About: Number of arrhythmia beats determination in Holter electrocardiogram: How many clusters?

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Holter signals correspond to long-term electrocardiograph (ECG) registers. Manual inspection of such signals is difficult because of the enormous quantity of beats involved. Throughout the literature several methods of automatically detecting and separating the significant beats using unsupervised learning were proposed. An important part of the unsupervised learning problem is determining the number of constituent clusters which best describe the data. In this paper we concentrate on the problem of the number of arrhythmia beats-clusters selection presented in Holter ECG. We apply and compare several criteria for assessing the number of clusters and we show that, with a Gaussian mixture model, the approach is able to select 'an optimal' number of arrhythmia beats and so partition a Holter ECG. The following criteria has been examined: Bayesian selection method, Akaike's information criteria, minimum description length, minimum message length, fuzzy hyper volume, evidence density and . Holter signals correspond to long-term electrocardiograph (ECG) registers. Manual inspection of such signals is difficult because of the enormous quantity of beats involved. Throughout the literature several methods of automatically detecting and separating the significant beats using unsupervised learning were proposed. An important part of the unsupervised learning problem is determining the number of constituent clusters which best describe the data. In this paper we concentrate on the problem of the number of arrhythmia beats-clusters selection presented in Holter ECG. We apply and compare several criteria for assessing the number of clusters and we show that, with a Gaussian mixture model, the approach is able to select 'an optimal' number of arrhythmia beats and so partition a Holter ECG. The following criteria has been examined: Bayesian selection method, Akaike's information criteria, minimum description length, minimum message length, fuzzy hyper volume, evidence density and . (en)
Title	Number of arrhythmia beats determination in Holter electrocardiogram: How many clusters? Number of arrhythmia beats determination in Holter electrocardiogram: How many clusters? (en)
skos:prefLabel	Number of arrhythmia beats determination in Holter electrocardiogram: How many clusters? Number of arrhythmia beats determination in Holter electrocardiogram: How many clusters? (en)
skos:notation	RIV/68407700:21220/03:03088729!RIV/2004/MSM/212204/N
http://linked.open.../vavai/riv/strany	2845 ; 2848
http://linked.open...avai/riv/aktivita	Z
http://linked.open...avai/riv/aktivity	Z(MSM 210000012)
http://linked.open...vai/riv/dodaniDat	2004
http://linked.open...aciTvurceVysledku	Lhotská, Lenka Novák, Daniel
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta strojní
http://linked.open...dnocenehoVysledku	618512
http://linked.open...ai/riv/idVysledku	RIV/68407700:21220/03:03088729
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Cluster analysis; Gaussian mixture models; Holter electrocardiogram model selection; unsupervised learning (en)
http://linked.open.../riv/klicoveSlovo	Gaussian mixture models Cluster analysis Holter electrocardiogram model selection unsupervised learning
http://linked.open...ontrolniKodProRIV	[643A7E885791]
http://linked.open...v/mistoKonaniAkce	Cancun
http://linked.open...i/riv/mistoVydani	Piscataway
http://linked.open...i/riv/nazevZdroje	EMBC 2003
http://linked.open...in/vavai/riv/obor	JC
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	4 (xsd:int)
http://linked.open...UplatneniVysledku	2003
http://linked.open...iv/tvurceVysledku	Lhotská, Lenka Novák, Daniel Cuesta-Frau, D. Mico Tormos, P.
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2003-09-17 (xsd:date)
http://linked.open...n/vavai/riv/zamer	http://linked.opendata.cz/resource/domain/vavai/zamer/MSM%20210000012
number of pages	4 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE
https://schema.org/isbn	0-7803-7790-7
http://localhost/t...ganizacniJednotka	21220

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