The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals

Hakan ÖZTÜRK, (Aydın Adnan Menderes University Faculty of Medicine, Department of Biostatistics)
Mevlüt TÜRE, (Adnan Menderes University, Faculty of Medicine, Department of Biostatistics, Aydın, Turkey)
Nefati KIYLIOĞLU, (Aydın Adnan Menderes University Faculty of Medicine, Department of Clinical Neurology)
İmran KURT ÖMÜRLÜ (Aydın Adnan Menderes University Faculty of Medicine, Department of Biostatistics)
Meandros Medical And Dental Journal
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Yıl: 2018 Cilt: 19 Sayı: 4 Sayfa Aralığı: 336 - 344 Metin Dili: İngilizce DOI: 10.4274/meandros.96168 İndeks Tarihi: 06-09-2019

The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals

Öz:
Objective: Electroencephalogram (EEG) signals have been broadly utilized for the diagnosis of epilepsy. Expert physicians must monitor long-term EEG signals that is sometimes difficult and time consuming process for epilepsy diagnosis. In this study, classification performances of support vector machine (SVM) and linear discriminant analysis (LDA), which are widely used in computer supported epilepsy diagnosis, were compared by using wavelet-based features of extracted from EEG signals which were derived in either normal or inter-ictal periods. In addition, principal component analysis (PCA) and independent component analysis (ICA) were used to determine the effects of dimension reduction on classification success. Materials and Methods: The EEG data were sampled from the EEG laboratory of the Department of Neurology and Clinical Neurophysiology in Adnan Menderes University. Study was approved by Local Ethics Committee with protocol number 2016/873. Ten patients with epilepsy and 10 normal were the study group. EEG signals of patients with epilepsy were contains only seizure free- epochs. EEG signals were first decomposed into frequency sub-bands by using discrete wavelet transform (DWT) and then some statistical features were calculated from those to classify it's as normal or epileptic. Results: In classification of the EEG signals, it's as normal or epileptic, we achieved 88.9% accuracy rate using SVM with radial basis function (RBF) kernel without dimension reduction. Conclusion: Results showed that SVM was a powerful tool in classifying EEG signals if it's normal or epileptic.
Anahtar Kelime:

Konular: Tıbbi Araştırmalar Deneysel Genel ve Dahili Tıp Diş Hekimliği Cerrahi

Elektroensefalografi Sinyallerinde Farklı Boyut Indirgeme ve Sınıflandırma Yöntemlerinin Karşılaştırılması

Öz:
Amaç: Bu çalışmada, epileptik ve epileptik olmayan elektroensefalografi (EEG) sinyallerinden elde edilen özniteliklerin boyutlarının temel bileşenler analizi ve bağımsız bileşenler analizi yöntemleri ile indirgenmesinin sınıflandırma başarısı üzerine etkilerinin belirlenmesi ve doğrusal ayırma analizi ile destek vektör makinesi (DVM) yöntemlerinin sınıflandırma performanslarının karşılaştırılması amaçlanmıştır. Gereç ve Yöntemler: Çalışmaya 10 kontrol ve uzman hekim tarafından epilepsi tanısı konmuş 10 hasta olmak üzere toplam 20 kişi dahil edildi. Epilepsi tanısı konmuş hastalardan alınan EEG kayıtları nöbet geçirmedikleri sırada alınan kayıtlardı. Epileptik ve epileptik olmayan sinyalleri sınıflandırmak için ayrık dalgacık dönüşümü ile sinyallerinin spektral analizi gerçekleştirildi ve sınıflandırmada kullanılacak olan öznitelikler elde edildi. Öncelikle özniteliklerin boyutu indirgenmeden, daha sonra temel bileşenler analizi ve bağımsız bileşenler analizi ile indirgenerek sınıflandırma yapıldı. Sınıflandırma doğrusal diskriminant analizi, lineer ve radyal tabanlı çekirdek fonksiyonlarının kullanıldığı DVM yöntemleri ile gerçekleştirildi. Bulgular: EEG sinyallerinin epileptik ya da normal olarak sınıflandırılmasında radyal tabanlı çekirdek fonksiyonunun kullanıldığı DVM ile %88,9 doğruluk oranı elde edildi. Sonuç: DVM yönteminin, epileptik ve normal sinyalleri ayırt etmede kullanılabilecek güçlü bir yöntem olduğu sonucuna varıldı.
Anahtar Kelime:

Konular: Tıbbi Araştırmalar Deneysel Genel ve Dahili Tıp Diş Hekimliği Cerrahi
Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
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APA Ozturk H, TÜRE M, KIYLIOĞLU N, KURT ÖMÜRLÜ İ (2018). The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. , 336 - 344. 10.4274/meandros.96168
Chicago Ozturk Hakan,TÜRE Mevlüt,KIYLIOĞLU Nefati,KURT ÖMÜRLÜ İMRAN The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. (2018): 336 - 344. 10.4274/meandros.96168
MLA Ozturk Hakan,TÜRE Mevlüt,KIYLIOĞLU Nefati,KURT ÖMÜRLÜ İMRAN The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. , 2018, ss.336 - 344. 10.4274/meandros.96168
AMA Ozturk H,TÜRE M,KIYLIOĞLU N,KURT ÖMÜRLÜ İ The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. . 2018; 336 - 344. 10.4274/meandros.96168
Vancouver Ozturk H,TÜRE M,KIYLIOĞLU N,KURT ÖMÜRLÜ İ The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. . 2018; 336 - 344. 10.4274/meandros.96168
IEEE Ozturk H,TÜRE M,KIYLIOĞLU N,KURT ÖMÜRLÜ İ "The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals." , ss.336 - 344, 2018. 10.4274/meandros.96168
ISNAD Ozturk, Hakan vd. "The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals". (2018), 336-344. https://doi.org/10.4274/meandros.96168
APA Ozturk H, TÜRE M, KIYLIOĞLU N, KURT ÖMÜRLÜ İ (2018). The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. Meandros Medical And Dental Journal, 19(4), 336 - 344. 10.4274/meandros.96168
Chicago Ozturk Hakan,TÜRE Mevlüt,KIYLIOĞLU Nefati,KURT ÖMÜRLÜ İMRAN The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. Meandros Medical And Dental Journal 19, no.4 (2018): 336 - 344. 10.4274/meandros.96168
MLA Ozturk Hakan,TÜRE Mevlüt,KIYLIOĞLU Nefati,KURT ÖMÜRLÜ İMRAN The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. Meandros Medical And Dental Journal, vol.19, no.4, 2018, ss.336 - 344. 10.4274/meandros.96168
AMA Ozturk H,TÜRE M,KIYLIOĞLU N,KURT ÖMÜRLÜ İ The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. Meandros Medical And Dental Journal. 2018; 19(4): 336 - 344. 10.4274/meandros.96168
Vancouver Ozturk H,TÜRE M,KIYLIOĞLU N,KURT ÖMÜRLÜ İ The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals. Meandros Medical And Dental Journal. 2018; 19(4): 336 - 344. 10.4274/meandros.96168
IEEE Ozturk H,TÜRE M,KIYLIOĞLU N,KURT ÖMÜRLÜ İ "The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals." Meandros Medical And Dental Journal, 19, ss.336 - 344, 2018. 10.4274/meandros.96168
ISNAD Ozturk, Hakan vd. "The Comparison of Different Dimension Reduction and Classification Methods in Electroencephalogram Signals". Meandros Medical And Dental Journal 19/4 (2018), 336-344. https://doi.org/10.4274/meandros.96168
Sayfa Oluşturulma Tarihi
17-04-2024 11:57

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