EEG Signal of Epiliptic Patient by Fast Fourier and Wavelet Transforms

Authors

  • Goh Chien Yong Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru Johor, Malaysia
  • Normah Maan Ibnu Sina Institute for Fundamental Science Studies, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru Johor, Malaysia
  • Tahir Ahmad Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v61.1617

Keywords:

Electroencephalography (EEG), Fast Fourier Transform (FFT), Wavelet Transform (WT)

Abstract

Electroencephalography (EEG) is one of the field in diagnosing g epilepsy. Analysis of the EEG records can provide valuable insight and improve understanding of the mechanisms causing epileptic disorders. In this paper, the fast Fourier transform (FFT) and wavelet transform are used as spectral analysis tools of the EEG signals. These methods are chosen because they provide time–frequency shifted on the EEG signals. Since the frequency characteristics are important information that can be observed from the signals, FFT and wavelet transform are among a the best methods in analysis of EEG signals. The comparisons between these two methods are also carried out. Result showed that the wavelet transform is better than FFT in analysis of EEG signals. A software for analysing EEG signal is also developed using C++ programming. The software is able to compute and show the results of the analysis signal data by both of the two methods in graphical form.

References

[1] Tyner, F. S., Knott, R. J., Mayer, W. B. J. 1983. Fundamentals of EEG

Technology, Volume 1: Basic Concepts and Methods. New York:

Raven Press.

Swartz, B. E., Goldensohn, E. S. 1998. Timeline of the History of EEG

and Associated Fields. Electroencephalography and Clinical

Neurophysiology. 106. 173–176.

Adeli, H., Zhou, Z., Dadmehr, N. 2003. Analysis of EEG records in an

epileptic patient using wavelet transform. Journal of Neuroscience

Methods. 123(1). 69–87.

Akin, M. 2002. Comparison of Wavelet Transform and FFT Methods

in the Analysis of EEG Signals. Journal of Medical Systems. 26(3).

–247.

Hazarika, N. 1997. Classification of EEG signals using the wavelet

transform. Signal Processing. 59(1). 61.

Cooley, J. W., Tukey, J. W. 1965. An algorithm for machine

calculation of complex Fourier series. Math Comp. 19: 297–301.

Soman, K. P., Ramachandran, K. I. 2005. Insight into Wavelets - From

Theory to Practice. Second Edition. New Delhi: Prentice-Hall India.

Downloads

Published

2013-02-15

Issue

Section

Science and Engineering

How to Cite

EEG Signal of Epiliptic Patient by Fast Fourier and Wavelet Transforms. (2013). Jurnal Teknologi, 61(1). https://doi.org/10.11113/jt.v61.1617