Computational and Mathematical Methods in Medicine

Computational and Mathematical Methods in Medicine / 2006 / Article

Open Access

Volume 7 |Article ID 639317 |

Kaushik Majumdar, Mark H. Myers, "Amplitude Suppression and Chaos Control in Epileptic EEG Signals", Computational and Mathematical Methods in Medicine, vol. 7, Article ID 639317, 14 pages, 2006.

Amplitude Suppression and Chaos Control in Epileptic EEG Signals

Revised26 May 2006
Accepted05 Jun 2006


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.

Copyright © 2006 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

More related articles

 PDF Download Citation Citation
 Order printed copiesOrder

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.