1 March 2013 Adaptive wavelet-based recognition of oscillatory patterns on electroencephalograms
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Abstract
The problem of automatic recognition of specific oscillatory patterns on electroencephalograms (EEG) is addressed using the continuous wavelet-transform (CWT). A possibility of improving the quality of recognition by optimizing the choice of CWT parameters is discussed. An adaptive approach is proposed to identify sleep spindles (SS) and spike wave discharges (SWD) that assumes automatic selection of CWT-parameters reflecting the most informative features of the analyzed time-frequency structures. Advantages of the proposed technique over the standard wavelet-based approaches are considered.
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Alexey I. Nazimov, Alexey I. Nazimov, Alexey N. Pavlov, Alexey N. Pavlov, Alexander E. Hramov, Alexander E. Hramov, Vadim V. Grubov, Vadim V. Grubov, Alexey A. Koronovskii, Alexey A. Koronovskii, Evgenija Yu. Sitnikova, Evgenija Yu. Sitnikova, } "Adaptive wavelet-based recognition of oscillatory patterns on electroencephalograms", Proc. SPIE 8580, Dynamics and Fluctuations in Biomedical Photonics X, 85801D (1 March 2013); doi: 10.1117/12.2001888; https://doi.org/10.1117/12.2001888
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