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Automatic detection of ischemia in ECG using artificial neural network
Noremberczyk, Adam ; Smital, Lukáš (referee) ; Ronzhina, Marina (advisor)
This thesis discusses the utilization of the artificial neural networks (ANN) as electrocardiography (ECG) classifiers of coronary artery disease (CAD) and myocardial infarction (MI) in ECG signal. The first part of this thesis is orientated towards the theoretical knowledge and describes the issue of ECG pathological changes, methods for automatic detection of CAD and MI and the issue of the perceptron and ANN. The second deals with use of Neural Network Toolbox MATLAB® version R2010a. In graphical user interface development environment (Guide) is created application that is used to compare the success of automatic detection of ischemia in ECG using ANN. It allows the user to set various parameter settings UNS and display ECG waveforms.
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Automatic delineation of ECG signals
Jurek, Jakub ; Janoušek, Oto (referee) ; Vítek, Martin (advisor)
This project deals with basic description of ECG signal and some of known methods of delineation ECG´s individual parts. Next this work deals with detailed description of the method of authors Laguna, Jané, Caminal and realization of the complete delineation algorithm based on this method. Next this work deals with testing this algorithm on the CSE database, evaluation results and comparing results with results of authors of the method.
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Heart beat representation for classification
Smíšek, Radovan ; Janoušek, Oto (referee) ; Ronzhina, Marina (advisor)
Selection of ECG segment plays a significant role in design of a heart beat classifier. The type of selected segments influences the classification not only in regard to the type and maximum number of recognized pathological groups but also in regard to the complexity of classification model, which consequently creates indirect demands on the memory of the computer technology used as well as on the time needed for the classification. The thesis is focused on the comparison of success rates of the ECG heart beat classifications in different input segments. The input segments used were QRST, RST, ST-T, QRS, and T. The ECG signal was obtained from isolated rabbit hearts and divided into individual types according to the T-wave amplitude and changes in the ST segment. The signal subsequently enters the artificial neural network where it is classified into predefined types. The network used had twenty-four neurons in the first layer and one neuron in the second layer. Efficiency of the classification is in the conclusion of this thesis.
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Classification of heart beats using artificial neuronal networks
Doležalová, Radka ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This work deals with using of artificial neural networks (ANN) for ECG classification. The issue of ECG and ANN technique are described theoretically at first, the next section describes use of Matlab to design ANN and graphical user interface. ECG data (namely QRST segments from the orthogonal X- lead from seven phases of the experiment) obtained from experiments in isolated hearts of rabbits are used for learning and testing of the classifier. The result of this work is the software with GUI that allows user to set various parameters and structure of ANN. After learning phase, ANN realized in this work able to classify cardiac cycles according to their morphology into seven groups.
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Measurement of cardiovascular parameters
Németh, Štefan ; Ronzhina, Marina (referee) ; Kolářová, Jana (advisor)
This thesis is about evaluating ECG signal with help of MATLAB. Grafic user iterface aplication was programmed to provide evaluation of source signal, its power spectrum, detects R-R intervals and determines ration between spectral components. Furthemore this thesis is considering practical use of HRV power evaluation in general medical practise.
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Automatic detection of ischemia in ECG
Noremberczyk, Adam ; Potočňák, Tomáš (referee) ; Ronzhina, Marina (advisor)
This thesis discusses the utilization of the artificial neural networks (ANN) for detection of coronary artery disease (CAD) in frequency area. The first part of this thesis is orientated towards the theoretical knowledge. Describes the issue of ECG pathological changes. ECQ are converted to frequency area. Described statistical methods and methods for automatic detection of CAD and MI. Explained the issue of the perceptron and ANN. The second deals with use of Neural Network Toolbox MATLAB®. This part focuses on counting and finding suitable parameters and making connection of band. At the end of the thesis UNS is used to detect ischemic parameters and the results are discussed. Average values for the best settings are 100% accuracy.
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Evaluation of heart arrhythmias
Šromová, Michaela ; Kozumplík, Jiří (referee) ; Provazník, Ivo (advisor)
The thesis is a brief description of the anatomy and electrophysiology of the heart. The thesis also describes the different types of electrocardiogram and cardiac arrhythmias with a description of their treatment. The next section provides design of a programme for the classification of selected types of arrhythmias, and three options for rhythm detection, using the length of RR intervals, finding extremes of P and R waves, measuring the length of intervals and heights of amplitudes. The practical part of this work was to create a rhythm classifier assigning appropriate treatment of arrhythmias, verification of its functions on the signals available from the library of arrhythmias and its evaluation.
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Heart rate variability in decreasing of alertness level
Strublová, Tereza ; Provazník, Ivo (referee) ; Janoušek, Oto (advisor)
Objective of this study is to familiarize with problems of measuring heart rate variability. At first there is described physiology of vascular system, then practical measuring of heart rate variability during falling asleep. At the end of this project is the statistical processing of results and comparison of the differences between heart rate variability during sleep and wakefulness.
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Measurement of cardiovascular parameters
Németh, Štefan ; Ronzhina, Marina (referee) ; Kolářová, Jana (advisor)
This thesis is about evaluating ECG signal with help of MATLAB. Grafic user iterface aplication was programmed to provide evaluation of source signal, its power spectrum, detects R-R intervals and determines ration between spectral components. Furthemore this thesis is considering practical use of HRV power evaluation in general medical practise.
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LabView and biosignal analysis
Kutílek, Miloš ; Harabiš, Vratislav (referee) ; Kolář, Radim (advisor)
This bachelor’s thesis deals with the analysis of biological signals in LabView environment. Mainly it focuses on the analysis of ECG signals. The thesis also describes the theory of electrocardiogram and occupies by several programs which consider various approaches to digital filtering of ECG signals, programs for detection R wave by different ways and simple cardiology monitor.
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