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Segmentation of Hidden P Waves Using Deep Learning Methods
Boudová, Markéta ; Ronzhina, Marina (referee) ; Hejč, Jakub (advisor)
The aim of this thesis is segmentation of P waves in ECG signals. The theoretical part of the thesis describes the physiology of the heart and the basics of deep learning methods. Preprocessing of the signals is performed and neural network U-Net is implemented in the Python software environment in the practical part. Afterwards, optimization of network architecture is performed in order to reduce model complexity. Lastly the success rate of the model is evaluated.
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P wave detection in ECG signals
Bajgar, Jiří ; Kozumplík, Jiří (referee) ; Smital, Lukáš (advisor)
The aim of this diploma thesis is to introduce methods of detection of the QRS complex and the subsequent detection of P waves. The intention is to create a program by specified method in the software Matlab which will be able to implement this method. The thesis describes the basic and important methods of detection and subsequent algorithm to detect P waves. Solution of the algorithm is tested on real data. It also describes the automatic signal evaluation and the results of this automatic function.
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Analysis of difference between HRV parameters gained from PP and RR intervals
Svobodová, Sabina ; Janoušek, Oto (referee) ; Milek, Jakub (advisor)
This bachelor thesis aims to solve problems of ECG signals, respectively detection of QRS complex and P wave, and subsequent analysis of heart rate variability. The first part is focused on literary research. It deals with the heart anatomy, electrocardiography and more detailed description of individual waves, as well as with the pre-processing of ECG signal, QRS complex detection and P wave detection. The last theoretical part describes the analysis of heart rate variability. In the practical part detection of QRS complex, P wave and subsequent analysis of heart rate variability is programmed in MATLAB. Finally, statistical evaluation is performed in STATISTICA.
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Segmentation of Hidden P Waves Using Deep Learning Methods
Boudová, Markéta ; Ronzhina, Marina (referee) ; Hejč, Jakub (advisor)
The aim of this thesis is segmentation of P waves in ECG signals. The theoretical part of the thesis describes the physiology of the heart and the basics of deep learning methods. Preprocessing of the signals is performed and neural network U-Net is implemented in the Python software environment in the practical part. Afterwards, optimization of network architecture is performed in order to reduce model complexity. Lastly the success rate of the model is evaluated.
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Analysis of difference between HRV parameters gained from PP and RR intervals
Svobodová, Sabina ; Janoušek, Oto (referee) ; Milek, Jakub (advisor)
This bachelor thesis aims to solve problems of ECG signals, respectively detection of QRS complex and P wave, and subsequent analysis of heart rate variability. The first part is focused on literary research. It deals with the heart anatomy, electrocardiography and more detailed description of individual waves, as well as with the pre-processing of ECG signal, QRS complex detection and P wave detection. The last theoretical part describes the analysis of heart rate variability. In the practical part detection of QRS complex, P wave and subsequent analysis of heart rate variability is programmed in MATLAB. Finally, statistical evaluation is performed in STATISTICA.
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|
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P wave detection in ECG signals
Bajgar, Jiří ; Kozumplík, Jiří (referee) ; Smital, Lukáš (advisor)
The aim of this diploma thesis is to introduce methods of detection of the QRS complex and the subsequent detection of P waves. The intention is to create a program by specified method in the software Matlab which will be able to implement this method. The thesis describes the basic and important methods of detection and subsequent algorithm to detect P waves. Solution of the algorithm is tested on real data. It also describes the automatic signal evaluation and the results of this automatic function.
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