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Comparison of heart activity sensing devices
Babicová, Martina ; Smital, Lukáš (referee) ; Smíšek, Radovan (advisor)
The goal of this work is comparison of heart activity sensing devices. However, an ECG record cannot be evaluated with the presence of muscle interference. Removing this noise is one of the needs for device success. The theoretical part represents electrophysiology of the heart, electrocardiography, various interferences types, theoretical basis for recording of biosignals including used devices and methods signal quality estimation. The practical part is SNR (signal-to-noise ratio) calculation. The Wavelet filter and Wiener filter-based wavelet domain are used to separate the useful and noise component.
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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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Comparison Of Heart Activity Sensing Devices
Babicová, Martina
The goal of this work is comparison of heart activity sensing devices. ECG record cannot be evaluated in the presence of large amounts of muscle noise. Removing this noise is one of the needs for devices success. The discrete wavelet transform is used to separate the useful and noise component. The result is an estimate of SNR for four devices: CorScience, Faros, BiosignalPlux, CardioSignal and a comparison between them. Quality measurement and evaluation indicates that Faros device is the most reliable.
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Comparison of heart activity sensing devices
Babicová, Martina ; Smital, Lukáš (referee) ; Smíšek, Radovan (advisor)
The goal of this work is comparison of heart activity sensing devices. However, an ECG record cannot be evaluated with the presence of muscle interference. Removing this noise is one of the needs for device success. The theoretical part represents electrophysiology of the heart, electrocardiography, various interferences types, theoretical basis for recording of biosignals including used devices and methods signal quality estimation. The practical part is SNR (signal-to-noise ratio) calculation. The Wavelet filter and Wiener filter-based wavelet domain are used to separate the useful and noise component.
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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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