Automatic Diagnostics and Processing of EEG

  • Alexander E. Hramov
  • Alexey A. Koronovskii
  • Valeri A. Makarov
  • Alexey N. Pavlov
  • Evgenia Sitnikova
Part of the Springer Series in Synergetics book series (SSSYN)


This chapter considers basic problems of automatic diagnostics and processing of EEG. We discuss the wavelet-based techniques in order to fully automatize “routine” operations, such as visual inspection of EEG. In addition to that, we exemplify some practical applications of wavelet methods for automatic analysis of pre-recorded signals of neuronal activity (off-line diagnostics), and also some examples of EEG analysis in real-time (on-line). We also discuss principles of fast and precise detection of transient events in EEG and organization of closed-loop control systems that can be used in BCI. Finally, we consider methods of artifact suppression in multichannel EEG based on a combination of wavelet and independent component analysis.


Independent Component Analysis Independent Component Analysis Morlet Wavelet Cerebral Activity Sleep Spindle 
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

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Alexander E. Hramov
    • 1
    • 2
  • Alexey A. Koronovskii
    • 1
    • 2
  • Valeri A. Makarov
    • 3
  • Alexey N. Pavlov
    • 1
    • 4
  • Evgenia Sitnikova
    • 5
  1. 1.Research and Education Center ‘Nonlinear Dynamics of Complex Systems’Saratov State Technical UniversitySaratovRussia
  2. 2.Department of Nonlinear ProcessesSaratov State UniversitySaratovRussia
  3. 3.Department of Applied MathematicsComplutense UniversityMadridSpain
  4. 4.Physics DepartmentSaratov State UniversitySaratovRussia
  5. 5.Institute for Higher Nervous Activity and NeurophysiologyRussian Academy of SciencesMoscowRussia

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