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Comparison of seven approaches for holter ECG clustering and classification
V. Chudacek, M. Petrik, G. Georgoulas, M. Cepek, L. Lhotska, C. Stylios
Jazyk angličtina Země Spojené státy americké
Typ dokumentu srovnávací studie
- MeSH
- algoritmy MeSH
- elektrokardiografie MeSH
- financování organizované MeSH
- lidé MeSH
- nemoci srdce klasifikace patofyziologie MeSH
- počítačové zpracování signálu MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- srovnávací studie MeSH
In this work we present a comparative study, testing selected methods for clustering and classification of holter electrocardiogram (ECG). More specifically we focus on the task of discriminating between normal 'N' beats and premature ventricular 'V' beats Some of the tested methods represent the state of the art in pattern analysis, while others are novel algorithms developed by us. All the algorithms were tested on the same datasets, namely the MIT-BIH and the AHA databases. The results for all the employed methods are compared and evaluated using the measures of sensitivity and specificity.
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- $a Gerstner Laboratory at Dept. of Cybernetics of Czech Technical University, Prague, Czech Republic. chudacv@fel.cvut.cz
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- $a In this work we present a comparative study, testing selected methods for clustering and classification of holter electrocardiogram (ECG). More specifically we focus on the task of discriminating between normal 'N' beats and premature ventricular 'V' beats Some of the tested methods represent the state of the art in pattern analysis, while others are novel algorithms developed by us. All the algorithms were tested on the same datasets, namely the MIT-BIH and the AHA databases. The results for all the employed methods are compared and evaluated using the measures of sensitivity and specificity.
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