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Automatic diagnosis of the 12-lead ECG using deep learning
Blaude, Ondřej ; Smital, Lukáš (referee) ; Provazník, Valentine (advisor)
The aim of this diploma thesis is to investigate the problematics of automatic ECG diagnostics, namely on twelve-lead recordings. In the first chapter the heart and its electrical activity measurement is described shortly. In addition to that, the abnormalities which are going to be classified in this thesis are also briefly described. In the second chapter, it is described how the ECG was diagnosed earlier, by classical methods that preceded deep learning. Some of the shortcomings that the classical methods have compared to deep learning are also described here. The third part already pays attention to deep learning itself, and its contribution and advantages compared to classical methods. Convolutional neural networks and their individual blocks are also described here, later attention is paid to selected architectures that were used in some studies. The fourth chapter already focuses on the practical part, in which the data used from the PhysioNet database, the proposed algorithm and its implementation are described in more detail. In the fifth chapter the results are discussed and compared to the corresponding publications.
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HRV analysis based on PPG signal
Kadlčík, Jindřich ; Hrbotický, Lukáš (referee) ; Smital, Lukáš (advisor)
Heart rate variability analysis has lately gained remarkable popularity as a tool in training optimalization and in prevention of cardiac disease. It is usually based on the ECG signal, the acquisition of which is uncomfortable during activity. Therefore, the option to base the analysis on the PPG signal instead was proposed, but not yet sufficiently studied. This study compiles the necessary information for correct heart rate variability analysis and introduces our own implemented detectors of fiducial points in the PPG signal, and compares their usability for calculation of HRV analysis metrics.
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Calculation of the cyclist's power output based on data from shoe pressure insoles
Teturová, Iveta ; Smital, Lukáš (referee) ; Hrbotický, Lukáš (advisor)
Překlad abstraktu The Bachelor’s thesis deals with the question of utilizing pressure values measured by pressure inserts for calculating the performance of cyclists. Since this method has not been used in cycling before, the result of this work can be applied to expanding the methods of measuring performance in this sport in the future. The goal was to verify whether the use of this conversion is applicable in practice. This goal was verified by obtaining data during practical measurements, subsequent analysis of this data, and comparison of the results with other methods currently used for measuring performance in cycling.
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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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Averaging of biological signals
Němeček, Tomáš ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
The main objectives of this thesis are to study theory of signal averaging, filtered residue method and methods of stretching/shrinking signal. It will also test the functionality of those methods. Thesis contains theoretical analysis, explanation of principles and testing of behaving of used methods.
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Sleep scoring using EEG
Holdova, Kamila ; Smital, Lukáš (referee) ; Ronzhina, Marina (advisor)
This thesis deals with wavelet analysis of sleep electroencephalogram to sleep stages scoring. The theoretical part of the thesis deals with the theory of EEG signal creation and analysis. The polysomnography (PSG) is also described. This is the method for simultaneous measuring the different electrical signals; main of them are electroencephalogram (EEG), electromyogram (EMG) and electrooculogram (EOG). This method is used to diagnose sleep failure. Therefore sleep, sleep stages and sleep disorders are also described in the present study. In practical part, some results of application of discrete wavelet transform (DWT) for decomposing the sleep EEGs using mother wavelet Daubechies 2 „db2“ are shown and the level of the seven. The classification of the resulting data was used feedforward neural network with backpropagation errors.
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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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QRS complex detection in multilead ECG signals
Šlancar, Matěj ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
The aim of this thesis is to introduce the principles of software QRS detection, which is based on different combinations of orthogonal (pseudoorthogonal) leads. The thesis describes the main components of the ECG signal, a selection of methods that can be used for QRS detection in orthogonal leads and finally the evaluation of the effectiveness of the chosen methods and a comparing the approaches with the results of other authors. Functionality of detection algorithm has been tested on signals of CSE standard library.
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ECG baseline wander correction based on the empirical mode decomposition
Šlancar, Matěj ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
The aim of this thesis is to introduce with principle of Empirical Mode Decomposition method and possibility use for correction of baseline wander in ECG signals. The thesis describes the main components of the ECG signal, a selection of possible types of signal noise, its property and principles of chosen methods for filtration of ECG signals. In conclusion the evaluation of the effectiveness of the EMD method for filtering a baseline wander and it comparing with effectiveness of the linear filtration. Functionality of used algorithms has been tested on signals of CSE standard library.
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Biometric fingerprint identification
Dašek, Filip ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
In biometrics we use distinctive physical features for identification and verification of identity. The most famous technique is identification by fingerprints. This technique use unique structure created by papillary lines for unambiguous identification. Thesis contains methods which were created throughout the years for analysis and adjustments of fingerprint. The algorithm is based on compairng two pairs of minitua and calculating transform matrix for correct alignment. Algorithm is tested on dataset created from LivDet databases. Performance of algorithm is represented by value EER which is compared with EERs of other algorithms tested in FVC 2006.
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