Analysis of spike-wave discharges in rats using discrete wavelet transform

Ubeyli E. D., Ilbay G., ŞAHİN D., ATEŞ N.

COMPUTERS IN BIOLOGY AND MEDICINE, vol.39, no.3, pp.294-300, 2009 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 39 Issue: 3
  • Publication Date: 2009
  • Doi Number: 10.1016/j.compbiomed.2009.01.004
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.294-300
  • Keywords: Discrete wavelet transform, Wavelet coefficients, Spike-wave discharges, WAG/Rij rats, ABSENCE EPILEPSY, WAG/RIJ RATS, STRAIN, EEG, CLASSIFICATION, NETWORK, MODELS
  • Kocaeli University Affiliated: Yes


A feature is a distinctive or characteristic measurement, transform, structural component extracted from a segment of a pattern. Features are used to represent patterns with the goal of minimizing the loss of important information. The discrete wavelet transform (DWT) as a feature extraction method was used in representing the spike-wave discharges (SWDs) records of Wistar Albino Glaxo/Rijswijk (WAG/Rij) rats. The SWD records of WAG/Rij rats were decomposed into time-frequency representations using the DWT and the statistical features were calculated to depict their distribution. The obtained wavelet coefficients were used to identify characteristics of the signal that were not apparent from the original time domain signal. The present study demonstrates that the wavelet coefficients are useful in determining the dynamics in the time-frequency domain of SWD records. (c) 2009 Elsevier Ltd. All rights reserved.