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

Shivkumar Sabesan, Narayanan Krishnamurthi, Awadhesh Prasad, Andreas Spanias, J. C. Sackellares, L. D. Iasemidis

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)129-135
Number of pages7
JournalBiomedical Sciences Instrumentation
Volume39
StatePublished - 2003

Keywords

  • Chaos
  • Epileptic seizures
  • Kullback-Leibler Entropy
  • Lyapunov Exponent
  • Optimization
  • Predictability
  • Shannon Entropy

ASJC Scopus subject areas

  • Biophysics
  • Medical Laboratory Technology

Fingerprint Dive into the research topics of 'Predictability of epileptic seizures: A comparative study using Lyapunov exponent and entropy based measures'. Together they form a unique fingerprint.

Cite this