Analysis of spike-wave discharges in rats using discrete wavelet transform.
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.
Ubeyli
Elif Derya
ED
Department of Electrical and Electronics Engineering, Faculty of Engineering, TOBB Ekonomi ve Teknoloji Universitesi, 06530 Söğütözü, Ankara, Turkey. edubeyli@etu.edu.tr
Ilbay
Gül
G
Sahin
Deniz
D
Ateş
Nurbay
N
D000465:Algorithms; D000818:Animals; D001921:Brain / Q000473:pathology*; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000628:therapy; D008297:Male; D015233:Models, Statistical; D051381:Rats; D017208:Rats, Wistar; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors