Discriminating between V and N Beats from ECGs Introducing an Integrated Reduced Representation along with a Neural Network Classifier
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00203834" target="_blank" >RIV/68407700:21230/09:00203834 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007%2F978-3-642-04277-5_49#page-1" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-642-04277-5_49#page-1</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Discriminating between V and N Beats from ECGs Introducing an Integrated Reduced Representation along with a Neural Network Classifier
Original language 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 ofa 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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Artificial Neural Networks - ICANN 2009 19th International Conference, Limassol, Cyprus, September 14-17, 2009, Proceedings, Part II
ISBN
978-3-642-04276-8
ISSN
0302-9743
e-ISSN
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Number of pages
10
Pages from-to
485-494
Publisher name
Springer
Place of publication
Berlin
Event location
Limassol
Event date
Sep 14, 2009
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000275896800049