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Analysis of Atrial Fibrillation Heart Rate Dynamics
Tesařová, Tereza ; Ronzhina, Marina (referee) ; Hejč, Jakub (advisor)
Bachalor thesis focuses on clinical tracking of heart rate abnormalities to specify the level of variability in diverse-lengthy ECG signals, with a direct way to analyze atrial fibrillation and accuracy increasing its detection of actual available methods. The principle of heart electrophysiology and also the impulse genesis is mentioned in a introductory part of work, including elementary classification of cardiac arrhytmias and their deflection from normal sinus rhythm. The physiological analysis of atrial fibrilation dynamic structure helps with the application of detection algorithms in a MATLAB program and sets an underlying basis for an appropriate discussion in a final statistical ROC analysis.
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Analysis and processing of EEG signal
Esmaildokht Mamaghani, Amir Hossein ; Horák, Karel (referee) ; Petyovský, Petr (advisor)
This thesis deals with methods of electroencephalographic signals measurement and analysis. It covers the whole field of EEG from the basic principles of measuring through the methodology and various ways of measuring, signal preprocessing and processing, and classification of individual elements, up to the signal analysis capabilities. Then it provides an insight into the world of products for the consumer market and brings an overview of open-source solutions for EEG signal measuring. In the practical part it focuses on acquisition, processing and analysis of measured data, follows all individual steps from signal preprocessing up to its final presentation. Eventually it explains the structure and composition of an artificial neural network by which it would be possible to recognize and classify specific EEG signal.
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Diagnosing Parkinson's disease from analysis of speech recording
Vymlátil, Petr ; Trzos, Michal (referee) ; Lněnička, Jakub (advisor)
This thesis is focused on diagnosing Parkinson’s disease from analysis of speech recording. Introduction of this work deals with description of voice production mechanism, it’s basic qualities and influence of hypokinetic dysarthria on speech. In next chapter, there is described voice signal and some methods of it’s preprocessing. Next part continues dealing with description of chosen individual symptoms, which are needed for PD diagnosing, followed by definition of chosen reduction methods and classifiers. There is a comparison of classify succes of naive bayes classifier, depending on chosen reduction method in last chapter of this work.
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Analysis of Atrial Fibrillation Heart Rate Dynamics
Tesařová, Tereza ; Ronzhina, Marina (referee) ; Hejč, Jakub (advisor)
Bachalor thesis focuses on clinical tracking of heart rate abnormalities to specify the level of variability in diverse-lengthy ECG signals, with a direct way to analyze atrial fibrillation and accuracy increasing its detection of actual available methods. The principle of heart electrophysiology and also the impulse genesis is mentioned in a introductory part of work, including elementary classification of cardiac arrhytmias and their deflection from normal sinus rhythm. The physiological analysis of atrial fibrilation dynamic structure helps with the application of detection algorithms in a MATLAB program and sets an underlying basis for an appropriate discussion in a final statistical ROC analysis.
|
|
|
Diagnosing Parkinson's disease from analysis of speech recording
Vymlátil, Petr ; Trzos, Michal (referee) ; Lněnička, Jakub (advisor)
This thesis is focused on diagnosing Parkinson’s disease from analysis of speech recording. Introduction of this work deals with description of voice production mechanism, it’s basic qualities and influence of hypokinetic dysarthria on speech. In next chapter, there is described voice signal and some methods of it’s preprocessing. Next part continues dealing with description of chosen individual symptoms, which are needed for PD diagnosing, followed by definition of chosen reduction methods and classifiers. There is a comparison of classify succes of naive bayes classifier, depending on chosen reduction method in last chapter of this work.
|
|
|
Analysis and processing of EEG signal
Esmaildokht Mamaghani, Amir Hossein ; Horák, Karel (referee) ; Petyovský, Petr (advisor)
This thesis deals with methods of electroencephalographic signals measurement and analysis. It covers the whole field of EEG from the basic principles of measuring through the methodology and various ways of measuring, signal preprocessing and processing, and classification of individual elements, up to the signal analysis capabilities. Then it provides an insight into the world of products for the consumer market and brings an overview of open-source solutions for EEG signal measuring. In the practical part it focuses on acquisition, processing and analysis of measured data, follows all individual steps from signal preprocessing up to its final presentation. Eventually it explains the structure and composition of an artificial neural network by which it would be possible to recognize and classify specific EEG signal.
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