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The European Physical Journal Special Topics

, Volume 222, Issue 10, pp 2713–2722 | Cite as

Serial identification of EEG patterns using adaptive wavelet-based analysis

  • A.I. Nazimov
  • A.N. PavlovEmail author
  • A.A. Nazimova
  • V.V. Grubov
  • A.A. Koronovskii
  • E. Sitnikova
  • A.E. Hramov
Regular Article Applications in Biology and Medicine

Abstract

A problem of recognition specific oscillatory patterns in the electroencephalograms with the continuous wavelet-transform is discussed. Aiming to improve abilities of the wavelet-based tools we propose a serial adaptive method for sequential identification of EEG patterns such as sleep spindles and spike-wave discharges. This method provides an optimal selection of parameters based on objective functions and enables to extract the most informative features of the recognized structures. Different ways of increasing the quality of patterns recognition within the proposed serial adaptive technique are considered.

Keywords

European Physical Journal Special Topic Oscillatory Pattern Sleep Spindle Instantaneous Amplitude Wavelet Energy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© EDP Sciences and Springer 2013

Authors and Affiliations

  • A.I. Nazimov
    • 1
  • A.N. Pavlov
    • 1
    Email author
  • A.A. Nazimova
    • 2
  • V.V. Grubov
    • 3
    • 4
  • A.A. Koronovskii
    • 3
  • E. Sitnikova
    • 5
  • A.E. Hramov
    • 3
    • 4
  1. 1.Physics Department, Saratov State UniversitySaratovRussia
  2. 2.Biology Department, Saratov State UniversitySaratovRussia
  3. 3.Faculty of Nonlinear Processes, Saratov State UniversitySaratovRussia
  4. 4.REC “Nonlinear Dynamics of Complex Systems”, Saratov State Technical UniversitySaratovRussia
  5. 5.Institute of the Higher Nervous Activity and Neurophysiology of Russian Academy of SciencesMoscowRussia

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