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Conference Paper: Detection of pain from nociceptive laser-evoked potentials using single-trial analysis and pattern recognition

TitleDetection of pain from nociceptive laser-evoked potentials using single-trial analysis and pattern recognition
Authors
KeywordsPain perception
Pattern recognition
Quadratic classifier
Single-trial analysis
Issue Date2012
PublisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800540
Citation
The 2nd IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC 2012), Hong Kong, China, 12-15 August 2012. In Conference Proceedings, 2012, p. 67-71 How to Cite?
AbstractPain is an unpleasant multidimensional experience, which could be largely influenced by various peripheral and cognitive factors. Therefore, the pain experience and the related brain responses exhibit high variability from time to time and from condition to condition. The availability of an objective assessment of pain perception would be of great importance for both basic and clinical applications. In the present study, we combined single-trial analysis and pattern recognition techniques to differentiate nociceptive laser-evoked brain responses (LEPs) and resting electroencephalographical recordings (EEG). We found that quadratic classifier significantly outperformed linear classifier when separating LEP trials from resting EEG trials. Across subjects, the error rates of quadratic classifier, when it was tested on all trials (I1+I2), trials with low ratings (I1), and trials with high rating (I2), are respectively 17.5±3.5%, 20.6±4.3%, and 9.1±4.9%. © 2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/189875
ISBN

 

DC FieldValueLanguage
dc.contributor.authorHu, Len_US
dc.contributor.authorZhang, Zen_US
dc.date.accessioned2013-09-17T15:01:03Z-
dc.date.available2013-09-17T15:01:03Z-
dc.date.issued2012en_US
dc.identifier.citationThe 2nd IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC 2012), Hong Kong, China, 12-15 August 2012. In Conference Proceedings, 2012, p. 67-71en_US
dc.identifier.isbn978-1-4673-2193-8-
dc.identifier.urihttp://hdl.handle.net/10722/189875-
dc.description.abstractPain is an unpleasant multidimensional experience, which could be largely influenced by various peripheral and cognitive factors. Therefore, the pain experience and the related brain responses exhibit high variability from time to time and from condition to condition. The availability of an objective assessment of pain perception would be of great importance for both basic and clinical applications. In the present study, we combined single-trial analysis and pattern recognition techniques to differentiate nociceptive laser-evoked brain responses (LEPs) and resting electroencephalographical recordings (EEG). We found that quadratic classifier significantly outperformed linear classifier when separating LEP trials from resting EEG trials. Across subjects, the error rates of quadratic classifier, when it was tested on all trials (I1+I2), trials with low ratings (I1), and trials with high rating (I2), are respectively 17.5±3.5%, 20.6±4.3%, and 9.1±4.9%. © 2012 IEEE.-
dc.languageengen_US
dc.publisherIEEE. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1800540-
dc.relation.ispartofIEEE International Conference on Signal Processing, Communications and Computing Proceedingsen_US
dc.rightsIEEE International Conference on Signal Processing, Communications and Computing Proceedings. Copyright © IEEE.-
dc.rights©2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectPain perception-
dc.subjectPattern recognition-
dc.subjectQuadratic classifier-
dc.subjectSingle-trial analysis-
dc.titleDetection of pain from nociceptive laser-evoked potentials using single-trial analysis and pattern recognitionen_US
dc.typeConference_Paperen_US
dc.identifier.emailZhang, Z: zgzhang@eee.hku.hken_US
dc.identifier.authorityZhang, Z=rp01565en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICSPCC.2012.6335677-
dc.identifier.scopuseid_2-s2.0-84869427544-
dc.identifier.hkuros223278en_US
dc.identifier.spage67-
dc.identifier.epage71-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 131024-

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