Predictability of epileptic seizures: a comparative study using Lyapunov exponent and entropy based measures

Document Type

Article

Abstract

In this paper, a comparative study involving measures from the theory of chaos, namely the short-term largest Lyapunov exponent, Shannon and Kullback-Leibler entropies from information theory, has been carried out in terms of their predictability of temporal lobe epileptic seizures. These three measures are estimated from electroencephalographic (EEG) recordings with sub-dural and in-depth electrodes from various brain locations in patients with temporal lobe epilepsy. Techniques from optimization theory are applied to select optimal sets of electrodes whose dynamics is then followed over time. Results from analysis of multiple seizures in two epileptic patients with these measures are presented and compared in terms of their ability to identify pre-ictal dynamical entrainment well ahead of seizure onset time.

Medical Subject Headings

Algorithms; Brain (physiopathology); Brain Mapping (methods); Electroencephalography (methods); Epilepsy (diagnosis, physiopathology); Epilepsy, Temporal Lobe (diagnosis, physiopathology); Humans; Models, Neurological; Models, Statistical; Monitoring, Ambulatory (methods); Nonlinear Dynamics; Reproducibility of Results; Sensitivity and Specificity

Publication Date

1-1-2003

Publication Title

Biomedical sciences instrumentation

ISSN

0067-8856

Volume

39

First Page

129

Last Page

35

PubMed ID

12724881

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