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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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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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Analysis of sleep EEG signal
Ježek, Martin ; Kozumplík, Jiří (referee) ; Rozman, Jiří (advisor)
Cílem této práce byl vývoj programu pro automatickou detekci arousalu v signálu spánkového EEG s použitím metod časově-frekvenční analýzy. Předmětem studie bylo 13 celonočních polysomnografických nahrávek (čtyři svody EEG, EMG, EKG a EOG), tj. celkově více než 100 hodin záznamu. Jednalo se o část dat z dřívějších výzkumných prací expertní lékařky v problematice spánku Dr. Emilie Sforzy, Ženeva, Švýcarsko, která rovněž poskytla základní hodnocení těchto dat. V záznamech bylo celkem označeno 1551 arousal událostí. Pro usnadnění výběru konkrétní metody časově-frekvenční analýzy byla následně vytvořena sada nástrojů pro vizualizaci jednotlivých signálů a jejich různých časově-frekvenčních vyjádření. S ohledem na závěry vizuální analýzy, charakter signálu EEG a efektivitu výpočetních metod byla pro analýzu vybrána waveletová transformace s mateřskou vlnkou Daubechies řádu 6. Jednotlivé svody EEG byly dekomponovány do šesti frekvenčních pásem. Z takto odvozených signálů a signálu EMG byly následně stanoveny ukazatele možné přítomnosti události arousalu. Tyto ukazatele byly dále váhovány lineárním klasifikátorem, jehož hodnoty vah byly optimalizovány pomocí genetického algoritmu. Na základě hodnoty lineárního klasifikátoru bylo rozhodnuto o přítomnosti události arousalu v daném svodě EEG – arousal byl detekován, jestliže hodnota klasifikátoru překročila danou mez na dobu více než 3 a méně než 30 vteřin. V celém záznamu pak byl arousal označen, byl-li detekován alespoň v jednom ze svodů EEG. Následně byly odvozeny míry senzitivity a selektivity detekce, jež byly rovněž základem pro stanovení fitness funkce genetického algoritmu. Pro učení genetického algoritmu byly vybrány první čtyři záznamy. Na základě takto optimalizovaných vah vznikl program pro automatickou detekci, který na celém souboru 13 záznamů dosáhl ve srovnání s expertním hodnocením míry senzitivity 76,09%, selektivity 53,26% a specificity 97,66%.
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Measurement of ECG signal for TWA analysis
Řezáč, Petr ; Vítek, Martin (referee) ; Kozumplík, Jiří (advisor)
The thesis deals with possibilities of using wavelet transform in the field of surface electrocardiogram (ECG) signals denoising and ECG signals measuring. Several algorithms have been used to detect and estimate T-wave alternans (TWA), such as spectral method (SM), Poincaré Mapping (PM) or correlation method (CM). T-wave alternans, also called repolarization alternans, is a phenomenon appearing in the electrocardiogram as a consistent fluctuation in the repolarization morphology on every-other-beat basis. Electrical TWA has been recognized as a marker of electrical instability, and has been shown to be related with patients at increased risk for ventricular arrhytmias. Presence of TWA has been reported in a wide range of clinical and experimental situations including long QT syndrome, myocardial infarction, angina pectoris, acute ischemia, etc. Projected methods of detection TWA are realized in Matlab software, and they are experimentally verified on real ECG signals from the European ST-T Database.
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Adaptive Filtering of Biological Signals
Šmíd, Karel ; Kozumplík, Jiří (referee) ; Provazník, Ivo (advisor)
Objective of this diploma work was to study methods of adaptive filtering and their use in suppression of noise in biological signals. Adaptive filtering represents effective means of suppression of parasitic nonstationary disturbances in a useful signal. The task was to design various types of adaptive filters and implement an adaptation algorithm in Matlab programming environment. It namely included suppression of powerline noise at 50 Hz and 100 Hz in ECG signals with minimization useful components disturbing. The realized filters were verified on real ECH signals and their efficiency was evaluated.
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Detection and filtering of ECG signals
Princ, Martin ; Kozumplík, Jiří (referee) ; Provazník, Ivo (advisor)
The aim of this thesis is to provide insight into certain elementary methods/ways of electrocardiographical signals filtration. Also, the thesis aims to introduce different techniques of detecting the EKG signal waves. The first part of the work analyses the theory of heart, electrical processes in heart, and the EKG signals systems. Further, the elementary methods of filtration and QRS detection are introduced.In the second part, the thesis analyses the BIOPAC student Lab system and presents simple methods of measuring the static EKG. The measure data results are then processed using the MATLAB program, and they are further used to demonstrate and practice the elementary methods of EKG filtration and QRS complex detection. Operation detectors QRS test on database EKG signal.
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Filtering of the ECG Signals
Slezák, Roman ; Kolář, Radim (referee) ; Kozumplík, Jiří (advisor)
Main objective of this thesis was to learn about possibility of suppression of narrow band disturbances. We focused on use of Lynn’s filters. The objective was to realize these filters with respect to a fast algorithm of filtering. Concretely, for suppression of drift we realized the fast high pass filter with flexible cut off frequency. Then we realized filter for suppression of electrical network disturbance. We have realized these filters for sampling frequencies 250 and 500 Hz and we tested them with real ECG signals. Then we have evaluated their efficiency.
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ECG Signal Compression Based on Wavelet Transform
Ondra, Josef ; Hrubeš, Jan (referee) ; Kozumplík, Jiří (advisor)
Signal compression is daily-used tool for memory capacities reduction and for fast data communication. Methods based on wavelet transform seem to be very effective nowadays. Signal decomposition with a suitable bank filters following with coefficients quantization represents one of the available technique. After packing quantized coefficients into one sequence, run length coding together with Huffman coding are implemented. This thesis focuses on compression effectiveness for the different wavelet transform and quantization settings.
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A Detections and Measurements in ECG Signals
Toušek, Vojtěch ; Vítek, Martin (referee) ; Kozumplík, Jiří (advisor)
Automatic detection and delineation of ECG characteristic points is a basic procedure of any analyze of ECG using computer. This detection is a necessary step to simplify the work of cardiologists to evaluate long ECG records. In this thesis is proposed and evaluate a method of detection and delineation in a single-lead ECG using dyadic wavelet transform followed by correction in pseudo-orthogonal lead system taken from standard 12-lead system. The method uses information about position of positive maximum – negative minimum pair to detect ECG characteristic waves. At first the QRS complex is detected and than its morphology (waves Q and S) and the onset and end of the complex. After that the T-wave is detected and delineated within a searching window dependent on QRS position. And last the P-wave is detected and delineated. There are used two types of wavelets in developed method, “haar” and “quadratic spline”. The developed method was evaluated on CSE database. When haar wavelet was used the QRS detector sensitivity was 99.14%. In the work is also evaluated the accuracy of delineation characteristic points. As the P-wave and QRS complex delineation produced quite good results the T-wave end delineator produced relatively big deviations. All deviations are presented in histograms.
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Portál pro klienty insolvenčních správců
Kozumplík, Jiří
This thesis deals with processes and workflow within insolvency administrator's office, problematics of communication with their clients and sorting clients by their characteristics, considering changes in laws valid since 1. 1. 2014.
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