https://doi.org/10.1140/epjst/e2013-02051-6
Regular Article
Serial identification of EEG patterns using adaptive wavelet-based analysis
1 Physics Department, Saratov State University, Astrakhanskaya Str. 83, Saratov, 410012 Russia
2 Biology Department, Saratov State University, Astrakhanskaya Str. 83, Saratov, 410012 Russia
3 Faculty of Nonlinear Processes, Saratov State University, Astrakhanskaya Str. 83, Saratov 410012, Russia
4 REC “Nonlinear Dynamics of Complex Systems”, Saratov State Technical University, Politechnicheskaya Str. 77, Saratov 410056, Russia
5 Institute of the Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences, Butlerova Str. 5a, Moscow 117485, Russia
a e-mail: pavlov.lesha@gmail.com
Received: 16 July 2013
Revised: 13 August 2013
Published online: 28 October 2013
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.
© EDP Sciences, Springer-Verlag, 2013
