Seizure Detection Using Parameter Estimation and Morlet Wavelet Transform

The EEG signals prove to be an efficient tool in analyzing Epileptic seizure. The parameters like mean, standard deviation and their confidence interval of the seizure EEG signal are compared with the normal EEG signal. The seizure EEG signals have higher values of parameter estimates when compared...

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Bibliographic Details
Published inGlobal Trends in Information Systems and Software Applications pp. 674 - 679
Main Authors Prince, P. Grace Kanmani, Rani Hemamalini, R.
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesCommunications in Computer and Information Science
Subjects
EEG signals
Epileptic Seizure
parameter estimation
wavelet transform
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Summary:The EEG signals prove to be an efficient tool in analyzing Epileptic seizure. The parameters like mean, standard deviation and their confidence interval of the seizure EEG signal are compared with the normal EEG signal. The seizure EEG signals have higher values of parameter estimates when compared to the normal EEG signals. In this paper Morlet wavelet transform is also performed on the EEG signals. Significant variations are observed in the Morlet coefficient of the seizure EEG when compared to the normal EEG signal.
ISBN:3642292151
9783642292156
ISSN:1865-0929
1865-0937
DOI:10.1007/978-3-642-29216-3_73