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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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Implementation of wavelet transform in C++
Valouch, Lukáš ; Hasmanda, Martin (referee) ; Beneš, Radek (advisor)
The aim of this thesis is implementation of wavelet transform algorithm for noise reduction. The noise reduction itself is focused on improving informative capabilities of sonographic (ultrasound) images in medicine. For this purpose, thresholding of detailed coefficients on individual levels of multiresolution analysis was used. Common procedures were not used for searching for the most suitable thresholds of those levels. The alternative concept's design is based on fundamental empirical approach, where the individual thresholds are optimised by evolution algorithms. However, with this algorithmic procedure, more problems manifest regarding the objective evaluation of the success of noise reduction. Because of this, the program uses commonly used parameters such as mean square error of the whole image, linear slope edge approximation, relative contrast of two differently bright and distinct points and the standard deviation of compact surface. Described theoretical knowledge is used in developed application DTWT. It executes multilevel decomposition and reversed reconstruction by discrete time wavelet transform, thresholding of detailed coefficients and final evaluation of performed noise reduction. The developed tool can be used separately to reduce noise. For our purposes, it has been modified in way, that it executed through the component for evolutionary optimization of parameters (Optimize Parameters) in created scenario in RapidMiner program. In the optimization process, this component used evaluation received from DTWT program as fitness function. Optimal thresholds were sought separately for three wavelet families - Daubeschies, Symmlets and Coiflets. The evolution algorithm chose soft threshold for all three wavelet families. In comparison to hard threshold, it is more suitable for noise reduction, but it has tendencies to blur the edges more. The devised method had in most cases greater evaluated success of noise reduction with wavelet transform with threshold search done by evolution algorithms, than commonly used filters. In visual comparison however the wavelet transform introduced some minor depreciating artefacts into the image. It is always about compromise between noise reduction and maximal preservation of image information. Objectively evaluating this dilemma is not easy and is always dependant on subjective viewpoint which in case of sonographic images is that of the attending physician.
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Biosignal processing - clusetr analysis
Příhodová, Petra ; Maděránková, Denisa (referee) ; Kolářová, Jana (advisor)
This thesis deals with the problem with cluster analysis and biosignal classification options. The principle of cluster analysis, methods for calculating distances between objects and the standard process in the implementation of clustering are described in the first part. For biosignals processing,it is necessary to get familiar with the primary parameters of these signals in the following sections of thesis, process biosignals and methods for recording of action potentials described. Based on studying different clustering methods is presented a program with the applied method kmedoid in the next section of this thesis. The steps of this program are described in detail and in the end of thesis functionality is tested on a database of signals ÚBMI.
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Wavelet filtering of ECG Signals
Šugra, Marián ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
This masters thesis is focused on filtering the ECG signal for suppression of spurious frequency components of the network. The theoretical part is talking about electrocardiography, ECG signal interference and about principle different types of filtration. In practical part of this thesis are described linear filtering methods and wavelet transform methods with discrete time. The main topic of this work is recommended the best type of filtration.
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Time-frequency analysis of Czech republic gross domestic product
Tráge, David ; Poměnková, Jitka (referee) ; Maršálek, Roman (advisor)
The aim of this master's thesis is to get familier with problematic and concepts of econometrics (GDP, investment, usage and others). We see into used data mainly their characters and expectations and we discuss possibilities of frequention and time-frequention analysis of these data by Fourier and Wavelet transform. Data of quarter development of gross domestic product in Czech Republic, EU and USA will be analysed by the help of programm MATLAB. Data will be filtered by three ekonomic filters: Hodrick-Prescott, Baxter-King and Christiano-Fitzgerald filters. The aim is to find cyclic elements in developments of GDPs and to suggest an optimal type of analysis.
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Segmentation in microscopic images
T.Kovács, Matúš ; Jiřík, Radovan (referee) ; Kolář, Radim (advisor)
This thesis deals with the segmentation of microscopic images from plant sections. It describes the importance of the histogram for obtaining information from the image, and the utilization of the wavelet transformation for the preprocessing of the images. The thesis describes and categorizes different segmentation methods. In the thesis we use MATLAB for the validation of the presented theories and as the interface for creating a software model. The created software application automatically analyzes and evaluates microscopic images.
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Wavelet Filtering of ECG Signal
Slezák, Pavel ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
The thesis deals with possibilities of using wavelet transform in applications dealing with noise reduction, primarily in the field of ECG signals denoising. We assess the impact of the various filtration parameters setting as the thresholding wavelet coefficients method, thresholds level setting and the selection of decomposition and reconstruction filter banks.. Our results are compared with the results of linear filtering. The results of wavelet Wieners filtration with pilot estimation are described below. Mainly, we tested a combination of decomposition and reconstruction filter banks. All the filtration methods described here are tested on real ECG records with additive myopotential noise character and are implemented in the Matlab environment.
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Optimal detection of QRS boundaries in ECG signals
Spáčil, Jakub ; Hrubeš, Jan (referee) ; Vítek, Martin (advisor)
This diploma thesis deals with location optimal wavelet for detecton charakterics points of QRS complex in ECG signals. The first part of this thesis deals with description of heart, genesis of electric signals on heart and problem of noise. The second part describes the wavelet transform and the designed program and the third part evaluate detection results. The created program is working with 10 ECG signals from the CSE database and is testing 12 different mother wavelets. The program was developed in Matlab environment and is based on the finding zero-points in the transformed signal.
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QRS Complex Detection Using Wavelet Transform
Loviška, David ; Čech, Petr (referee) ; Smital, Lukáš (advisor)
The aim of diploma thesis named “QRS detection using wavelet transform” is to simplify and accelerate the work of doctors. This can be achieved by using application for QRS detection, which can use one of four proposed algorithms. Application shows basic informations about inserted electrocardiogram. Part of this program is a graphical window with displayed record and with coloured marks on detected QRS complexes. By another algorythm are marks color-coded due to accurancy percentil of every detected complex. This program is designed for a several hours record from Holter ECG monitoring.
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