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ECG Signal Distortion Measures
Požár, Pavel ; Kozumplík, Jiří (referee) ; Vítek, Martin (advisor)
This master's thesis deals with electrocardiogram and its distortion, which causes errors, due to which a doctor can make a wrong diagnosis. In the theoretical part electrocardiogram is briefly described, further theory of wavelet transform, introduction to the signal compression and some information about ECG delineation. Methods used for the signal evaluation and therefore determination of the distortion size are described in the main theoretical part. This thesis contains known methods and also a method of own design based on the ECG delineation. Some of the described methods are checked in the practical part. These methods are tested for two different compression algorithms, which cause various distortion. In the final part distortion was tested on the influence on setting the wrong diagnosis.
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An Arrhytmia Classifiication Based on RR Interval
Novotný, Jiří ; Škutková, Helena (referee) ; Kozumplík, Jiří (advisor)
This bachelor’s thesis deals with automatic classification of cardiac rhytm based on the sequence of RR intervals. The theoretical part deals both with characteristics of arrhytmias, which have been classified and the principles of the detectors and classificators used in this thesis. In the practical part, the QRS detector based on the calculation of the envelope of the ECG signal was realized in Matlab. Furthermore, the algoritm classifying arrhytmias based on the analysis of RR intervals was created. The reliability of the detector and the efficiency of the classificator was tested on the standard database CSE. The sensitivity of the detector was 98,28% and its positive predictive value was 98,38%. The diagnoses of the implemented classificator concurred in 73,17% with the cardiologists‘ diagnoses.
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A Wavelet-Based QRS-Complex Detection
Kocian, Ondřej ; Provazník, Ivo (referee) ; Kozumplík, Jiří (advisor)
This project investigates methods of construction the wavelet-based QRS-complex detector. QRS-complex detection is very important, because it helps automatically calculate heart rate and in some cases it is used for compression ECG signal. The design of QRS detector can be made with many methods, in this project were mentioned and consequently tested only a few variants. The principle of designed detector used a wavelet-based decomposition of the original ECG signal to several frequency-coded bands. These bands are consequently transformed to absolute values and with the help of the threshold value are marked positions of assumed QRS complexes. Then are these assumed positions from all bands compared between themselves. If the position is confirmed at least at one nearby band, then is this position marked as true QRS complex. To increase efficiency of designed detector, two modifications were additionally mentioned. The first one, using the envelope of the signal, had rather negative effect on detectors efficiency. The second modification, using combined signal from three pseudoorthogonal leads, had reversely very good effect on detectors efficiency. In the end, the designed detector and all its modifications were tested on signals from CSE library (exactly on leads II, V2 and V6).
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Software for manual delineation of ECG signals
Jež, Radek ; Kozumplík, Jiří (referee) ; Vítek, Martin (advisor)
This thesis deals with evaluation EKG in terms of classification rhythm and analysis HRV. In theoretic part of work are described basics of heart physiology and its usual pathology, basics of electrocardiography, evaluation EKG and standard methods of HRV evaluation. In practical part are described algorithms used in created application. Mainly describes technique of rhythm evaluation, ectopic rhythms and delineation error elimination, data preparing for HRV evaluation, drift removal from DES and HRV evaluation methods. Created program was tested on CSE and MIT- BIH database records. For lack of suitable data and absence of tested data, it wasn’t possible to test all the classification rules of used algorithms. Tested part of program appears reliable and functional.
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Modeling of RR intervals
Jach, Daniel ; Kozumplík, Jiří (referee) ; Kubičková, Alena (advisor)
This thesis is focused on modelling RR intervals. Different models are created illustrating the function of cardiovascular system in order to test various methods for expressing, removing trend and analyzing heart rate variability signals. In this thesis the IPFM model as well as the McSharry model are described and realized.
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Heart Sounds Detector
Hlaváčová, Kristýna ; Králík, Martin (referee) ; Kozumplík, Jiří (advisor)
In this thesis deals with detection of heart sounds in signal. In first half of thesis is discussed anatomy, physiology of cardiovascular system and issue of heart sounds. Afterwards, devices for evalution phonocardigram signals and their analysis are described. Thereafter the work focuseson the algorithm for detection of the first and second heart sound, which was implemented in the MATLAB R2014a environment. In conclusion, there is a summary of the proposed method and statistic evaluation.
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Monitoring Trends of Electrical Activity of the Heart Using Time-Frequency Decomposition
Čáp, Martin ; Kozumplík, Jiří (referee) ; Provazník, Ivo (advisor)
Work is aimed at the time-frequency decomposition of a signal application for monitoring the EKG trend progression. Goal is to create algorithm which would watch changes in the ST segment in EKG recording and its realization in the Matlab program. Analyzed is substance of the origin of EKG and its measuring. For trend calculations after reading the signal is necessary to preprocess the signal, it consists of filtration and detection of necessary points of EKG signal. For taking apart, also filtration and measuring the signal is used wavelet transformation. Source of the data is biomedicine database Physionet. As an outcome of the algorithm are drawn ST segment trends for three recordings from three different patients and its comparison with reference method of ST qualification. For qualification of the heart stability, as a system, where designed methods watching differences in position of the maximal value in two-zone spectrum and the Poincare mapping method. Realized method is attached to this thesis.
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The EEG segmentation
Nečadová, Anežka ; Kozumplík, Jiří (referee) ; Kubicová, Vladimíra (advisor)
Subject of this bachelor project is the introduction of the EEG signal. Are discussed his characteristics, application and methods of processing. The main part deals with the segmentation of the EEG signal. Two methods are implemented in program Matlab - adaptive segmentation based on differential average amplitude and differential average frequency and adaptive segmentation based on differential estimated based on FFT. Functionality of algorithms is verified on real EEG signals.
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