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rdf:type
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Description
| - In this work we investigate the use of wavelet packets transform as a mean to extract features capable of providing the information needed by a classifier for discrimination between normal beats (N), premature ventricular (V), left bundle branch block beat 'L' and right bundle branch block beat 'R'. We have used our approach of feature extraction which is based on wavelet packets decomposition of window with QRS complex and on the method of wavelet packet tree node selection. This selection has been performed as finding of the path with maximum of relative entropy between current beat and template. We have used the MIT-BIH arrhythmia database for testing this approach. The database was divided into two subsets for training and testing the classifier. Results of the classification are evaluated by the sensitivity (Se), specificity (Sp) and overall accuracy. We obtained sensitivity 81,1%, 98,5%, specificity 95,1% and 97,5% overall accuracy for ventricular beat.
- In this work we investigate the use of wavelet packets transform as a mean to extract features capable of providing the information needed by a classifier for discrimination between normal beats (N), premature ventricular (V), left bundle branch block beat 'L' and right bundle branch block beat 'R'. We have used our approach of feature extraction which is based on wavelet packets decomposition of window with QRS complex and on the method of wavelet packet tree node selection. This selection has been performed as finding of the path with maximum of relative entropy between current beat and template. We have used the MIT-BIH arrhythmia database for testing this approach. The database was divided into two subsets for training and testing the classifier. Results of the classification are evaluated by the sensitivity (Se), specificity (Sp) and overall accuracy. We obtained sensitivity 81,1%, 98,5%, specificity 95,1% and 97,5% overall accuracy for ventricular beat. (en)
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Title
| - ECG Beat Classification Using Feature Extraction from Wavelet Packets of R Wave Window
- ECG Beat Classification Using Feature Extraction from Wavelet Packets of R Wave Window (en)
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skos:prefLabel
| - ECG Beat Classification Using Feature Extraction from Wavelet Packets of R Wave Window
- ECG Beat Classification Using Feature Extraction from Wavelet Packets of R Wave Window (en)
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skos:notation
| - RIV/68407700:21230/09:00158541!RIV10-AV0-21230___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/68407700:21230/09:00158541
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - wavelet transform; wavelet packets; feature extraction; local discriminant bases; ECG; arrhythmias (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Huptych, Michal
- Lhotská, Lenka
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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issn
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number of pages
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http://purl.org/ne...btex#hasPublisher
| - Springer Science+Business Media
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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