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Wavelet Filtering of ECG Signals
Staša, Josef ; Kolář, Radim (referee) ; Kozumplík, Jiří (advisor)
The aim of this project is introduction to problems about filtering of signals using wavelet transform. This method is very effective and in present it is often exploited. The main imposition is to use wavelet transform for filtering of ECG signals. Practical part of my project is realized wiener filtering based on DTWT in MATLAB software, to show advantages, disadvantages and compare linear filtering .
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Delineation of experimental ECG data
Hejč, Jakub ; Janoušek, Oto (referee) ; Vítek, Martin (advisor)
This thesis deals with a proposition of an algorithm for QRS complex and typical ECG waves boundaries detection. It incorporates a literature research focused on heart electrophysiology and commonly used methods for ECG fiducial points detection and delineation. Out of the presented methods an algorithm based on a continuous wavelet transform is implemented. Detection and delineation algorithm is tested on CSE standard signal database towards references determined both manually and automatically. Obtained results are compared to other congenerous methods. The diploma thesis is further concerned with an algorithm modification for experimental electrocardiograms of isolated rabbit hearts. Recording specifics of these data are introduced. Additionally, based on time and frequency analysis, particular modifications of the algorithm are proposed and realized. Due to a large extent of records functionality is verified on randomly selected database samples. Efficiency of the modified algorithm is evaluated through manually annotated references.
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Monitoring Trends of Electrical Activity of the Heart Using Time-Frequency Decomposition
Čáp, Martin ; Kozumplík, Jiří (referee) ; Provazník, Ivo (advisor)
Work is aimed at the time-frequency decomposition of a signal application for monitoring the EKG trend progression. Goal is to create algorithm which would watch changes in the ST segment in EKG recording and its realization in the Matlab program. Analyzed is substance of the origin of EKG and its measuring. For trend calculations after reading the signal is necessary to preprocess the signal, it consists of filtration and detection of necessary points of EKG signal. For taking apart, also filtration and measuring the signal is used wavelet transformation. Source of the data is biomedicine database Physionet. As an outcome of the algorithm are drawn ST segment trends for three recordings from three different patients and its comparison with reference method of ST qualification. For qualification of the heart stability, as a system, where designed methods watching differences in position of the maximal value in two-zone spectrum and the Poincare mapping method. Realized method is attached to this thesis.
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ECG Signal Compression Based on Wavelet Transform
Ondra, Josef ; Hrubeš, Jan (referee) ; Kozumplík, Jiří (advisor)
Signal compression is daily-used tool for memory capacities reduction and for fast data communication. Methods based on wavelet transform seem to be very effective nowadays. Signal decomposition with a suitable bank filters following with coefficients quantization represents one of the available technique. After packing quantized coefficients into one sequence, run length coding together with Huffman coding are implemented. This thesis focuses on compression effectiveness for the different wavelet transform and quantization settings.
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Time-frequency analysis of electrograms
Doležal, Petr ; Ronzhina, Marina (referee) ; Kolářová, Jana (advisor)
This thesis deals with time-frequency analysis of electrograms measured on isolated guinea pig hearts perfused according to Langendorff. Time-frequency analysis is based on algorithms Matching Pursuit and Wigner-Ville Distribution. The theoretical part describes the basics of electrocardiography, measurement on isolated hearts, the theory of approximation method Matching Pursuit and its combination with the Wigner-Ville distribution spectrum showing the energy density of the signal. Also other common approaches of time-frequency analysis are presented including the theory of continuous wavelet transform. The presented algorithms were tested on a set of electrograms, on which were induced ischemia within measurement followed by reperfusion. The proposed method allows for the fast detection of ischemia without any a priori knowledge of the signal, and also serves as a tool for measurement of EG important points and intervals. In the conclusion efficacy of the method was presented and its possible uses has been discussed.
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Time-Frequency Signal Analysis
Kovačev, Radovan ; Polok, Lukáš (referee) ; Bařina, David (advisor)
The main subject of this work represents the time-frequency signal analysis. Firstly, it intends to provide the most essential theoretical background with focus on the continuous wavelet transform, where also a comparison of the key features with its close relative the short-time Fourier transform is performed. Afterwards, there follows a demonstration of the purpose with a practical example. The particular aim is to create a phase vocoder solution for modifying the length of a sound record duration and pitch shifting. Here, in this place, the functional principles, design, procedure of assembling, outputs and achieved results are well documented.
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ECG signal filtering in the wavelet domain
Zedníček, Vlastimil ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
The aim of this work is introduction with the method of filtering the signal using wavelet transform. Our task was to use a redundant wavelet transform for filtering ECG signals. First we met with wavelet filtering. In the practical part, we implemented a filter based on redundant DTWT in Matlab. The results were evaluated based on the achieved signal / noise ratio. The proposed filter, we tested the CSE database, and we tried to optimize the filter parameters and the degree of decomposition of wavelet transform, the bank decomposition and reconstruction filters, thresholding methods and threshold setting. The results were evaluated based on the achieved signal / noise ratio. as a last resort, we compared the results obtained with the results of different filtering methods
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ECG Signal Wavelet Filtering
Zahradník, Radek ; Kozumplík, Jiří (referee) ; Smital, Lukáš (advisor)
The aim of this work is introduction to problems about the wavelet transform and then to use this transformation to filter ECG signal disturbed with myopotentials. The first part of this thesis contains basic information about the measurement, waveform and disturbance of ECG signal. The next part describes the method of wavelet transform and its use for the signal filtering The last part describes the practical part of work, where the results of filtering with different filter settings are evaluated, especially the various types of thresholding. At the end of this part is a comparison of results from wavelet and linear filter.
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Identifikace finančních cyklů v eurozóně
Šmídová, Petra
Šmídová, P. Identification of financial cycles in euro area. Diploma thesis. Brno: Mendel University, 2023. This diploma thesis examines financial cycles in euro area countries using wavelet analysis. This method has significant advantages compared to the methods presented in the theoretical part of the thesis. The wavelet analysis allows to investigate both the time and the frequency domain at the same time and does not work with the assumption of the frequencies in which the financial cycle should be located. Credit and house prices were used as indicators of financial cycles. Statistically significant cycles in credit and house prices for individual euro area countries were identified in a Continuous Wavelet Transform. In the second section of the empirical part, a Wavelet Coherence Analysis was performed in order to answer the question whether financial cycles in the euro area are synchronised. Based on the results obtained, recommendations for macroprudential policy makers were made
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