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Fokal ve Fokal Olmayan EEG Sinyallerinin Sınıflandırılması

Year 2021, Volume: 17 Issue: 1, 20 - 29, 30.06.2021

Abstract

Epilepsi beyinde bulunan nöronlarda ani ve kontrolsüz boşalmalar sonucu oluşan nörofizyolojik bir hastalıktır. Dünya üzerinde birçok insan epilepsi hastalığından muzdariptir. Fokal (F) ve Fokal olmayan (NF) bölgelerin Elektroensefalogram (EEG) sinyalleri üzerinden otomatik olarak sınıflandırılması epilepsi hastalığının teşhisinde önemli bir yere sahiptir. Önerilen çalışmada F ve NF EEG sinyallerinin dalgacık katsayıları için Ayrık Dalgacık Dönüşümü kullanılmıştır. Bu katsayılardan Shannon Entropi, Log Enerji Entropi, Aritmetik Ortalama ve Medyan olarak dört özellik çıkarılmıştır. Bu özellikler WEKA (bilgi analizi için wikato ortamı) programında yer alan Lojistik Regresyon (LR) ve Destek Vektör Makineleri (SVM) algoritmaları ile sınıflandırılmıştır. Yapılan bu sınıflandırmalar sonucunda LR ve SVM sırasıyla %81 ve %83 sınıflandırma doğruluğu elde edilmiştir.

References

  • Referans1 Fisher, RS., Van Emde Boas, W., Blume, W., et al., “Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE).”, Epilepsia, 46(4)., 470-2., 2005.
  • Referans2 http://www.who.int/news-room/fact-sheets/detail/epilepsy. World Health Organization, World Health Organization, 10.10.2020.
  • Referans3 Savic, I., Thorell, JO., & Roland, P., “[11C] flumazenil positron emission tomography visualizes frontal epileptogenic regions.”, Epilepsia, 36(12), 1225-1232, 1995.
  • Referans4 Newton, M.R., Berkovic, S.F., Austin, M.C., Row, C.C., McKay, W. J., & Bladin, P.F., “SPECT in the localisation of extratemporal and temporal seizure foci”, Journal of Neurology, Neurosurgery & Psychiatry, 59(1), 26-30, 1995.
  • Referans5 Seeck, M., Lazeyras, F. C., Michel, M., Blanke, O., Gericke, C. A., Ives, J., & Landis, T., “Non-invasive epileptic focus localization using EEG-triggered functional MRI and electromagnetic tomography”, Electroencephalography and clinical Neurophysiology, 106(6), 508-512, 1998.
  • Referans6 Acharya, U.R., Hagiwara, Y., Despande, S.N., Suren, S., Koh, J.E.W., Oh, S.L., Arunkumar, N., Ciaccio, E.J., Lim, C.M., "Characterization of focal EEG signals: A review", Future Generation Computur Systems, 91, 290-299, 2019.
  • Referans7 Sharma, R., Kumar, M., Pachori, R.B., Acharya, U.R., "Decision support system for focal EEG signals using tunable-Q wavelet transform", Journal of Computational Science, 20, 52-60, May 2017.
  • Referans8 Andrzejak, R.G., Schindler, K., Rummel, C., "Nonrandomness nonlinear dependence and nonstationarity of electroencephalographic recordings from epilepsy patients", Physical Review E, 86, 046206, 2012.
