Title: Improving diagnosis of some brain disease by analysing chaotic indices of EEG signals
Authors: Sarah Nazari; Mohammad Ataei; Ali Tamizi
Addresses: Faculty of Electrical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran ' Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Isfahan, Iran ' Faculty of Electrical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran
Abstract: This paper investigated the effect of Electroencephalogram signals on diagnosis of the possible brain dysfunctions. It is the most common non-offensive way to analyse brain healthiness on the basis of chaotic theory. Normal person's EEG signals are different from the people who suffer from epilepsy, schizophrenia, post-traumatic stress disorder and Alzheimer's diseases in many respects, namely amplitude, frequency, statistical features and in general dynamic behaviour. The findings indicate EEG signals are non-linear and chaotic. EEG signal was considered as chaotic time series in the research. Diagnosis of diseases was conducted using analysis of chaotic parameters. They include Lyapunov exponent and correlation dimension. For this end, appropriate algorithms were rendered to extract necessity parameters for reconstructing phase space and calculated chaotic indices with relative consideration. The findings showed patients are recognised from healthy persons. It was also possible to distinguish two types of epilepsy, namely grand mal and temporal lobe. The results showed acceptable way of predicating epilepsy. Visual diagnosis of disorders by EEG is a big challenge for neurologist as complexity of the brain dysfunctions. This research can be useful for physicians to diagnose and predict diseases.
Keywords: chaotic signals; EEG signals; electroencephalograms; Lyapunov exponents; correlation dimension; epilepsy diagnosis; brain diseases; brain dysfunctions; nonlinear signals; grand mal epilepsy; temporal lobe epilepsy.
DOI: 10.1504/IJBET.2016.081222
International Journal of Biomedical Engineering and Technology, 2016 Vol.22 No.4, pp.349 - 369
Received: 12 Oct 2015
Accepted: 08 Feb 2016
Published online: 29 Dec 2016 *