Multichannel-Based Newborn EEG Seizure Detection using Time-Frequency Matched Filter

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Multichannel-Based Newborn EEG Seizure Detection using Time-Frequency Matched Filter

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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 2012-10-18T11:36:39Z
dc.date.available 2012-10-18T11:36:39Z
dc.date.issued 2007
dc.identifier.citation M. S. Khlif, M. Mesbah, B. Boashash, and P. Colditz, "Multichannel-Based Newborn EEG Seizure Detection using Time-Frequency Matched Filter," in Proc. of Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE, 2007, pp. 1265-1268 en_US
dc.identifier.other doi: 10.1109/iembs.2007.4352527
dc.identifier.uri http://hdl.handle.net/10576/10878
dc.description This paper proposes a TF matched filter using a 10 s duration simpler template to detect newborn EEG data for reducing both the computational cost and the rate of false positive (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 In recent years, much effort has been made toward developing computerized methods to detect seizures. In adults, the clinical signs of seizures are well defined and easily recognizable. But in newborns, these signs are either subtle or completely absent. For this reason, the electroencephalogram (EEG) has been the most dependable tool used for detecting seizures in newborns. Considering the non-stationary and multicomponent nature of the EEG signals, timefrequency (TF) based methods were found to be very suitable for the analysis of such signals. Using TF representation of EEG signals allows extracting TF signatures that are characteristic of EEG seizures. In this paper we present a TF method for newborn EEG seizure detection using a TF matched filter. The threshold used to distinguish between seizure and nonseizure is data-dependent and is set using the EEG background. Multichannel geometrical correlation, based on a concept of incidence matrix, was utilized to further enhance the performance of the detector. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject bandpass filter en_US
dc.subject data acquisition en_US
dc.subject data labeling en_US
dc.subject electroencephalogram en_US
dc.subject incidence matrix concept en_US
dc.subject linear frequency modulated pattern en_US
dc.subject multichannel geometrical correlation en_US
dc.subject multichannel-based newborn EEG seizure detection en_US
dc.subject time-frequency matched filter en_US
dc.subject t-f matched filter en_US
dc.subject neonatal EEG en_US
dc.subject seizure spike patterns en_US
dc.subject quadratic TFDs en_US
dc.subject MBD en_US
dc.subject modified B distribution en_US
dc.subject t-f correlation en_US
dc.subject piece-wise linear FM en_US
dc.subject t-f patterns en_US
dc.title Multichannel-Based Newborn EEG Seizure Detection using Time-Frequency Matched Filter en_US
dc.type Article en_US

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