  • Referans9 Kaya, Y., Uyar, M., Tekin, R., Yıldırım, S., “1D-local binary pattern based feature extraction for classification of epileptic EEG signals”, Applied Mathematics and Computation, 243, 209-219, 2014.
  • Referans10 Arunkumar, N., Ram Kumar, K., Venkataraman, V., "Entropy features for focal EEG and nonfocal EEG", J. Comput. Sci, 27, 440-444, 2018.
  • Referans11 Bhattacharyya, A., Sharma, M., and Bilas, R., “A novel approach for automated detection of focal EEG signals using empirical wavelet transform,” Neural Comput. Appl., 29(8), 47–57, 2018.
  • Referans12 Singh, P., Pachori, R.B., "Classification of focal and nonfocal EEG signals using features derived from Fourier-based rhythms", Journal of Mechanics in Medicine and Biology, 17(07), 2017.
  • Referans13 Prasanna, J., Sairamya, N.J., George, S.T., Vinutha, C.R., and Subathra, M.S.P., “Classification of Non-focal and Focal EEG signals using Local Binary Pattern”, International Conference on Computer Communication and Informatics (ICCCI), 1-4, IEEE, 2019.
  • Referans14 Das, A.B., Bhuiyan, M.I.H., “Discrimination and classification of focal and non-focal EEG signals using entropy-based features in the EMD-DWT domain”, Biomedical Signal Processing Control, 11-21, 2016.
  • Referans15 Daubechies, I., “The wavelet transform, timefrequency localization and signal analysis”, IEEE Transactions on Information Theory, 36(5), 961- 1005, 1990.
  • Referans16 Serap, A., Hamdi, M.S., Sadık, K., “Log energy entropy-based EEG classification with multilayer neural network in seizure”, Annals of Biomedical Engineering, 37(12); 2009.
  • Referans17 Behshad, H., Moradi, M.H., and Rostami, R., “Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal” Computer methods and programs in biomedicine, 109.3, 339-345., 2013.
  • Referans18 Sezer, O.G., Erçil, A., Keskinöz, M., “Destek Vektör Makinesi Kullanarak Bağımsız Bileşen Tabanlı 3B Nesne Tanıma”, 2005.
  • Referans19 Siyah, B. “Destek Vektör Makineleri ve Çok Katmanlı Algılayıcılar ile Göğüs Kanseri Teşhisi”.
  • Referans20 Vapnik, V., “Statistical Learning Theory”, Wiley, New York, 1998.
  • Referans21 Chen, D., Wan, S., and Bao, F.S., "Epileptic Focus Localization Using Discrete Wavelet Transform Based on Interictal Intracranial EEG", IEEE Transactions on Neural Systems and Rehabilitation Engineering, 4320, 1-12, 2016.
  • Referans22 Itakura, T., Tanaka, T., A., Dataset, "Epileptic Focus Localization Based on Bivariate Empirical Mode Decomposition and Entropy", AsiaPacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 1426-1429, December 2017.
  • Referans23 Fasil, O.K., Rajesh, R., & Thasleema, T.M., “Influence of differential features in focal and non-focal EEG signal classification”, IEEE Region 10 Humanitarian Technology Conference, 646-649, 2017.
Year 2021, Volume: 17 Issue: 1, 20 - 29, 30.06.2021

