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Title:
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Time-Frequency Detection of EEG Abnormalities |
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Author:
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Boashash, B; Mesbah, M; Colditz, P
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Abstract:
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The patterns obtained by a TF analysis of newborn EEG seizure signals show a
linear FM or piecewise linear FM characteristic. This suggests a method of seizure
detection and classification in the TF domain. A TF detector is proposed that
involves cross-correlating the TFD of the EEG signal with a template. The design of
the template takes into account the TF characteristics of the EEG seizure extracted
in the TF domain. The performance of this time-frequency detector was tested on
synthetic signals, corresponding to one specific type of seizure pattern (LFM). At the time of publication, the methodology was being extended to deal with LFM
patterns of varying slopes, and with piecewise linear FM patterns. The procedure
will then allow classification within the selected sub-classes.
Another time-frequency approach to newborn EEG seizure detection is described
in [11]. |
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Description:
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This Article shows that the patterns obtained by a TF analysis indicate that newborn EEG seizure signals show a linear FM or piecewise linear FM characteristic. This suggests a method of seizure detection and classification in the TF domain that involves cross-correlating the TFD of the EEG signal with a template.
(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). |
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URI:
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http://hdl.handle.net/10576/10798
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Date:
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2003 |