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Background: Investigation of the functioning of the brain in living systemshas been a major effort amongst scientists and medical practitioners. Amongstthe various disorder of the brain, epilepsy has drawn the most attentionbecause this disorder can affect the quality of life of a person. In this paperwe have reinvestigated the EEGs for normal and epileptic patients usingsurrogate analysis, probability distribution function and Hurst exponent.  Results: Using random shuffled surrogate analysis, we have obtained some ofthe nonlinear features that was obtained by Andrzejak \textit{et al.} [Phys RevE 2001, 64:061907], for the epileptic patients during seizure. Probabilitydistribution function shows that the activity of an epileptic brain isnongaussian in nature. Hurst exponent has been shown to be useful tocharacterize a normal and an epileptic brain and it shows that the epilepticbrain is long term anticorrelated whereas, the normal brain is more or lessstochastic. Among all the techniques, used here, Hurst exponent is found veryuseful for characterization different cases.  Conclusions: In this article, differences in characteristics for normalsubjects with eyes open and closed, epileptic subjects during seizure andseizure free intervals have been shown mainly using Hurst exponent. The H showsthat the brain activity of a normal man is uncorrelated in nature whereas,epileptic brain activity shows long range anticorrelation.

Comparative study of nonlinear properties of EEG signals of a normal person and an epileptic patient