Abstract

References

  • Referans1 Fisher, RS., Van Emde Boas, W., Blume, W., et al., “Epileptic seizures and epilepsy: definitions proposed by the International League Against Epilepsy (ILAE) and the International Bureau for Epilepsy (IBE).”, Epilepsia, 46(4)., 470-2., 2005.
  • Referans2 http://www.who.int/news-room/fact-sheets/detail/epilepsy. World Health Organization, World Health Organization, 10.10.2020.
  • Referans3 Savic, I., Thorell, JO., & Roland, P., “[11C] flumazenil positron emission tomography visualizes frontal epileptogenic regions.”, Epilepsia, 36(12), 1225-1232, 1995.
  • Referans4 Newton, M.R., Berkovic, S.F., Austin, M.C., Row, C.C., McKay, W. J., & Bladin, P.F., “SPECT in the localisation of extratemporal and temporal seizure foci”, Journal of Neurology, Neurosurgery & Psychiatry, 59(1), 26-30, 1995.
  • Referans5 Seeck, M., Lazeyras, F. C., Michel, M., Blanke, O., Gericke, C. A., Ives, J., & Landis, T., “Non-invasive epileptic focus localization using EEG-triggered functional MRI and electromagnetic tomography”, Electroencephalography and clinical Neurophysiology, 106(6), 508-512, 1998.
  • Referans6 Acharya, U.R., Hagiwara, Y., Despande, S.N., Suren, S., Koh, J.E.W., Oh, S.L., Arunkumar, N., Ciaccio, E.J., Lim, C.M., "Characterization of focal EEG signals: A review", Future Generation Computur Systems, 91, 290-299, 2019.
  • Referans7 Sharma, R., Kumar, M., Pachori, R.B., Acharya, U.R., "Decision support system for focal EEG signals using tunable-Q wavelet transform", Journal of Computational Science, 20, 52-60, May 2017.
  • Referans8 Andrzejak, R.G., Schindler, K., Rummel, C., "Nonrandomness nonlinear dependence and nonstationarity of electroencephalographic recordings from epilepsy patients", Physical Review E, 86, 046206, 2012.
  • Referans9 Kaya, Y., Uyar, M., Tekin, R., Yıldırım, S., “1D-local binary pattern based feature extraction for classification of epileptic EEG signals”, Applied Mathematics and Computation, 243, 209-219, 2014.
  • Referans10 Arunkumar, N., Ram Kumar, K., Venkataraman, V., "Entropy features for focal EEG and nonfocal EEG", J. Comput. Sci, 27, 440-444, 2018.
  • Referans11 Bhattacharyya, A., Sharma, M., and Bilas, R., “A novel approach for automated detection of focal EEG signals using empirical wavelet transform,” Neural Comput. Appl., 29(8), 47–57, 2018.
  • Referans12 Singh, P., Pachori, R.B., "Classification of focal and nonfocal EEG signals using features derived from Fourier-based rhythms", Journal of Mechanics in Medicine and Biology, 17(07), 2017.
  • Referans13 Prasanna, J., Sairamya, N.J., George, S.T., Vinutha, C.R., and Subathra, M.S.P., “Classification of Non-focal and Focal EEG signals using Local Binary Pattern”, International Conference on Computer Communication and Informatics (ICCCI), 1-4, IEEE, 2019.
  • Referans14 Das, A.B., Bhuiyan, M.I.H., “Discrimination and classification of focal and non-focal EEG signals using entropy-based features in the EMD-DWT domain”, Biomedical Signal Processing Control, 11-21, 2016.
  • Referans15 Daubechies, I., “The wavelet transform, timefrequency localization and signal analysis”, IEEE Transactions on Information Theory, 36(5), 961- 1005, 1990.
  • Referans16 Serap, A., Hamdi, M.S., Sadık, K., “Log energy entropy-based EEG classification with multilayer neural network in seizure”, Annals of Biomedical Engineering, 37(12); 2009.
  • Referans17 Behshad, H., Moradi, M.H., and Rostami, R., “Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal” Computer methods and programs in biomedicine, 109.3, 339-345., 2013.
  • Referans18 Sezer, O.G., Erçil, A., Keskinöz, M., “Destek Vektör Makinesi Kullanarak Bağımsız Bileşen Tabanlı 3B Nesne Tanıma”, 2005.
  • Referans19 Siyah, B. “Destek Vektör Makineleri ve Çok Katmanlı Algılayıcılar ile Göğüs Kanseri Teşhisi”.
  • Referans20 Vapnik, V., “Statistical Learning Theory”, Wiley, New York, 1998.
  • Referans21 Chen, D., Wan, S., and Bao, F.S., "Epileptic Focus Localization Using Discrete Wavelet Transform Based on Interictal Intracranial EEG", IEEE Transactions on Neural Systems and Rehabilitation Engineering, 4320, 1-12, 2016.
  • Referans22 Itakura, T., Tanaka, T., A., Dataset, "Epileptic Focus Localization Based on Bivariate Empirical Mode Decomposition and Entropy", AsiaPacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 1426-1429, December 2017.
  • Referans23 Fasil, O.K., Rajesh, R., & Thasleema, T.M., “Influence of differential features in focal and non-focal EEG signal classification”, IEEE Region 10 Humanitarian Technology Conference, 646-649, 2017.
There are 23 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Bayram Karaman 0000-0002-2448-0219

Ayşegül Güven

Publication Date June 30, 2021
Submission Date March 7, 2021
Published in Issue Year 2021 Volume: 17 Issue: 1

Cite

APA Karaman, B., & Güven, A. (2021). Fokal ve Fokal Olmayan EEG Sinyallerinin Sınıflandırılması. Electronic Letters on Science and Engineering, 17(1), 20-29.