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Methods for detection of QRS complex
Lysák, Karel ; Chrobák, Martin (referee) ; Smital, Lukáš (advisor)
This bachelor’s thesis deals with methods for detection of QRS complex in the ECG signal. There are described selected detection approaches, basic information about ECG and electrical activity of cardiac muscle. There is also described detailed procedure for the implementation of the three methods of detection in MATLAB and an assessment is made of the detectors tested on the CSE database. There are described some methods of cluster analysis and their possibilities of usage. There is also a description of detectors created by using cluster analysis and their efficiency is tested on the CSE database. Finally, there is a comparison of detection rates of all created detectors.
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Classification of ECG signals using Cluster Analysis
Kremličková, Lenka ; Janoušek, Oto (referee) ; Klimek, Martin (advisor)
This thesis deals with methods of cluster analysis and their applications to short-term recording of the electrocardiogram (ECG). The work describes the physiological properties of the heart and cardiac muscle, as well as its electrical behavior and the formation and ECG. Part of this work is to describe the issue of cluster analysis of biosignals and distribution of clustering methods for hierarchical and non-hierarchical. Are described in detail agglomerative hierarchical method, which is outlined the procedure for the solution. Further described is the use of cluster analysis for classification of ECG and its application to the signals from the CSE. This work assesses which of clustering methods is applied to ECG signals appropriate.
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Methods for detection of QRS complex
Lysák, Karel ; Chrobák, Martin (referee) ; Smital, Lukáš (advisor)
This bachelor’s thesis deals with methods for detection of QRS complex in the ECG signal. There are described selected detection approaches, basic information about ECG and electrical activity of cardiac muscle. There is also described detailed procedure for the implementation of the three methods of detection in MATLAB and an assessment is made of the detectors tested on the CSE database. There are described some methods of cluster analysis and their possibilities of usage. There is also a description of detectors created by using cluster analysis and their efficiency is tested on the CSE database. Finally, there is a comparison of detection rates of all created detectors.
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Classification of ECG signals using Cluster Analysis
Kremličková, Lenka ; Janoušek, Oto (referee) ; Klimek, Martin (advisor)
This thesis deals with methods of cluster analysis and their applications to short-term recording of the electrocardiogram (ECG). The work describes the physiological properties of the heart and cardiac muscle, as well as its electrical behavior and the formation and ECG. Part of this work is to describe the issue of cluster analysis of biosignals and distribution of clustering methods for hierarchical and non-hierarchical. Are described in detail agglomerative hierarchical method, which is outlined the procedure for the solution. Further described is the use of cluster analysis for classification of ECG and its application to the signals from the CSE. This work assesses which of clustering methods is applied to ECG signals appropriate.
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