Time-Frequency Methodology for Newborn Electroencephalographic Seizure Detection

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Time-Frequency Methodology for Newborn Electroencephalographic Seizure Detection

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dc.contributor.author Boashash, B
dc.contributor.author Mesbah, M
dc.date.accessioned 2012-06-18T05:59:46Z
dc.date.available 2012-06-18T05:59:46Z
dc.date.issued 2002-10
dc.identifier.citation B. Boashash and M. Mesbah, "Time-Frequency Methodology for Newborn Electroencephalographic Seizure Detection” in A. Papandreou-Suppappola, editor, Applications in Time-Frequency Signal Processing, CRC Press, Chapter 9, pp. 339-369, October , 2002 en_US
dc.identifier.uri http://hdl.handle.net/10576/10839
dc.description This chapter shows that the TF domain is the preferable approach to develop a complete EEG seizure detection scheme with illustration on newborn seizure.identification. (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).
dc.description.abstract Techniques previously designed for electroencephalographic (EEG) seizure detection in the newborn have been relatively inefficient due to their incorrect assumption of local stationarity of the EEG. To overcome the problem raised by" the proven nonstationarity of the EEG signal, current methods are extended to a time-frequency (TF) approach [8, 10]. This allows the analysis and characterization of the different newborn EEG patterns, the first step toward an automatic TF seizure detection and classification. An in-depth analysis of the previously proposed autocorrelation and spectrum seizure detection techniques identified the detection criteria that can be readily extended to the TF domain. We present the various patterns of observed TF seizure signals and relate them to current specialist knowledge of seizures. In particular, initial results indicate that a quasilinear instantaneous frequency (IF) can be used as a critical feature of the EEG seizure characteristics. These findings led to propose a TF-based seizure detector. This detector performs a two-dimensional (2D) correction between the EEG signal and a reference template selected as a model of the EEG seizure in TF domain. en_US
dc.language.iso en en_US
dc.publisher CRC Press en_US
dc.subject Time-Frequency analysis
dc.subject EEG
dc.subject seizure detection
dc.subject Newborn
dc.subject time-frequency distribution
dc.subject quadratic TFD
dc.subject time-frequency matched filter
dc.subject instantaneous frequency
dc.subject multicomponent IF
dc.subject non-stationary signals
dc.subject MBD
dc.subject modified B distribution;
dc.subject t-f domain
dc.subject time-frequency calibration
dc.subject LFM
dc.subject linear frequency modulation
dc.subject piece-wise LFM
dc.subject seizure patterns
dc.subject feature extraction
dc.subject background pattern
dc.subject burst suppression
dc.subject neonate abnormalities
dc.title Time-Frequency Methodology for Newborn Electroencephalographic Seizure Detection en_US
dc.type Book chapter en_US

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