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Maximization of ECG signals diagnostic yield
Beháňová, Andrea ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This bachelor thesis deals with the maximization of ECG signals diagnostic yield. In the theoretical section we deal with the physiology of the heart, electrocardiography, types of ECG noises. It describes some known methods for the estimation of quality of the ECG signal. The practical section contains two parts. The first one contains a continuous Signal-to-Noise Ratio (SNR). It includes generating artificial ECG signal, artificial myopotentials and implementation of Adaptive Wiener Wiener Filtrate (AWWF). After verification of the correctness of the filter on the artificial data, we started to use real data from MIT-BIH database. The second part involves a segmentation process that divides the ECG signal into three categories: a signal suitable for full analysis, suitable for detection of QRS complexes and a signal unsuitable for further analysis.
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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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Maximization of ECG signals diagnostic yield
Beháňová, Andrea ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This bachelor thesis deals with the maximization of ECG signals diagnostic yield. In the theoretical section we deal with the physiology of the heart, electrocardiography, types of ECG noises. It describes some known methods for the estimation of quality of the ECG signal. The practical section contains two parts. The first one contains a continuous Signal-to-Noise Ratio (SNR). It includes generating artificial ECG signal, artificial myopotentials and implementation of Adaptive Wiener Wiener Filtrate (AWWF). After verification of the correctness of the filter on the artificial data, we started to use real data from MIT-BIH database. The second part involves a segmentation process that divides the ECG signal into three categories: a signal suitable for full analysis, suitable for detection of QRS complexes and a signal unsuitable for further analysis.
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