Title: Complexity analysis of electroencephalogram records of epileptic patients using Hurst exponent

Authors: K.P. Indiradevi, Elizabeth Elias, P.S. Sathidevi

Addresses: Department of Electronics and Communication Engineering, National Institute of Technology Calicut, NIT Campus, (P.O), Calicut – 673 601, Kerala, India. ' Department of Electronics and Communication Engineering, National Institute of Technology Calicut, NIT Campus, (P.O), Calicut – 673 601, Kerala, India. ' Department of Electronics and Communication Engineering, National Institute of Technology Calicut, NIT Campus, (P.O), Calicut – 673 601, Kerala, India

Abstract: Approximately 1% of the world|s population suffers from epilepsy. Antiepileptic drugs can control two thirds of affected patients and only 8% of people may be cured from epilepsy surgery. The remaining 25% of epileptic patients cannot be treated by any available therapy. Many antiepileptic drugs have side effects and reduce efficiency of other medications. Surgery is the last resort since many complications are reported. Hence, if it is possible to forecast random and unforeseen seizures, it will be helpful to improve the therapeutic possibilities, thereby the quality of epileptic patient|s life can be improved. In this study, complexity of epileptic EEG signal is evaluated by estimating the Hurst exponent (H). It was found that Hurst exponent significantly increases before seizure and its value decreases after seizure. Hence, we believe that these properties could be used for the prediction of a number of epileptic seizures. The proposed algorithm has been implemented in MATLAB.

Keywords: epilepsy; Hurst exponent; seizure prediction; epilepsy self-similar process; wavelet transform; electroencephalogram; epileptic EEG signals; epileptic seizures; medical engineering; patient records.

DOI: 10.1504/IJMEI.2009.022647

International Journal of Medical Engineering and Informatics, 2009 Vol.1 No.3, pp.368 - 380

Published online: 22 Jan 2009 *

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