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Annals of Biomedical Engineering

, Volume 23, Issue 5, pp 608–611 | Cite as

Analysis of EEG transients by means of matching pursuit

  • P. J. Durka
  • K. J. Blinowska
Invited Articles

Abstract

Matching pursuit (MP), a new technique of time-frequency signal analysis, was applied to simulated signals and the awake and sleep EEG. With the MP algorithm, waveforms from a very large class of functions were fitted to the local signal structures in a recursive procedure. By means of this technique, sleep spindles were localized in the time-frequency plane with high precision, and their intensities and time spans were found. The MP technique makes following the temporal evolution of transients and their propagation in brains possible. It opens up new possibilities in EEG research providing a means of investigation of dynamic processes in brains in a much finer time-frequency scale than any other method available at present.

Keywords

Matching Pursuit Wavelet analysis EEG Sleep spindles 

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References

  1. 1.
    Davis, G., S. Mallat, and Z. Zhang. Adaptive time-frequency decomposition with matching pursuit. In: Wavelets Theory, Algorithms and Applications, edited by C. Chui, L. Montefusco, and L. Pucio. Boston: Academic Press, 1994, in press.Google Scholar
  2. 2.
    Delapierre, G., E. Dreano, D. Samson-Doffus, J. Senant, J. F. Menard, and D. De Brucq. Mise au point chez le nourisson d'un critere de detection automatique des fuseaux de sommeil.Rev. EEG Neurophysiol. Clin. 16:311–316, 1986.Google Scholar
  3. 3.
    Fish, D. R., P. J. Allen, and J. D. Blackie. A new method for the quantitative analysis of sleep spindles during continuous overnight EEG recordings.Electroencephalogr. Clin. Neurophysiol. 70:273–277, 1988.PubMedCrossRefGoogle Scholar
  4. 4.
    Jobert, M., E. Poiseau, P. Jahnig, H. Schulz, and S. Kubicki. Pattern recognition by matched filtering: an analysis of sleep spindle and K-complex density under the influence of Lormetazepam and Zopicolone.Neuropsychobiology 26: 100–107, 1992.PubMedGoogle Scholar
  5. 5.
    Jobert, M., E. Poiseau, P. Jahnig, H. Schulz, and S. Kubicki. Topographical analysis of sleep spindle activity.Neuropsychobiology 26:210–217, 1992.PubMedCrossRefGoogle Scholar
  6. 6.
    Kumar, A., W. Hofman, and K. Campbell. An automatic spindle analysis and detection system based on the evaluation of human ratings of the spindle quality.Waking Sleeping 3:325–333, 1979.PubMedGoogle Scholar
  7. 7.
    Mallat, S. G., and Z. Zhang. Matching Pursuit with frequency dictionaries.IEEE Trans. Sign. Proc. 41:3397–3415, 1993.CrossRefGoogle Scholar
  8. 8.
    Pivik, R. T., F. W. Bylsma, and R. J. Nevins. A new device for automatic sleep spindle analysis: the “spindicator.”Electroencephalogr. Clin. Neurophysiol. 54:711–713, 1982.PubMedCrossRefGoogle Scholar

Copyright information

© Biomedical Engineering Society 1995

Authors and Affiliations

  • P. J. Durka
    • 1
  • K. J. Blinowska
    • 1
  1. 1.Laboratory of Medical PhysicsWarsaw UniversityWarszawaPoland

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