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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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Fast Digital filters for ECG Signals
Ráček, Tomáš ; Vítek, Martin (referee) ; Kozumplík, Jiří (advisor)
In the thesis there are described the implementations of various types of filters to remove disturbing signals, which often degrade the ECG signal. In particular, it is a zero isoline fluctuations and power network interference. It is used a principle of the Lynn’s linear filters. The individual filters are designed in a recursive and non-recursive implementation. Then there is described a time-varying linear Lynn's filter for removing drift of zero isoline signal. The thesis also includes filters with minimized calculating time of response, by sampling rate conversion method for both interference types. In conclusion there is an experimental study of the filter implementation for ECG signal with false and real interferences.
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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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Use of HRV analysis for automatic detection of ischemia in animal isolated heart
Vykoupil, Pavel ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This paper deals with HRV analysis, creating segments for this analysis, calculating HRV parameters and their classification for automatic detection of ischemia. First part of the work is dedicated to theoretical describtion of heart anatomy, ECG reading, its processing and methods of HRV analysis. Next part of this work outline the principle of creating segments used for calculation of HRV parameters. Last part of the work indtroduces classification of said parameters with the help of multilayered neural networks and finding their best possible setup based on least classification error and computing time achieved. Calculation of HRV parameters and classification was realized using software Matlab.
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Automatic delineation of ECG signals
Zimolka, Jakub ; Ronzhina, Marina (referee) ; Vítek, Martin (advisor)
This project describes selected methods of the QRS detection and ECG delineation. The theoretical part describes the principles of electrocardiography, certain QRS complex measurment methods, and contains a brief introduction into the wavelet transform theory. The paper also detailes the ECG delineation method by Laguna, Jané, and Caminal. The practice of algorith realization for the ECG delineation based on this method is ilustrated. As a conclusion, the statistical evaluation of the drafted algorithm is composed, and also its respective comparison with method and other authors is provided.
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Analysis of measured parameters of the cardiovascular system
Lysoň, Jakub ; Vítek, Martin (referee) ; Kratochvíla, Jiří (advisor)
This bachelor thesis talks about the measurement of heart electrical activity by twelve lead ECG. The diagnostic system Biopac is used for measurement, featured by the computer program Acqknowledge. The own authentic method is designed to detect effect of load on increasing in blood pressure and heartbeat. Using a statistical procedure for testing hypotheses in this area the measurement results will be evaluated. For the analysis of measured data in time and frequency domain was used program Matlab, in which the measured results were imported. It was created functions that are implemented in an medium of Guide to the graphic design program.
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Automatic delineation of ECG signals
Žiak, Milan ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This thesis deals about automatic delineation of ECG. We use algorithm, which is descriped by autors Lagune, Jané and Caminale. Their work uses first derivation for delineation ECG signal. This bachelor thesis also uses a wavelet transform to reach better results.
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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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QT interval measurement in electrograms
Ondráček, Vladimír ; Vítek, Martin (referee) ; Kolářová, Jana (advisor)
This diploma thesis focuses on determination of the QT interval in ECG. The thoretical part desribes physiology of the heart, electronic activity of the heart and possible methods of ECG measurement. The theoretical part also describes methods of signal processing, the processed signal is then used for determination of the QT interval. The practical part focuses on two chosen methods of QT interval determination and on implementation of the methods in a computer program. The results part is evaluation of measured QT intervals and a comparision of the results with reference values.
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Recognition of vehicles using signals sensed by smartphone
Nevěčná, Leona ; Vítek, Martin (referee) ; Smíšek, Radovan (advisor)
Thanks to the development in recent years, the placement of miniaturized sensors such as accelerometers, gyroscopes, magnetometers, global positioning system receivers (GPS), microphones or others to commercially sold smartphones is increasing. Use of these sensors (which are to be found in the smartphone) for human activity recognition with health care improvement in mind is a discussed theme. Advantages of the use of smartphone for human movement monitoring lies in the fact that it is a device that the person measured carries with them and there are no additional costs. The disadvantages are a limited storage and battery. Therefore, only accelerometer, gyroscope, magnetometer, and microphone were chosen because their combination achieves best results. GPS sensor was excluded for its lack of reliability in sampling and for being energy demanding. Features were computed from the measured data and used for learning of the classification model. The highest accuracy was achieved with the use of a machine learning method called Random Forest. The main goal of this work was to create an algorithm for transportation mode recognition using signals sensed by a smartphone. The created algorithm succeeds in classification of walk, car, bus, tram, train, and bike in 97.4 % with 20 % holdout validation. When tested on a new set of data from the tenth volunteer, the resulting accuracy counted as average form classification recall for each transportation mode reached 90.49 %.
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