Brain Activity Characterization by Entropic Clustering of EEG Signals

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Olcay B. O., Karacali B., Ozgoren M., GÜDÜCÜ Ç.

25th Signal Processing and Communications Applications Conference (SIU), Antalya, Türkiye, 15 - 18 Mayıs 2017, (Tam Metin Bildiri)

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/siu.2017.7960503
  • Basıldığı Şehir: Antalya
  • Basıldığı Ülke: Türkiye
  • Anahtar Kelimeler: Electroencephalography, Mutual Information, Entropy, Hierarchical Clustering
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

In this study, two novel entropy and mutual information based algorithms have been proposed to characterize the stimulus specific brain activity. In the first method, inter channel mutual information of electroencephalography signals has been calculated and the channels that exhibit synchronized behaivour during stimulus. In the second method, the responsiveness of the individual channels has been characterized in an entropic manner and then, the channels which demonstrates stimulus specific entropic behavior have been obtained. The performance of the proposed methods has been simulated on a real dataset obtained from Dokuz Eylul University Brain Biophysics laboratory. The results demonstrate that different regions of the brain exhibit a coherent activity during stimulus.