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Description
| - The main objective of this paper is to investigate and propose a new approach to distinguish between two classes of beats from the ECG holter recordings - the premature ventricular beats (V) and the normal ones (N). The integrated methodology consists of a specific sequence: R-peak detection, feature extraction, Principal Component Analysis dimensionality reduction and classification with a neural classifier. ECG heats of hotter recordings are described using means as simple as possible resulting in a description of the QRS complex by features derived mathematically from the signal using only R-peak detection. For this research work, normal (N) and ventricular (V) beats from the well known MIT-BIH database were used to test the proposed methodology. The results are promising paving the way for the more demanding multiclass classification problem.
- The main objective of this paper is to investigate and propose a new approach to distinguish between two classes of beats from the ECG holter recordings - the premature ventricular beats (V) and the normal ones (N). The integrated methodology consists of a specific sequence: R-peak detection, feature extraction, Principal Component Analysis dimensionality reduction and classification with a neural classifier. ECG heats of hotter recordings are described using means as simple as possible resulting in a description of the QRS complex by features derived mathematically from the signal using only R-peak detection. For this research work, normal (N) and ventricular (V) beats from the well known MIT-BIH database were used to test the proposed methodology. The results are promising paving the way for the more demanding multiclass classification problem. (en)
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Title
| - Discriminating between V and N Beats from ECGs Introducing an Integrated Reduced Representation along with a Neural Network Classifier
- Discriminating between V and N Beats from ECGs Introducing an Integrated Reduced Representation along with a Neural Network Classifier (en)
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skos:prefLabel
| - Discriminating between V and N Beats from ECGs Introducing an Integrated Reduced Representation along with a Neural Network Classifier
- Discriminating between V and N Beats from ECGs Introducing an Integrated Reduced Representation along with a Neural Network Classifier (en)
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skos:notation
| - RIV/68407700:21230/09:00203834!RIV13-MSM-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/68407700:21230/09:00203834
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - Holter Monitoring; PCA; Neural Networks; MLP Classification (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
| - Artificial Neural Networks - ICANN 2009 19th International Conference, Limassol, Cyprus, September 14-17, 2009, Proceedings, Part II
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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...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Chudáček, Václav
- Huptych, Michal
- Lhotská, Lenka
- Georgoulas, G.
- Stylios, Ch.
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http://linked.open...vavai/riv/typAkce
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http://linked.open...ain/vavai/riv/wos
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http://linked.open.../riv/zahajeniAkce
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http://linked.open...n/vavai/riv/zamer
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issn
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number of pages
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http://purl.org/ne...btex#hasPublisher
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https://schema.org/isbn
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http://localhost/t...ganizacniJednotka
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