A two-stage feature extraction approach for ECG signals
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
A two-stage feature extraction approach for ECG signals
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in intelligent systems and computing. Volume 565
ISBN
978-3-319-60833-4
ISSN
2194-5357
e-ISSN
neuvedeno
Number of pages
12
Pages from-to
299-310
Publisher name
Springer
Place of publication
Berlin
Event location
Marrákeš
Event date
Nov 21, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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