A two-stage feature extraction approach for ECG signals

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241895" target="_blank" >RIV/61989100:27240/18:10241895 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-60834-1_30" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-60834-1_30</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-60834-1_30" target="_blank" >10.1007/978-3-319-60834-1_30</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A two-stage feature extraction approach for ECG signals

Popis výsledku v původním jazyce

This paper investigate various techniques of extracting features from the electrocardiogram (ECG) signal in order to analyze the ECG signals to detect the heart disease. Feature extraction, is a one of the widespread process of decompose the ECG data. This paper introduce a two-stage feature extraction approach to extract features from ECG signals for different types of arrhythmias. Firstly, Modified Pan-Tomkins Algorithm (MPTA) is implemented to remove noise and extract nine features. Then the proposed Improved Feature Extraction Algorithm (IFEA) is applied to extract additionally ten different features from the ECG signal. The MIT-BIH arrhythmia database have been used to test the proposed approach. It is obvious from the results that the proposed approach shows a high classification in terms of the following four statistical measures: Accuracy (Ac) 98.37%, Recall 48.29%, Precision 43.91%, F Measure 45.31%, and Specificity (Sp) 93.30%, respectively. (C) 2018, Springer International Publishing AG.

Název v anglickém jazyce

A two-stage feature extraction approach for ECG signals

Popis výsledku anglicky

This paper investigate various techniques of extracting features from the electrocardiogram (ECG) signal in order to analyze the ECG signals to detect the heart disease. Feature extraction, is a one of the widespread process of decompose the ECG data. This paper introduce a two-stage feature extraction approach to extract features from ECG signals for different types of arrhythmias. Firstly, Modified Pan-Tomkins Algorithm (MPTA) is implemented to remove noise and extract nine features. Then the proposed Improved Feature Extraction Algorithm (IFEA) is applied to extract additionally ten different features from the ECG signal. The MIT-BIH arrhythmia database have been used to test the proposed approach. It is obvious from the results that the proposed approach shows a high classification in terms of the following four statistical measures: Accuracy (Ac) 98.37%, Recall 48.29%, Precision 43.91%, F Measure 45.31%, and Specificity (Sp) 93.30%, respectively. (C) 2018, Springer International Publishing AG.

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

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in intelligent systems and computing. Volume 565

ISBN

978-3-319-60833-4

ISSN

2194-5357

e-ISSN

neuvedeno

Počet stran výsledku

12

Strana od-do

299-310

Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Marrákeš

Datum konání akce

21. 11. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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