Comparison of Baseline Wandering Removal Algorithms for Automatic Clas sification of Electrocardiogram

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of Baseline Wandering Removal Algorithms for Automatic Clas sification of Electrocardiogram

Popis výsledku v původním jazyce

Baseline wandering (sometimes also baseline drift) is a noise that exacerbates the evaluation of ECG and reduces the success of automatic ECG classifiers. In previous works, many methods have been proposed to remove such noise. The aim of this article is to compare commonly used methods. Each signal is in parallel reprocessed by all analyzed methods a nd then enters an automatic classifier that is able to classify QRS complexes. According to the classification success, the proposed methods were compared. Based on the results of this work, the best method for removing baseline wandering in the ECG is wav elet filtration. The success of the classification is further improved by the combination of wavelet filtration and EEMD. The disadvantage of this combination is its very high computational complexity .

Název v anglickém jazyce

Comparison of Baseline Wandering Removal Algorithms for Automatic Clas sification of Electrocardiogram

Popis výsledku anglicky

Baseline wandering (sometimes also baseline drift) is a noise that exacerbates the evaluation of ECG and reduces the success of automatic ECG classifiers. In previous works, many methods have been proposed to remove such noise. The aim of this article is to compare commonly used methods. Each signal is in parallel reprocessed by all analyzed methods a nd then enters an automatic classifier that is able to classify QRS complexes. According to the classification success, the proposed methods were compared. Based on the results of this work, the best method for removing baseline wandering in the ECG is wav elet filtration. The success of the classification is further improved by the combination of wavelet filtration and EEMD. The disadvantage of this combination is its very high computational complexity .

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20204 - Robotics and automatic control

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of IEEE Student Branch Conference Mikulov 2017

ISBN

978-80-214-5526-9

ISSN

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e-ISSN

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Počet stran výsledku

77

Strana od-do

63-66

Název nakladatele

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií

Místo vydání

Mikulov

Místo konání akce

Mikulov, Czech republic

Datum konání akce

28. 8. 2017

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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