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Automatic Diagnostics and Processing of EEG

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Wavelets in Neuroscience

Abstract

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.

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Notes

  1. 1.

    The experimental system OSDS (on-line SWD detection system) was designed and developed at the Donders Institute of Brain, Cognition and Behavior, Radboud University Nijmegen, The Netherlands.

  2. 2.

    That is, the EEG epoch which does not contain any oscillatory patterns, i.e., SWD and spindle-like patterns.

  3. 3.

    Available at www.mat.ucm.es/%7Evmakarov/downloads.php

  4. 4.

    Available at sccn.ucsd.edu/eeglab

  5. 5.

    Available at www.cis.hut.fi/projects/ica/fastica

  6. 6.

    Available at chronux.org/chronux

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Hramov, A.E., Koronovskii, A.A., Makarov, V.A., Pavlov, A.N., Sitnikova, E. (2015). Automatic Diagnostics and Processing of EEG. In: Wavelets in Neuroscience. Springer Series in Synergetics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43850-3_7

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