Advances in Bioscience and Bioengineering

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Definition of the Instantaneous Frequency of an Electroencephalogram Using the Hilbert Transform

Received: 11 July 2016    Accepted: 05 August 2016    Published: 31 August 2016
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Abstract

Application of methods of signal processing used in radioengineering for electroencephalograms (EEG) provides to increase the information content of the analysis and medical diagnostic quality. In this paper the method of EEG analysis based on the Hilbert transform are considered. Comparing results analysis with the Fourier transform (FT) and wavelet transform (WT) is carried out. Using the Hilbert transform for calculations, the analysis data on the informative parameters of EEG of healthy persons and those of epileptic patients were obtained. The calculated time dependences of the total phase and instantaneous frequency are presented on the diagrams. It is shown that application of the Hilbert transform provides an evident and simple interpretation of EEG diagnostics results. The phase-frequency method of EEG analysis gives an opportunity to track the dynamics of EEG change, to numerically characterize the duration and variation of the basic physiological rhythms, and, also, to observe the frequency change in time within the limits of each rhythm.

DOI 10.11648/j.abb.20160405.11
Published in Advances in Bioscience and Bioengineering (Volume 4, Issue 5, October 2016)
Page(s) 43-50
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Electroencephalogram, Hilbert Transform, Instantaneous Frequency, EEG Rhythms

References
[1] L. P. Zenkov. Clinical electroencephalography (with elements of epileptology) / Doctors’ manual. – M., Medpressinform, 2004-368 p. (in Russian).
[2] Campbell J. et al. On the sufficiency of autocorrelation functions as EEG descriptors // IEEE Trans. Bio-Med. Eng. – 1967. – V. BME-14. – P. 49-52.
[3] Zhang Xizheng, Yin Ling, Wang Weixiong. Wavelet time-frequency Analysis of Electro-encephalogram (EEG) processing // (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 1, No. 5, November 2010. –P. 1-5.
[4] N. D. Devyatkov, O. M. Grindel, I. F. Kharchenko et al. Investigations on the instability of time characteristics of human EEG by the method of phase-frequency analysis // Vestnik Akademii Meditsinskikh Nauk SSSR.-M.: Meditsina.-1973.-45 p. (in Russian).
[5] Yu. I. VoloshchukSignals and processes in radio engineering.- Kharkov: CMIT, 2003, - 444 p. (in Ukrainian).
[6] V. I. Tikhonov Statistical radio engineering.-M.: Sovetskoye Radio, 1966.-678 p. (in Russian).
[7] I. S. Gonorovsky. Radiotechnical circuits and signals.- M.: Sovetskoye Radio, 1966. Vol. 1. – 439 p. (in Russian).
[8] O. I. Kharchenko. Methods of frequency- time analysis in the systems of electroencephalogram-type random signal processing. Ph.D. dissertation on technical sciences.-Kharkov: Kharkov National University of Radio Electronics.- 2007.-253 p. (in Russian).
[9] Sara Marianie. a. EEG segmentation for improving automatic CAP detection // Clinical Neurophysiology Volume 124, Issue 9, September 2013.- P 1815–1823.
[10] Tsuyoshi Inouye, SeigoToi, Yuko Matsumoto A new segmentation method of electroencephalograms by use of Akaike's information criterion // Cognitive Brain Research, Volume 3, Issue 1, December 1995. – P. 33–40.
Author Information
  • Physics and Technology Institute of Plasma Electronics and New Methods of Acceleration, National Science Center Kharkov Institute, Kharkiv, Ukraine

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    Kharchenko Okcana. (2016). Definition of the Instantaneous Frequency of an Electroencephalogram Using the Hilbert Transform. Advances in Bioscience and Bioengineering, 4(5), 43-50. https://doi.org/10.11648/j.abb.20160405.11

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    Kharchenko Okcana. Definition of the Instantaneous Frequency of an Electroencephalogram Using the Hilbert Transform. Adv. BioSci. Bioeng. 2016, 4(5), 43-50. doi: 10.11648/j.abb.20160405.11

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    AMA Style

    Kharchenko Okcana. Definition of the Instantaneous Frequency of an Electroencephalogram Using the Hilbert Transform. Adv BioSci Bioeng. 2016;4(5):43-50. doi: 10.11648/j.abb.20160405.11

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  • @article{10.11648/j.abb.20160405.11,
      author = {Kharchenko Okcana},
      title = {Definition of the Instantaneous Frequency of an Electroencephalogram Using the Hilbert Transform},
      journal = {Advances in Bioscience and Bioengineering},
      volume = {4},
      number = {5},
      pages = {43-50},
      doi = {10.11648/j.abb.20160405.11},
      url = {https://doi.org/10.11648/j.abb.20160405.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.abb.20160405.11},
      abstract = {Application of methods of signal processing used in radioengineering for electroencephalograms (EEG) provides to increase the information content of the analysis and medical diagnostic quality. In this paper the method of EEG analysis based on the Hilbert transform are considered. Comparing results analysis with the Fourier transform (FT) and wavelet transform (WT) is carried out. Using the Hilbert transform for calculations, the analysis data on the informative parameters of EEG of healthy persons and those of epileptic patients were obtained. The calculated time dependences of the total phase and instantaneous frequency are presented on the diagrams. It is shown that application of the Hilbert transform provides an evident and simple interpretation of EEG diagnostics results. The phase-frequency method of EEG analysis gives an opportunity to track the dynamics of EEG change, to numerically characterize the duration and variation of the basic physiological rhythms, and, also, to observe the frequency change in time within the limits of each rhythm.},
     year = {2016}
    }
    

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