Detection of neonatal EEG seizure using multichannel matching pursuit

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Detection of neonatal EEG seizure using multichannel matching pursuit

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dc.contributor.author Khlif, M.S.
dc.contributor.author Mesbah, M
dc.contributor.author Boashash, B
dc.contributor.author Colditz, P
dc.date.accessioned 2012-03-21T06:03:24Z
dc.date.available 2012-03-21T06:03:24Z
dc.date.issued 2008-08
dc.identifier.citation Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE Issue Date : 20-25 Aug. 2008 On page(s): 907 - 910 en_US
dc.identifier.isbn 978-1-4244-1814-5
dc.identifier.issn 1557-170X
dc.identifier.other Digital Object Identifier : 10.1109/IEMBS.2008.4649301
dc.identifier.other E-ISBN : 978-1-4244-1815-2
dc.identifier.uri http://hdl.handle.net/10576/10809
dc.description This paper defines a new structural complexity measure (SCM) for neonatal seizure detection, based on the MP decomposition of EEG using QTFDs, resulting in 4% reduction in overall FPR. (Additional details can be found in the comprehensive book on Time-Frequency Signal Analysis and Processing (see http://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 It is unusual for a newborn to have the classic “tonic-clonic” seizure experienced by adults and older children. Signs of seizure in newborns are either subtle or may become clinically silent. Therefore, the electroencephalogram (EEG) is becoming the most reliable tool for detecting neonatal seizure. Being non-stationary and multicomponent, EEG signals are suitably analyzed using time-frequency (TF) based methods. In this paper, we present a seizure detection method using a new measure based on the matching pursuit (MP) decomposition of EEG data. Signals are represented in the TF domain where seizure structural characteristics are extracted to form a new coherent TF dictionary to be used in the MP decomposition. A new approach to set data-dependent thresholds, used in the seizure detection process, is proposed. To enhance the performance of the detector, the concept of areas of incidence is utilized to determine the geometrical correlation between EEG recording channels. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Epilepsy en_US
dc.subject Matching pursuit algorithms en_US
dc.subject Pediatrics en_US
dc.subject Signal analysis en_US
dc.subject Signal design en_US
dc.subject Artificial Intelligence en_US
dc.subject Diagnosis en_US
dc.subject Computer-Assisted en_US
dc.subject Electroencephalography en_US
dc.subject Humans en_US
dc.subject Infant en_US
dc.subject Newborn en_US
dc.subject Pattern Recognition en_US
dc.subject Automated en_US
dc.subject Reproducibility of Results en_US
dc.subject Seizures en_US
dc.subject Sensitivity and Specificity en_US
dc.subject Matching pursuit en_US
dc.subject Quadratic TFDs en_US
dc.subject time-frequency analysis en_US
dc.subject linear FM signal en_US
dc.subject newborn seizure detection en_US
dc.subject multichannel EEG channel en_US
dc.subject instantaneous frequency en_US
dc.subject time-frequency correlation en_US
dc.subject time-frequency signal processing en_US
dc.subject time-frequency distributions en_US
dc.title Detection of neonatal EEG seizure using multichannel matching pursuit en_US
dc.type Article en_US

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