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Comparison of Wavelet Transform and FFT Methods in the Analysis of EEG Signals

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Abstract

In this study, whether the wavelet transform method is better for spectral analysis of the brain signals is investigated. For this purpose, as a spectral analysis tool, wavelet transform is compared with fast Fourier transform (FFT) applied to the electroencephalograms (EEG), which have been used in the previous studies. In addition, the time-domain characteristics of the wavelet transform are also detected. The comparison results show that the wavelet transform method is better in detecting brain diseases.

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REFERENCES

  1. Akin, M., Investigation of Excited Brain Potential With Spectral Analysis Methods, Ph.D. Thesis, University of Erciyes, Turkey, 1995.

    Google Scholar 

  2. Arserim, M. A., The Estimation of Brain Signals With Modern Spectral Analysis Methods, Master Thesis, Diyarbakir, Turkey, 2001.

    Google Scholar 

  3. Bruce, A., Donoho, D., and Gao, H.-y., Wavelet analysis. IEEE Spectrum 26, 1996.

  4. Akin, M., Kiymik, M. K., Application of periodogram and AR spectral analysis to EEG signals. J. Med. Syst. 24(4), 2000.

  5. Cromwell, L., Weibell, F. J., and Pfeiffer, E. A., Biomedical Instrumentation and Measurements, Prentice-Hall, Englewood Cliffs, NJ, 1980.

    Google Scholar 

  6. Proakis, J., and Manolakis, D., Digital Signal Processing, Prentice-Hall, Englewood Cliffs, NJ, 1996.

    Google Scholar 

  7. Akin, M., Kiymik, M. K., Arserim, M. A., and Turkoglu, I., Separation of Brain Signals Using FFT and Neural Networks, Biyomut, Istanbul, Turkey, 2000.

    Google Scholar 

  8. Hazarika, N., Classification of EEG signals using the wavelet transform. Signal Processing 59(1):61, May 1997.

    Google Scholar 

  9. Misiti, M., Misiti,Y., Oppenheim,G., and Poggi, J. M.,Wavelet Toolbox Users Guide, The Math Works, Inc. 1996–1997.

  10. Goswami, J., and Chan, A., Fundementals of Wavelets, Wiley, New York, 1999.

    Google Scholar 

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Akin, M. Comparison of Wavelet Transform and FFT Methods in the Analysis of EEG Signals. Journal of Medical Systems 26, 241–247 (2002). https://doi.org/10.1023/A:1015075101937

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  • DOI: https://doi.org/10.1023/A:1015075101937

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