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  A Comparative Approach to ECG Feature Extraction Methods

Molaei-Vaneghi, F., Oladazimi, M., Shiman, F., Kordi, A., Safari, M., & Ibrahim, F. (2012). A Comparative Approach to ECG Feature Extraction Methods. In 2012 Third International Conference on Intelligent Systems Modelling and Simulation (pp. 252-256). Piscataway, NJ, USA: IEEE.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-8F60-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0001-8F61-1
Genre: Conference Paper

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 Creators:
Molaei-Vaneghi, F1, Author              
Oladazimi, M, Author
Shiman, F, Author
Kordi, A, Author
Safari, MJ, Author
Ibrahim, F, Author
Affiliations:
1Department of Biomedical Engineering, Faculty of Engineering University Malaya, Kuala Lumpur, ou_persistent22              

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 Abstract: This paper discusses six most frequent methods used to extract different features in Electrocardiograph (ECG) signals namely Autoregressive (AR), Wavelet Transform (WT), Eigenvector, Fast Fourier Transform (FFT), Linear Prediction (LP), and Independent Component Analysis (ICA). The study reveals that Eigenvector method gives better performance in frequency domain for the ECG feature extraction.

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 Dates: 2012-02
 Publication Status: Published in print
 Pages: -
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 Rev. Method: -
 Identifiers: DOI: 10.1109/ISMS.2012.35
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Title: Third International Conference on Intelligent Systems, Modelling and Simulation (ISMS 2012)
Place of Event: Kota Kinabalu, Malaysia
Start-/End Date: 2012-02-08 - 2012-02-10

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Title: 2012 Third International Conference on Intelligent Systems Modelling and Simulation
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 252 - 256 Identifier: ISBN: 978-0-7695-4668-1