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Measurement of ECG signal for TWA analysis
Řezáč, Petr ; Vítek, Martin (referee) ; Kozumplík, Jiří (advisor)
The thesis deals with possibilities of using wavelet transform in the field of surface electrocardiogram (ECG) signals denoising and ECG signals measuring. Several algorithms have been used to detect and estimate T-wave alternans (TWA), such as spectral method (SM), Poincaré Mapping (PM) or correlation method (CM). T-wave alternans, also called repolarization alternans, is a phenomenon appearing in the electrocardiogram as a consistent fluctuation in the repolarization morphology on every-other-beat basis. Electrical TWA has been recognized as a marker of electrical instability, and has been shown to be related with patients at increased risk for ventricular arrhytmias. Presence of TWA has been reported in a wide range of clinical and experimental situations including long QT syndrome, myocardial infarction, angina pectoris, acute ischemia, etc. Projected methods of detection TWA are realized in Matlab software, and they are experimentally verified on real ECG signals from the European ST-T Database.
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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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Wiener Wavelet Filtering of ECG Signals
Sizov, Vasily ; Vítek, Martin (referee) ; Kozumplík, Jiří (advisor)
Tato práce se zabývá možností využití vlnkové transformace v aplikacích, které se zabývají potlačením šumu. Především se jedná o oblast filtrace signálu EKG. Úkolem je zhodnotit vliv různých parametrů nastavení samotné filtrace a zjistit jaký vliv má různé nastavení prahování wavelet koeficientů. Výsledkem práce je také stanovení hodnot prahů, stanovení nejlepšího způsobu rozkladu signálu a volba rekonstrukčních bank filtrů. Text obsahuje výsledky Wienerovy filtrace, při které byly testovány různé banky rozkladových a rekonstrukčních filtrů.Všechny popsané filtrační metody byly testovány na reálných záznamech EKG s aditivním myopotenciálním šumem. Algoritmy byly realizovány v prostředí MATLAB.
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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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Muscle noise filtering in ECG signals
Novotný, Jiří ; Kubičková, Alena (referee) ; Smital, Lukáš (advisor)
This master's thesis deals with the optimization of numerical coefficients of the Wiener filter for muscle noise filtering in ECG signals. The theoretical part deals with ECG signal characteristic and muscle interference. It also contains a summary of the wavelet transform, wavelet Wiener's filtration, methods for calculating of the threshold and thresholding. In the last theoretical part the characteristic optimization techniques, the exhausive search and Nelder-Mead simplex method are mentioned, which were implemented in the practical part of this thesis in MATLAB. The functional verification and Wiener's filter optimization were tested on the standard electrocardiograms database CSE. By using the methods of exhausive search, the initial estimate for the solution method Nelder-Mead was obtained. The optimization method Nelder-Mead gives better results in the orders of hundredths or tenths than the method of exhausive search. The practical part is finished by the comparison of results of implemented algorithm with optimum coefficients, implemented in this thesis, with the results of other methods for filtering muscle interference in ECG signals.
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ECG quality estimation
Vršková, Markéta ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This master thesis solves the problem of estimating the quality of ECG signals. The main objective of the work is to implement a self-assessment of the quality assessment method based on the studied methods for estimating the quality of the ECG signal. The theoretical part of the thesis contains mainly the description of the electrical activity of the heart, cardiac anatomy, and physiology, electrocardiography, various types of ECG signal interference and methods describing the estimation of ECG signal quality. The practical part deals with the application of individual methods for estimating the quality of ECG signals. The SNR (signal-to-noise ratio) calculation is used to continuously estimate the quality of the ECG. Signal quality can also be judged based on statistical functions, adaptive filtering, or by analyzing independent components. The proposed method is based on the calculation of the correlation coefficient between the adaptive template and the disturbed signal. The robustness of the method was verified on artificially created ECG signals with different noise levels and then on real signals from the MIT-BIH database.
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ECG quality estimation
Vršková, Markéta ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This master thesis solves the problem of estimating the quality of ECG signals. The main objective of the work is to implement a self-assessment of the quality assessment method based on the studied methods for estimating the quality of the ECG signal. The theoretical part of the thesis contains mainly the description of the electrical activity of the heart, cardiac anatomy, and physiology, electrocardiography, various types of ECG signal interference and methods describing the estimation of ECG signal quality. The practical part deals with the application of individual methods for estimating the quality of ECG signals. The SNR (signal-to-noise ratio) calculation is used to continuously estimate the quality of the ECG. Signal quality can also be judged based on statistical functions, adaptive filtering, or by analyzing independent components. The proposed method is based on the calculation of the correlation coefficient between the adaptive template and the disturbed signal. The robustness of the method was verified on artificially created ECG signals with different noise levels and then on real signals from the MIT-BIH database.
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Wiener Wavelet Filtering of ECG Signals
Sizov, Vasily ; Vítek, Martin (referee) ; Kozumplík, Jiří (advisor)
Tato práce se zabývá možností využití vlnkové transformace v aplikacích, které se zabývají potlačením šumu. Především se jedná o oblast filtrace signálu EKG. Úkolem je zhodnotit vliv různých parametrů nastavení samotné filtrace a zjistit jaký vliv má různé nastavení prahování wavelet koeficientů. Výsledkem práce je také stanovení hodnot prahů, stanovení nejlepšího způsobu rozkladu signálu a volba rekonstrukčních bank filtrů. Text obsahuje výsledky Wienerovy filtrace, při které byly testovány různé banky rozkladových a rekonstrukčních filtrů.Všechny popsané filtrační metody byly testovány na reálných záznamech EKG s aditivním myopotenciálním šumem. Algoritmy byly realizovány v prostředí MATLAB.
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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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Muscle noise filtering in ECG signals
Novotný, Jiří ; Kubičková, Alena (referee) ; Smital, Lukáš (advisor)
This master's thesis deals with the optimization of numerical coefficients of the Wiener filter for muscle noise filtering in ECG signals. The theoretical part deals with ECG signal characteristic and muscle interference. It also contains a summary of the wavelet transform, wavelet Wiener's filtration, methods for calculating of the threshold and thresholding. In the last theoretical part the characteristic optimization techniques, the exhausive search and Nelder-Mead simplex method are mentioned, which were implemented in the practical part of this thesis in MATLAB. The functional verification and Wiener's filter optimization were tested on the standard electrocardiograms database CSE. By using the methods of exhausive search, the initial estimate for the solution method Nelder-Mead was obtained. The optimization method Nelder-Mead gives better results in the orders of hundredths or tenths than the method of exhausive search. The practical part is finished by the comparison of results of implemented algorithm with optimum coefficients, implemented in this thesis, with the results of other methods for filtering muscle interference in ECG signals.
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