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Reseach Article

The Detection of Normal and Epileptic EEG Signals using ANN Methods with Matlab-based GUI

by Gamze Dogali Cetin, Ozdemir Cetin, Mehmet Recep Bozkurt
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 114 - Number 12
Year of Publication: 2015
Authors: Gamze Dogali Cetin, Ozdemir Cetin, Mehmet Recep Bozkurt
10.5120/20034-2145

Gamze Dogali Cetin, Ozdemir Cetin, Mehmet Recep Bozkurt . The Detection of Normal and Epileptic EEG Signals using ANN Methods with Matlab-based GUI. International Journal of Computer Applications. 114, 12 ( March 2015), 45-50. DOI=10.5120/20034-2145

@article{ 10.5120/20034-2145,
author = { Gamze Dogali Cetin, Ozdemir Cetin, Mehmet Recep Bozkurt },
title = { The Detection of Normal and Epileptic EEG Signals using ANN Methods with Matlab-based GUI },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 114 },
number = { 12 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 45-50 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume114/number12/20034-2145/ },
doi = { 10.5120/20034-2145 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:52:37.546380+05:30
%A Gamze Dogali Cetin
%A Ozdemir Cetin
%A Mehmet Recep Bozkurt
%T The Detection of Normal and Epileptic EEG Signals using ANN Methods with Matlab-based GUI
%J International Journal of Computer Applications
%@ 0975-8887
%V 114
%N 12
%P 45-50
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Epilepsy is common neurological disorder disease in the world. Electroencephalogram (EEG) can provide significant information about epileptic activity in human brain. Since detection of the epileptic activity requires analyzing of very length EEG recordings by an expert, researchers tend to improve automated diagnostic systems for epilepsy in recent years. In this work, we try to automate detection of epilepsy using EEG based on Matlab Graphical User Interface (GUI). Three different types of Artificial Neural Networks (ANN), namely, Feed Forward Backpropagation, Cascade and Elman neural networks, are used for the classification EEG (existence of epileptic seizure or not). Before classification process, we use autoregressive model to data reduction and three different AR model algorithms to calculate the coefficients. Developed Matlab-based GUI provides flexible and visual utilization to observe normal/epileptic EEG and test results. Training parameters and type of neural networks are decided by users on the interface. Performance of the proposed model is evaluated using overall accuracy.

References
  1. Adeli H. , Zhou Z. , Dadmehr N. , (2003), "Analysis of EEG records in an epileptic patient using wavelet transform", Journal of Neuroscience Methods, ,123, 69–87.
  2. Agarwal, R. , Gotman, J. , Flanagan, D. , & Rosenblatt, B. (1998). "Automatic EEG analysis during long-term monitoring in the ICU". Electroencephalography and Clinical Neurophysiology 107, 44-58.
  3. Guo L. ,Rivero D. , Dorado J. , Rabu˜nal J. R. , Pazos A. ,(2010) "Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks", Journal of NeuroScience Methods, 191,101-109.
  4. Kumar S. P, Sriraam N. , Benakop P. G. , Jinaga B. C. , 2010, "Entropies based detection of epileptic seizures with artificial neural network classifiers", Expert Systems with Applications, 37, 3284–3291
  5. ?ahin C. , Ogulata S. N. , Aslan K. , Bozdemir H. , Erol R. , 2008, "A Neural Network-Based Classification Model for Partial Epilesy by EEG Signals", International Journal of Pattern Recognition and Artificial Intelligence, Vol. 22, No. 5, pp. 973-985.
  6. Orhan U. , Hekim M. , Ozer M. , 2011, "EEG signals classification using the K-means clustering and a multilayer perceptron neural network model", Expert Systems with Applications, 38, 13475–13481
  7. Batar H. , 2007, "Analysis Of EEG Signals Using The Wavelet Transform And Artificial Neural Network", M. Sc. Thesis, Süleyman Demirel University Graduate School of Applied and Natural Sciences, Isparta, Turkey.
  8. http://www. diytdcs. com/tag/1020-positioning, 29. 01. 2015
  9. Yazgan E. , Korürek M. , 1995. "T?p Elektroni?i", ?stanbul, Turkey.
  10. http://www. earthzense. com/rem-sleep. html, 29. 01. 2015
  11. Eksi Z. , Akgul A. ,Bozkurt M. R. , 2013,"The Classification of EEG Signals Recorded in Drunk and Non-Drunk People",International Journal of Computer Applications (0975-8887),Vol. 68, No. 10.
  12. http://www. slideshare. net/syedirshadmurtaza/ilae-classification-of-seizures-by-murtaza, 29. 01. 2015
  13. Vatansever F. , Do?al? G. , 2011, "Klasik Enterpolasyon Yöntemleri ve Yapay Sinir A?? Yakla??mlar?n?n Kar??la?t?r?lmas?", 6th International Advanced Technologies Symposium (IATS'11), pp. 51-54.
  14. Negishi, M. 1998, "Everything that Linguists have Always Wanted to Know about Connectionism", Department of Cognitive and Neural Systems, Boston University.
  15. Elmas Ç. , 2003, Yapay Sinir A?lar?, Seçkin Yay?nc?l?k, Ankara.
  16. http://www. itl. nist. gov/div898/handbook/pmc/section4/pmc444. htm, 29. 01. 2015
  17. EEG time series are available under http://epileptologie-bonn. de/cms/front_content. php?idcat=193⟨=3, 01. 12. 2014
  18. Ralph K. L. , Andrzejak G. , Mormann F. , Rieke C. , David P. , Elger C. E. , 2001, "Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state", Physical Review E, 64, 061907-1-061907-8
Index Terms

Computer Science
Information Sciences

Keywords

EEG Signals Artificial Neural Network Epilepsy Matlab Graphical User Interface