Adaptive threshold and principal component analysis for features extraction of electrocardiogram signals

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F14%3A00219399" target="_blank" >RIV/68407700:21220/14:00219399 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/IS3C.2014.324" target="_blank" >https://doi.org/10.1109/IS3C.2014.324</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IS3C.2014.324" target="_blank" >10.1109/IS3C.2014.324</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Adaptive threshold and principal component analysis for features extraction of electrocardiogram signals

Popis výsledku v původním jazyce

This paper presents a novel approach for QRS complex detection and extraction of electrocardiogram signals for different types of arrhythmias. Firstly, the ECG signal is filtered by a band pass filter, and then it is differentiated. After that, the Hilbert transform and the adaptive threshold technique are applied for QRS detection. Finally, the Principal Component Analysis is implemented to extract features from the ECG signal. Nineteen different records from the MIT-BIH arrhythmia database have been used to test the proposed method. A 96.28% of sensitivity and a 99.71% of positive predictivity are reported in this testing for QRS complexity detection, being a positive result in comparison with recent researches.

Název v anglickém jazyce

Adaptive threshold and principal component analysis for features extraction of electrocardiogram signals

Popis výsledku anglicky

This paper presents a novel approach for QRS complex detection and extraction of electrocardiogram signals for different types of arrhythmias. Firstly, the ECG signal is filtered by a band pass filter, and then it is differentiated. After that, the Hilbert transform and the adaptive threshold technique are applied for QRS detection. Finally, the Principal Component Analysis is implemented to extract features from the ECG signal. Nineteen different records from the MIT-BIH arrhythmia database have been used to test the proposed method. A 96.28% of sensitivity and a 99.71% of positive predictivity are reported in this testing for QRS complexity detection, being a positive result in comparison with recent researches.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Adaptive threshold and principal component analysis for features extraction of electrocardiogram signals

ISBN

978-1-4799-5277-9

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

1253-1258

Název nakladatele

IEEE Computer Society Washington

Místo vydání

Washington, DC

Místo konání akce

Taichung

Datum konání akce

10. 6. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000366660900312