This paper deals with the classification of ECG measured from isolated rabbit hearts during the experiment with repeated ischemia. Classification features were calculated using the methods of heart rate variability analysis. The results were statistically evaluated. Heart rate variability parameters were calculated using Kubios HRV, other calculations were performed in MATLAB. Artificial neural network was created to classify the analyzed parameters to specific groups.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:220051 |
| Date | January 2013 |
| Creators | Caha, Martin |
| Contributors | Vítek, Martin, Ronzhina, Marina |
| 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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