Classification of epileptic and healthy individual EEG signals using neural networks Epileptik ve saghkh birey eeg sinyallerinin sinir aglan kullamlarak simflandinlmasi

Aykat S., Senan S., Ensari T.

5th International Conference on Computer Science and Engineering, UBMK 2020, Diyarbakır, Türkiye, 9 - 10 Eylül 2020, ss.47-51, (Tam Metin Bildiri) identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/ubmk50275.2020.9219474
  • Basıldığı Şehir: Diyarbakır
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.47-51
  • Anahtar Kelimeler: EEG Signal, Artificial Neural Networks, Wavelet Transform, WAVELET, SEIZURE
  • İstanbul Üniversitesi-Cerrahpaşa Adresli: Evet

Özet

© 2020 IEEE.Electroencephalogram (EEG) are signals used for the analysis of the electrical and functional activity of the brain. These signals are commonly used to detect epileptic seizures. The aim of this study is to classify healthy and epileptic individual EEG signals using artificial neural networks (ANN). For this purpose, the open data source of the University of Bonn was used. The success rates of the classification results obtained with the designed ANN model show the effectiveness of this ANN structure in the application under consideration.