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Detekce začátku a konce komplexu QRS s využitím hlubokého učení
Müller, Jakub ; Šaclová, Lucie (referee) ; Smíšek, Radovan (advisor)
ECG measurement isan essential diagnostic tool for cardiac health, and automation of its analysis can aid to our healthcare to relieve staff workload or improve the quality of automated diagnostics from wearable devices. This work focuses specifically on the QRS complex in the ECG signal, with the main goal of using deep learning methods to detect its onset and offset. In the theoretical introduction, the reader is introduced to the origin of the QRS complex and ECG measurements, artificial neural networks and deep learning. Modified architecture U-Net for 1D signals was chosen to implement the actual method. Data were extracted from five publicly available databases and preprocessed in Matlab. This was followed by moving to the Python environment where parts of the model were implemented using the TensorFlow and Keras libraries, subsequent training, testing of the model and evaluation of the results.
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Detection of ventricular extrasystoles
Svánovská, Zuzana ; Mézl, Martin (referee) ; Sekora, Jiří (advisor)
Ventricular extrasystoles are pathological changes in the ECG signal. Detection of ventricular extrasystoles on 12leads ECG was created in MATLAB. My work contains two algorithms. The first of these algorithms is based on comparision wides of QRS komplexes. The second algorithm matchs maximum and minimum evaluations of QRS komplexes. We look for agreements beetween these two algorithms and finally if we find these agreenments in seven leads at least we will suppose presence of ventricular extrasystoles.
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QRS complex detector in ECG signals
Kosíř, Kamil ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
The aim of this thesis is to introduce issues and basic principles of QRS complex detection in ECG signals. This work is separated into several parts. The first part deals with anatomy and functions of the heart, for example the emergence and spread of potentials. The next part includes distribution ECG leads and explanation of ECG signal. Afterwards are described some detectors of QRS complex. The main part of this work is realization of two algorithms implemented in Matlab program. The first detector is based on squaring algorithm and the the second is based on a spreading of the signal into several frequency bands. The effectivness of both detectors is tested on signals from CSE library at the end of the work.
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QRS detection based on Stockwell transform
Kašík, Ondřej ; Kozumplík, Jiří (referee) ; Smital, Lukáš (advisor)
This bachelor´s thesis deals with the detection of QRS complexes in ECG record. The thesis provides a brief information related to the heart anatomy, generation of electrical signals in the heart, recording and description of the ECG record. In more detail, there is a description of the detection of QRS complexes by various methods and realization of a detector based on Stockwell transform, Shannon energy and adaptive thresholding. The evaluation process of the detection efficiency is also included. Sensitivity and positive prediction of the proposed detector on the complete MIT-BIH Arrhythmia database reached 99.80 % and 99.88 % respectively.
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Detection of ventricular extrasystoles
Veleba, Josef ; Vítek, Martin (referee) ; Mézl, Martin (advisor)
This thesis focuses on the issue of ventricular extrasystoles and their detection in ECG signal. It provides a brief description of physiological electrical activity of the heart with the theoretical analysis of ventricular extrasystoles, QRS complex detection methods and the related detection of premature ventricular contractions. The main part of the work presents the process of implementation of selected QRS complex detection and premature ventricular contractions detection methods in MATLAB with the evaluation of test results.
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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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ECG analysis
Heczko, Marian ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
The topic of this master's thesis is the analysis of ECG signals using wavelet transform. In the introductory chapters there is a brief description of heart anatomy, the emergence and spread of potentials, which evocating activities of myocardium. There is an overview of techniques used for ECG signals analysis and explanation of ECG curve diagnostic importance. Work also containts an ECG signal analysis common procedure explanation and different approaches brief overview. The main part of this work is an application detecting significant intervals in the ECG signal, developed in Matlab. In several chapters the detection procedure is described in more details and gave reasons for chosen methods. In the last chapter there is a preview of several signals as a result of developed application, together with evaluation of the tests carried out at the CSE database. Detector sensitivity was quantified over 99,10%.
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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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QRS detection based on wavelet transform
Zedníček, Vlastimil ; Ronzhina, Marina (referee) ; Smital, Lukáš (advisor)
This thesis deals with implementation of detector QRS complex with use of wavelet transform. The first part is focused on formation and possibility to measure cardiac activity. The other part of thesis we will familiarise with the different possibilities of detection QRS complex and we intimately focus on wavelet transform that will be used for a project of detection QRS complex. The practical part of thesis focuses on the project of detector in programming language Matlab and his different setting. This projected detector has been tested with CSE database. Achieved results of projected detector are evaluated with the results of others authors.
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Analysis of difference between HRV parameters gained from PP and RR intervals
Svobodová, Sabina ; Janoušek, Oto (referee) ; Milek, Jakub (advisor)
This bachelor thesis aims to solve problems of ECG signals, respectively detection of QRS complex and P wave, and subsequent analysis of heart rate variability. The first part is focused on literary research. It deals with the heart anatomy, electrocardiography and more detailed description of individual waves, as well as with the pre-processing of ECG signal, QRS complex detection and P wave detection. The last theoretical part describes the analysis of heart rate variability. In the practical part detection of QRS complex, P wave and subsequent analysis of heart rate variability is programmed in MATLAB. Finally, statistical evaluation is performed in STATISTICA.
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