Real-time Biological Signal Processing for Monitoring and Control

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Real-time Biological Signal Processing for Monitoring and Control

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Title: Real-time Biological Signal Processing for Monitoring and Control
Author: Mareš, Jan
ISBN: 978-80-7454-646-4
URI: http://hdl.handle.net/10563/50093
Date: 2017-05-03
Publisher: Univerzita Tomáše Bati ve Zlíně
Page count: 44
Availability: Teze habilitační práce jsou přístupné veřejně v tištěné podobě v Knihovně UTB. Plný text práce je přístupný elektronicky pouze v rámci univerzity.


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The habilitation thesis deals with methodological aspects of signal and image processing and applications of proposed methods for analysis of multichannel signals acquired from bioprocesses and human-machine systems. The purpose of the study is to show that similar mathematical background can be used in different areas including processing of biomedical signals and images. The thesis can be divided into two main streams, (i) mathematical analysis and expert systems in bioprocess control and (ii) signal and image processing in biomedicine. The first part is devoted to modeling and analysis of bioprosesses.. With some exceptions it is possible to say that measurement corresponds to data acquisition and control is equal to data (signal) processing. The research in this field originated as a result of cooperation with the Department of process control at Faculty of Electrical Engineering and Informatics, University of Pardubice, where the modeling, simulation and advanced process control techniques form important part of the work. The second part is the signal (image can be taken as an multidimensional signal) processing in biomedicine and robotics. Application of computational technologies in biomedicine is modern field with many possibilities where the research can be done. Signal and image processing in biomedicine is a crucial idea which is applied for ages. EEG signal is base for neurologists, ECG signal for cardiologists, CT, NMR are bases for radiologists. Unfortunately, signals and images are very often processed only visually by an expert and there are almost no objective criterions. Therefore there is a chance to improve standards by semi-automatic or fully automatic signal and image processing tools. This research is a result of cooperation with Faculty Teaching Hospitals in Prague and Hradec Králové, Department of Neurology and Department of Nephrology of the Charles University. Each part represents independent research project where crucial benefits or novelty can be found. The most important are (i) the confirmation of the hypothesis that the number of receptors, and thereby the number of connections between the neurons decreases with age (this analysis was the first one applied to EEG signal), (ii) development of a new software which is able to analyze the CT image semi-automatically and (iii) absolutely new bioprocess control strategy based on advanced signal analysis.

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