potential hearing test

Al-Ani, A

Van Dun, B Dillon, H Rabie, A

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Publication Type:: Journal Article
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, 7663 LNCS (PART 1), pp. 92 - 99
Issue Date:: 2012-11-19

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Field	Value	Language
dc.contributor.author	Al-Ani, A https://orcid.org/0000-0002-8092-8954	en_US
dc.contributor.author	Van Dun, B	en_US
dc.contributor.author	Dillon, H	en_US
dc.contributor.author	Rabie, A	en_US
dc.date.issued	2012-11-19	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, 7663 LNCS (PART 1), pp. 92 - 99	en_US
dc.identifier.isbn	9783642344749	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/22874
dc.description.abstract	In this paper, we analyze the EEG rhythms of subjects undergoing the cortical auditory evoked potential (CAEP) hearing test. Investigation of the importance of the different EEG rhythms in terms of their capability in differentiating between the different alertness states when considering 64 channel EEG montage is conducted. This is followed by considering subsets that contain 2, 3, 4 as well as all 5 EEG rhythms. Finally, a feature subset selection method based on differential evolution (DE) that has particularly been proposed to deal with multi-channel signals is used to search for the best subset of EEG rhythms for the various channels. © 2012 Springer-Verlag.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-642-34475-6_12	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Analysis of alertness status of subjects undergoing the cortical auditory evoked potential hearing test	en_US
dc.type	Journal Article
utslib.citation.volume	PART 1	en_US
utslib.citation.volume	7663 LNCS	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Doha, Qatar	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 Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	closed_access
pubs.issue	PART 1	en_US
pubs.publication-status	Published	en_US
pubs.volume	7663 LNCS	en_US

Abstract:

In this paper, we analyze the EEG rhythms of subjects undergoing the cortical auditory evoked potential (CAEP) hearing test. Investigation of the importance of the different EEG rhythms in terms of their capability in differentiating between the different alertness states when considering 64 channel EEG montage is conducted. This is followed by considering subsets that contain 2, 3, 4 as well as all 5 EEG rhythms. Finally, a feature subset selection method based on differential evolution (DE) that has particularly been proposed to deal with multi-channel signals is used to search for the best subset of EEG rhythms for the various channels. © 2012 Springer-Verlag.

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http://hdl.handle.net/10453/22874