Detection of Structural Features in Biological Signals
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In this article structures in biological signals are treated. The simpler—directly visible in the signals, which still demand serious methods and algorithms in the feature detection, similarity investigation and classification. The major actions in this domain are of geometric, thus simpler sort, though there are still hard problems related to simple situations. The other large class of less simple signals unsuitable for direct geometric or statistic approach, are signals with interesting frequency components and behavior, those suitable for spectroscopic analysis. Semantics of spectroscopy, spectroscopic structures and research demanded operations and transformations on spectra and time spectra are presented. The both classes of structures and related analysis methods and tools share a large common set of algorithms, all of which aiming to the full automatization. Some of the signal features present in the brain signal patterns are demonstrated, with the contexts relevant in BCI, brain computer interfaces. Mathematical representations, invariants and complete characterization of structures in broad variety of biological signals are in the central focus.
KeywordsStructures in biological signals Spectrogram features WYSIWIG in geometric structures and spectroscopy Mathematical invariants and characterizations BCI—brain computer interface
We are thankful to our support team leading Nenad Andonovski, Maja Jovanović, Group for Intelligent Systems, School of Mathematics, and Professor Nina Japundžić Zigon, from Institute for pharmacology and toxicology, School of Medicine, University of Belgrade, for the BP experimental recordings.
This work was partly supported by Serbian Ministry of Science and Technological Development (Projects No. 143021 and No.143027).
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