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An efficient and automatic ECG arrhythmia diagnosis system using DWT and HOS features and entropy- based feature selection procedure Cover

An efficient and automatic ECG arrhythmia diagnosis system using DWT and HOS features and entropy- based feature selection procedure

Journal of Electrical Bioimpedance
Volume 10 (2019): Issue 1 (January 2019)
By: Abdullah Jafari Chashmi and  Mehdi Chehel Amirani  
Open Access
|Aug 2019
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DOI: https://doi.org/10.2478/joeb-2019-0007 | Journal eISSN: 1891-5469
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Language: English
Page range: 47 - 54
Submitted on: Feb 19, 2019
Published on: Aug 20, 2019
Published by: University of Oslo
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
ECG,
classification,
feature extraction,
feature selection,
entropy
Related subjects:
Engineering,
Bioengineering and biomedical engineering,
Biomedical electronics,
Life sciences,
Biophysics,
Medicine,
Biomedical engineering,
Physics,
Spectroscopy and metrology

© 2019 Abdullah Jafari Chashmi, Mehdi Chehel Amirani, published by University of Oslo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 10 (2019): Issue 1 (January 2019)
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