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Classification of heart beats from multilead ECG using principal component analysis
Vlček, Milan ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
The resume of this master´s thesis is to introduce reader into principal component analysis (PCA), namely, the use of PCA for analysis of ECG. This method allows to reduce quantity of the data without loss of useful information. That is why PCA is widespread for preprocessing of the data for further classification, which this thesis also deals. Data available at the Department of Biomedical Engineering at the University of Technology in Brno were used in this work. All the methods were realized using Matlab.
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QRS detection using zero crossing counting
Hanus, Rostislav ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This master’s thesis deals with the detection of QRS complex detection using zero crossing counts. QRS detection is an important part of the analysis of ECG signal. From the point of determining the R wave detection is based on the other waves and intervals necessary for the diagnosis of heart. This method is very effective even for very noisy signals. Implementation of the method in Matlab, and the success of detection is tested on the CSE and MIT-BIH database. The optimization algorithm is an optional value for the detector.
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Classification of ECG by artificial neural networks
Loviška, David ; Vítek, Martin (referee) ; Hrubeš, Jan (advisor)
The aim of project with name Classification ECG by artificial neural networks is simplify and speed up working a doctor. That reaches created program that the is capable simply and almost at once classify EKG signal using artificial neuronal nets. Created program will give to the doctor basic information about used electrocardiogram, as are time period and amplitude signal in single surveyed sections. Subsequently will program warn doctor about abnormalities from normal. Part of program is also graphic window with painted signal and on him in color points and partitions marked by program behind special. In next phase program alone classifies gained data and designating without doctor diagnose that doctor can evaluate and in case agreeable it sign and place for true diagnose patient. This program is also fit for data reading from bigger of the number of hours as far as days. It is concerned primarily Holter ECG monitoring.
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Analysis of EEG signal using principal component analysis (PCA)
Walczysko, Martin ; Vítek, Martin (referee) ; Rychtárik, Milan (advisor)
In the beginning of the bachelor’s thesis is dealt with the measurement of EEG signals in the laboratory of Department of Biomedical Engineering at FEEC BRNO and following processing in programming environment Matlab. The aim of the thesis tries to demonstrate the analysis of EEG dates using the principal components analysis. There are shown the using possibilities for reducing the dimension of input’s dates. It is considered the lay-out of electrodes, the duration of recording or existing artifact. There is also conducted a study of highlighting the abnormalities contained in EEG in order to easier detection. In the end are outlined the possibilities of using the ICA for analysis of EEG and eventually for removing unwanted artifacts.
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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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Multilead decision rules in delineation of ECG signals
Richter, Zdeněk ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This work deals with ECG signal measuring and methods of its processing. It compares some of the QRS detection methods and describes some of the testing databases. In this work a detector of QRS complex is realized, it is based on the approach of zero crossings. Next section makes combination of results from separate leads to one, which improves efficiency of detection. One section of this work deals with design and realization delination of ECG signal. In the last part outputs of this delineation are compared with the results of the other authors.
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Wavelet Filtering of ECG Signals
Mrázek, Jiří ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
This thesis deals myopotential denoising of ECG signals with using wavelet transform. There was used wavelet denoising subsequently wiener wavelet filtering. In both cases were found the most suitable coeficients for the best denoising. It is meant mainly settings suitable parameters for ideal filtration setting value of threshold, number of decomposition level, selection of thresholding and type of filter. These parameters are tested on real signals. Denoising is realized in Matlab version R2009b.
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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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Biological data averaging
Mlčoch, Marek ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
The thesis deals with the biological data averaging applied to a periodical and repetitive signal, specifically to an ECG signals. There were used signals from MIT-BIH Arrhythmia database and ÚBMI database. Averaging was realized with constant, floating and exponential Windows, where was used the method of addition of the filtered residue. This method is intended to capture the slow variations from the input to the output signal. The outcomes of these methods can be used as a basis for further work, or function as an example of principled methods. Methods and its outcomes were created in Matlab.
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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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