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Method for diagnostics of characteristic patterns of observable time series and its real-time experimental implementation for neurophysiological signals

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Abstract

A method is proposed for analysis and automatic diagnostics of characteristic oscillatory patterns of the electric activity of the brain in real time on the basis of a continuous wavelet transformation. The results of experimental investigation of automatic recognition of epileptic activity episodes on experimental animals based on the proposed approach are considered.

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Authors and Affiliations

  1. Chernyshevsky State University, Astrakhanskaya ul. 83, Saratov, 410012, Russia

    A. A. Ovchinnikov, A. E. Hramov & A. A. Koronovskii

  2. Donders Center for Cognition, Radboud University Nijmegen, Nijmegen, The Netherland

    A. Luttjehann & G. van Luijtelaar

Authors
  1. A. A. Ovchinnikov
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  2. A. E. Hramov
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  3. A. Luttjehann
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  4. A. A. Koronovskii
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  5. G. van Luijtelaar
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Correspondence to A. E. Hramov.

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Original Russian Text © A.A. Ovchinnikov, A.E. Hramov, A. Luttjehann, A. A. Koronovskii, G. van Luijtelaar, 2011, published in Zhurnal Tekhnicheskoĭ Fiziki, 2011, Vol. 81, No. 1, pp. 3–10.

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Ovchinnikov, A.A., Hramov, A.E., Luttjehann, A. et al. Method for diagnostics of characteristic patterns of observable time series and its real-time experimental implementation for neurophysiological signals. Tech. Phys. 56, 1–7 (2011). https://doi.org/10.1134/S1063784211010191

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  • DOI: https://doi.org/10.1134/S1063784211010191

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