Detection of alertness states using electroencephalogram and cortical auditory evoked potential responses

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

Detection of alertness states using electroencephalogram and cortical auditory evoked potential responses

Rabie, A Al-Ani, A

Van Dun, B Dillon, H

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Publication Type:: Conference Proceeding
Citation:: International IEEE/EMBS Conference on Neural Engineering, NER, 2013, pp. 1433 - 1436
Issue Date:: 2013-12-01

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Field	Value	Language
dc.contributor.author	Rabie, A	en_US
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.date.issued	2013-12-01	en_US
dc.identifier.citation	International IEEE/EMBS Conference on Neural Engineering, NER, 2013, pp. 1433 - 1436	en_US
dc.identifier.isbn	9781467319690	en_US
dc.identifier.issn	1948-3546	en_US
dc.identifier.uri	http://hdl.handle.net/10453/120781
dc.description.abstract	In this paper, we focus on identifying the alertness state of subjects undergoing the cortical auditory evoked potential (CAEP) hearing test. A supervised classification approach is adopted, where subjects were advised to indicate their alertness states in specified time instances. Two sets of features are considered here to represent the recorded data. The first is based on the wavelet transform of the background EEG, while the second is obtained from the peaks of the CAEP responses. The rational behind using the second feature set is to evaluate the relationship between CAEP responses and alertness levels. Obtained results suggest that the CAEP-based features are very comparable, in terms of classification accuracy, to the well-established wavelet-based features of EEG signals (79% compared to 80%). The findings of this paper will contribute towards a better understanding of CAEP responses at the different alertness states. © 2013 IEEE.	en_US
dc.relation.ispartof	International IEEE/EMBS Conference on Neural Engineering, NER	en_US
dc.relation.isbasedon	10.1109/NER.2013.6696213	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Detection of alertness states using electroencephalogram and cortical auditory evoked potential responses	en_US
dc.type	Conference Proceeding
utslib.for	090399 Biomedical Engineering not elsewhere classified	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	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.publication-status	Published	en_US

Abstract:

In this paper, we focus on identifying the alertness state of subjects undergoing the cortical auditory evoked potential (CAEP) hearing test. A supervised classification approach is adopted, where subjects were advised to indicate their alertness states in specified time instances. Two sets of features are considered here to represent the recorded data. The first is based on the wavelet transform of the background EEG, while the second is obtained from the peaks of the CAEP responses. The rational behind using the second feature set is to evaluate the relationship between CAEP responses and alertness levels. Obtained results suggest that the CAEP-based features are very comparable, in terms of classification accuracy, to the well-established wavelet-based features of EEG signals (79% compared to 80%). The findings of this paper will contribute towards a better understanding of CAEP responses at the different alertness states. © 2013 IEEE.

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http://hdl.handle.net/10453/120781