International Journal of Intelligent Systems and Applications, Volume (6), No (5), Year (2013-5) , Pages (41-46)

Title : ( Qualitative and Quantitative Evaluation of EEG Signals in Epileptic Seizure Recognition )

Authors: Seyyed Abed Hosseini , Mohammad Reza Akbarzadeh Totonchi , Mohammad Bagher Naghibi Sistani ,

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A chaos-ANFIS approach is presented for analysis of EEG signals for epileptic seizure recognition. The non-linear dynamics of the original EEGs are quantified in the form of the hurst exponent (H) and largest lyapunov exponent (λ). The process of EEG analysis consists of two phases, namely the qualitative and quantitative analysis. The classification ability of the H and λ measures is tested using ANFIS classifier. This method is evaluated with using a benchmark EEG dataset, and qualitative and quantitative results are presented. Our inter-ictal EEG based diagnostic approach achieves 97.4% accuracy with using 4-fold cross validation. Diagnosis based on ictal data is also tested in ANFIS classifier, reaching 96.9% accuracy. Therefore, our method can be successfully applied to both inter-ictal and ictal data.

Keywords

, ANFIS, EEG, Hurst Exponent, Lyapunov
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@article{paperid:1043700,
author = {Hosseini, Seyyed Abed and Akbarzadeh Totonchi, Mohammad Reza and Naghibi Sistani, Mohammad Bagher},
title = {Qualitative and Quantitative Evaluation of EEG Signals in Epileptic Seizure Recognition},
journal = {International Journal of Intelligent Systems and Applications},
year = {2013},
volume = {6},
number = {5},
month = {May},
issn = {2074-904X},
pages = {41--46},
numpages = {5},
keywords = {ANFIS; EEG; Hurst Exponent; Lyapunov Exponent},
}

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%0 Journal Article
%T Qualitative and Quantitative Evaluation of EEG Signals in Epileptic Seizure Recognition
%A Hosseini, Seyyed Abed
%A Akbarzadeh Totonchi, Mohammad Reza
%A Naghibi Sistani, Mohammad Bagher
%J International Journal of Intelligent Systems and Applications
%@ 2074-904X
%D 2013

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