A new approach towards predictability of epileptic seizures: KLT dimension

Rajeshkumar Venugopal; Narayanan Krishnamurthi; Awadhesh Prasad; Andreas Spanias; J. C. Sackellares; L. D. Iasemidis

A new approach towards predictability of epileptic seizures: KLT dimension

Rajeshkumar Venugopal, Narayanan Krishnamurthi, Awadhesh Prasad, Andreas Spanias, J. C. Sackellares, L. D. Iasemidis

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English (US)
Pages (from-to)	123-128
Number of pages	6
Journal	Biomedical Sciences Instrumentation
Volume	39
State	Published - 2003

Keywords

Biomedical signal processing
Electroencephalogram
KLT
Lyapunov exponents
Seizure prediction
T-index
Temporal lobe epilepsy

ASJC Scopus subject areas

Biophysics
Medical Laboratory Technology

Cite this

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abstract = "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.",

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AU - Venugopal, Rajeshkumar

AU - Krishnamurthi, Narayanan

AU - Prasad, Awadhesh

AU - Spanias, Andreas

AU - Sackellares, J. C.

AU - Iasemidis, L. D.

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AB - 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.

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KW - Electroencephalogram

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KW - Lyapunov exponents

KW - Seizure prediction

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A new approach towards predictability of epileptic seizures: KLT dimension

Abstract

Keywords

ASJC Scopus subject areas

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