A Feature Set for EEG Seizure Detection in the Newborn based on Seizure and Background Charactersitics

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A Feature Set for EEG Seizure Detection in the Newborn based on Seizure and Background Charactersitics

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dc.contributor.author Stevenson, N
dc.contributor.author Mesbah, M
dc.contributor.author Boashash, B
dc.date.accessioned 2012-09-21T15:16:06Z
dc.date.available 2012-09-21T15:16:06Z
dc.date.issued 2007
dc.identifier.citation Proc. of Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 2007, pp. 7-10. en_US
dc.identifier.issn 1557-170X
dc.identifier.other Digital Object Identifier : 10.1109/IEMBS.2007.4352209
dc.identifier.uri http://hdl.handle.net/10576/10874
dc.description This paper presents a feature set of four features for use in the detection of seizure in the EEGs of newborns, which are designed with the aid of recent advances in time-frequency modelling of the newborn EEG signal. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (seehttp://www.elsevier.com/locate/isbn/0080443354). In addition, the most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia, and then continuously updated). en_US
dc.description.abstract This paper presents a set of four features to be used in the detection of seizure in the electroencephalograms (EEGs) of newborns. The features are designed with the aid of recent advances in modelling of the newborn EEG.The performance of the features is analysed with a database of 500 epochs of newborn EEG (250background/250 seizure). The covariance of the features is also analysed to indicate the redundancy of thefeature set. The results show significant differences in the features between seizure and background EEG. Thecovariance between the features suggests that there is little redundant information between the features. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEG seizure detection en_US
dc.subject background characteristics en_US
dc.subject covariance function en_US
dc.subject data acquisition en_US
dc.subject electroencephalograms en_US
dc.subject feature extraction en_US
dc.subject newborn EEG en_US
dc.subject seizure characteristics en_US
dc.subject statistical testing en_US
dc.subject MBD en_US
dc.subject modified B distribution en_US
dc.subject time-frequency distributions en_US
dc.subject AM/FM en_US
dc.subject TFD en_US
dc.subject instantaneous frequency en_US
dc.subject correlation en_US
dc.subject Hurst exponent en_US
dc.title A Feature Set for EEG Seizure Detection in the Newborn based on Seizure and Background Charactersitics en_US
dc.type Article en_US

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