Amplitude suppression and chaos control in epileptic EEG signals

Kaushik Majumdar, Mark Myers

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In this paper we have proposed a novel amplitude suppression algorithm for EEG signals collected during epileptic seizure. Then we have proposed a measure of chaoticity for a chaotic signal, which is somewhat similar to measuring sensitive dependence on initial conditions by measuring Lyapunov exponent in a chaotic dynamical system. We have shown that with respect to this measure the amplitude suppression algorithm reduces chaoticity in a chaotic signal (EEG signal is chaotic). We have compared our measure with the estimated largest Lyapunov exponent measure by the largelyap function, which is similar to Wolf's algorithm. They fit closely for all but one of the cases. How the algorithm can help to improve patient specific dosage titration during vagus nerve stimulation therapy has been outlined.

Original languageEnglish (US)
Pages (from-to)53-66
Number of pages14
JournalComputational and Mathematical Methods in Medicine
Volume7
Issue number1
DOIs
StatePublished - Mar 1 2006

Fingerprint

Chaos Control
Electroencephalography
Chaos theory
Vagus Nerve Stimulation
Chaotic Dynamical Systems
Largest Lyapunov Exponent
Nerve
Titration
Lyapunov Exponent
Therapy
Epilepsy
Dynamical systems
Initial conditions
Electroencephalogram
Therapeutics

All Science Journal Classification (ASJC) codes

  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Applied Mathematics

Cite this

Amplitude suppression and chaos control in epileptic EEG signals. / Majumdar, Kaushik; Myers, Mark.

In: Computational and Mathematical Methods in Medicine, Vol. 7, No. 1, 01.03.2006, p. 53-66.

Research output: Contribution to journalArticle

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