A new approach towards predictability of epileptic seizures: KLT dimension

This paper proposes a measure of complexity of the epileptic electroencephalogram (EEG) based on the dimensionality of the Karhunen-Loeve Transform (KLT) in the time domain. We estimate the KLT dimensionality by assuming the same observation noise level in the EEG during the interictal period (betwe...

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Bibliographic Details
Published inBiomedical sciences instrumentation Vol. 39; p. 123
Main Authors Venugopal, Rajeshkumar, Narayanan, K, Prasad, Awadhesh, Spanias, A, Sackellares, J C, Iasemidis, L D
Format Journal Article
LanguageEnglish
Published United States 2003
Subjects
Algorithms
Brain - physiopathology
Brain Mapping - methods
Cerebral Cortex - physiopathology
Electroencephalography - methods
Epilepsy - diagnosis
Epilepsy - physiopathology
Hippocampus - physiopathology
Humans
Linear Models
Models, Neurological
Monitoring, Ambulatory - methods
Quality Control
Reproducibility of Results
Sensitivity and Specificity
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Summary:This paper proposes a measure of complexity of the epileptic electroencephalogram (EEG) based on the dimensionality of the Karhunen-Loeve Transform (KLT) in the time domain. We estimate the KLT dimensionality by assuming the same observation noise level in the EEG during the interictal period (between the seizures) as the one during an epileptic seizure (ictal period). Utilizing an optimality criterion based on the T-index [1] and the predictability time, derived from the created KLT dimensionality profiles, we show that 10 out of 15 seizures in one patient with temporal lobe epilepsy were predictable with an average predictability time of about 36 minutes.
ISSN:0067-8856