Comparison of STFT and wavelet transform methods in determining epileptic seizure activity in EEG signals for real-time application.
Electroencephalography (EEG) is widely used in clinical settings to investigate neuropathology. Since EEG signals contain a wealth of information about brain functions, there are many approaches to analyzing EEG signals with spectral techniques. In this study, the short-time Fourier transform (STFT) and wavelet transform (WT) were applied to EEG signals obtained from a normal child and from a child having an epileptic seizure. For this purpose, we developed a program using Labview software. Labview is an application development environment that uses a graphical language G, usable with an online applicable National Instruments data acquisition card. In order to obtain clinically interpretable results, frequency band activities of delta, theta, alpha and beta signals were mapped onto frequency-time axes using the STFT, and 3D WT representations were obtained using the continuous wavelet transform (CWT). Both results were compared, and it was determined that the STFT was more applicable for real-time processing of EEG signals, due to its short process time. However, the CWT still had good resolution and performance high enough for use in clinical and research settings.
Kiymik
M Kemal
MK
Department of Electric and Electronic Engineering, Kahramanmaraş Sütçü Imam University, 46100 Kahramanmaraş, Turkey.
Güler
Inan
I
Dizibüyük
Alper
A
Akin
Mehmet
M
D002675:Child, Preschool; D019295:Computational Biology; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000706:statistics & numerical data*; D004827:Epilepsy / Q000175:diagnosis* / Q000503:physiopathology; D005583:Fourier Analysis; D006801:Humans; D007223:Infant