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Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A03099085" target="_blank" >RIV/68407700:21230/04:03099085 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

High-Speed Feature Extraction in Holter Electrocardiogram Using Principal Component Analysis

Popis výsledku v původním jazyce

Due to their long duration (up to 48 hours) and because of the enormous quantity of beats involved, it results really difficult to perform a manual inspection of HOLTER electrocardiographic signals (ECG). In the other side, we have patients with chronicheart-troubles whose heart rithm needs to be checked everytime using portable ECG recording machines. Within this scenario it would be very interesting the possibility of real-time ANALYZING and clustering ECG records in order to detect arrhythmia beatsas soon as possible, allowing the patient to realize and prevent from a critical heart attack. To achieve this goal we have designed and implemented a C++ application that is based on the Principal Component Analysis (PCA) method applied to the beats (from a portable ECG recording machine) to decompose and cluster them in real-time. At the first stage of this article we will define holter ECG records and discuss about their desirable features for processing them ensuring better results y

Název v anglickém jazyce

High-Speed Feature Extraction in Holter Electrocardiogram Using Principal Component Analysis

Popis výsledku anglicky

Due to their long duration (up to 48 hours) and because of the enormous quantity of beats involved, it results really difficult to perform a manual inspection of HOLTER electrocardiographic signals (ECG). In the other side, we have patients with chronicheart-troubles whose heart rithm needs to be checked everytime using portable ECG recording machines. Within this scenario it would be very interesting the possibility of real-time ANALYZING and clustering ECG records in order to detect arrhythmia beatsas soon as possible, allowing the patient to realize and prevent from a critical heart attack. To achieve this goal we have designed and implemented a C++ application that is based on the Principal Component Analysis (PCA) method applied to the beats (from a portable ECG recording machine) to decompose and cluster them in real-time. At the first stage of this article we will define holter ECG records and discuss about their desirable features for processing them ensuring better results y

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2004

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Analysis of Biomedical Signals and Images

ISBN

80-214-2633-0

ISSN

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e-ISSN

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Počet stran výsledku

3

Strana od-do

81-83

Název nakladatele

VUTIUM Press

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

23. 6. 2004

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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