Beyin osilasyonlarına ilişkin enerji değişimlerinin dalgacık dönüşümü temelli yeni bir yaklaşım ile saptanması ve haritalanması: Epilepsi örneği

Öz

Beyin osilasyonlarının nicel analizi, başta epilepsi olmak üzere çeşitli beyin patolojilerinde beyin dinamiklerinin anlaşılmasına katkıda bulunur. Bu çalışmada dalgacık dönüşümü temelli yeni bir nicel yaklaşım kullanılarak beyin osilasyonlarının enerji değişimlerinin saptanması ve haritalanması amaçlanmıştır. Oluşturulan sinyallerin analizinde EEG’yi dört temel alt frekans bandına ayrıştıran ve ardından bu bantların enerji değerlerini nicelleştiren bir yaklaşım önerilmiştir. Ayrıca, bu enerji değerleri kullanılarak kafa yüzeyi enerji haritaları oluşturulmuştur. Önerilen yöntemi test etmek için CHB-MIT Scalp EEG Database veri tabanından alınan epilepsili hastalara ait EEG kayıtları kullanılmıştır. Analiz edilecek sinyaller nöbet anı ortada olmak üzere nöbet süresi uzunluğu kadar öncesi ve sonrasını kapsayacak şekilde tüm kayıttan ayrılarak hazırlanmıştır. Elde edilen sayısal veriler kullanılarak her bir alt bant enerji yüzdesi için nöbet öncesi, nöbet anı ve nöbet sonrası enerji farklılıkları istatistiksel olarak da karşılaştırılmıştır. Bu çalışmada sunulan yöntemin epilepsi ve diğer beyin patolojileri için kayıtlanan tüm EEG’ler için uygulanarak beyin dinamikleri hakkında bilgi edinilebileceği ve aynı anda çok sayıda montajdan kayıt alınması durumunda beyin patolojilerine yol açan odakların belirlenmesinde diğer beyin görüntüleme yöntemleriyle birlikte kullanılabileceği düşünülmüştür.

Anahtar Kelimeler

• Epilepsi,EEG,Nicel analiz,Beyin enerji haritası,Dalgacık dönüşümü

Determination and mapping of energy changes related to brain oscillations with a new approach based on wavelet transform: An epilepsy example

Öz

The quantitative analysis of brain oscillations has an importance in understanding brain dynamics of several brain pathologies. In this study, it is purposed to determine and map the change in the energy of brain oscillations using a new quantitative approach, based on wavelet transform. An approach, seperating the EEG records to four main sub-band and then quantizing the energy values of them, is suggested. Moreover, energy maps of scalp surface are formed by using these energy values. To test the suggested method, EEG records of epileptic patients which had been obtained from CHB-MIT Scalp EEG database were utilized. The signals which would be analyzed were prepared such that the seizure was in the middle and the signal consists of pre-seizure and post-seizure as long as the seizure time. Then, by using the data obtained, energy differences during pre-seizure, seizure and post-seizure were compared for each sub-band energy percentage. It is thought that the suggested method can be applied to EEGs recorded for epilepsy and other pathologies to be informed about brain dynamics. In addition, in case of getting records simultaneously from several montages, the method can be used for localization of sources causing brain pathologies with other brain imaging techniques.

Anahtar Kelimeler

• Epilepsy,EEG,Quantitative analysis,Brain energy map,Wavelet transform

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