Sleep Stage Classification Based on Filter Bank Optimization

Oral E. A., Codur M. M., ÖZBEK İ. Y.

25th Signal Processing and Communications Applications Conference (SIU), Antalya, Turkey, 15 - 18 May 2017 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2017.7960715
  • City: Antalya
  • Country: Turkey
  • Keywords: EEG signal, filter hank, SVM, sleep stages
  • Ataturk University Affiliated: Yes

Abstract

Sleep stage binary classification is studied using single channel EEG signals. The proposed approach is composed of two steps. In the first step, cepstrum coefficients based features are obtained from EEC signals using a filter bank approach which is tuned for sleep stage classification in terms of number of filters and their type. In the second step, these features are used with support vector machine approach for classification. It is observed that obtained results are comparable with the published results, and therefore, it is promising.