This diploma thesis is devoted to segmentation of ECG signal based on its quality and compression of quality segments suitable for diagnostics (in telemedicine). A completely new approach is to use accelerometer data to estimate ECG signal quality. This is possible thanks to the Bittium Faros mobile recorder. It records both the ECG signal motion – accelerometric data. A total of 34 features were extracted from accelerometric data. Using these features the predictive model was taught to classify the ECG signal into 3 quality groups according to the level of noise. Quality segments were compressed. The wavelet transform in combination with high-frequency bands zeroing and length encoding was used as a compression method.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:400966 |
| Date | January 2019 |
| Creators | Opravilová, Kamila |
| Contributors | Smital, Lukáš, Němcová, Andrea |
| 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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