This paper describes methods of automatic analysis and classification of biological signals. Polysomnographic (PSG) recordings encompass a set of heterogeneous biological signals (e.g. EEG, EOG, EMG, ECG, PNG) recorded simultaneously. These signals, especially EEG, are very complex and exhibit nonstationarity and stochasticity. Thus their processing represents a challenging multilevel procedure composed of several methods. Used methods are illustrated on examples of PSG recordings of newborns and sleep recordings of adults and can be applied to similar tasks in other problem domains. Analysis was performed using real clinical data. © 2009 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Gerla, V., Djordjevic, V., Lhotska, L., & Krajca, V. (2009). System approach to complex signal processing task. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5717 LNCS, pp. 579–586). https://doi.org/10.1007/978-3-642-04772-5_75
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