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.
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:442578 |
Date | January 2021 |
Creators | Boudová, Markéta |
Contributors | Ronzhina, Marina, Hejč, Jakub |
Publisher | Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií |
Source Sets | Czech ETDs |
Language | Czech |
Detected Language | English |
Type | info:eu-repo/semantics/masterThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
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