Loading...

Automatic detection of epileptic seizure using time-frequency distributions

Mohseni, H. R ; Sharif University of Technology | 2006

268 Viewed
  1. Type of Document: Article
  2. DOI: 10.1049/cp:20060378
  3. Publisher: 2006
  4. Abstract:
  5. The aim of this work is to introduce a new method based on time frequency distribution for classifying the EEG signals. Some parameters are extracted using time-frequency distribution as inputs to a feed-forward backpropagation neural networks (FBNN). The proposed method had better results with 98.25% accuracy compared to previously studied methods such as wavelet transform, entropy, logistic regression and Lyapunov exponent
  6. Keywords:
  7. Backpropagation ; Curve fitting ; Lyapunov functions ; Neural networks ; Parameter estimation ; Signal processing ; Wavelet transforms ; Automatic detection ; Epileptic seizure ; Feedforward backpropagation neural networks (FBNN) ; Time frequency ; Electroencephalography
  8. Source: IET 3rd International Conference MEDSIP 2006: Advances in Medical, Signal and Information Processing, Glasgow, 17 July 2006 through 19 July 2006 ; Issue 520 , 2006 , Pages 29- ; 0863416586 (ISBN); 9780863416583 (ISBN)
  9. URL: https://digital-library.theiet.org/content/conferences/10.1049/cp_20060378