Classification of ECG signals for detection of arrhythmia and congestive heart failure based on continuous wavelet transform and deep neural networks
ccording to World Health Organization (WHO) report an estimated 17.9 million lives are being lost each year due to cardiovascular diseases (CVDs) and is the top contributor to the death causes. 80% of the cardiovascular cases include heart attacks and strokes. This work is an effort to accurately pr...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Institute of Advanced Engineering and Science (IAES)
2021
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/98795/7/98795_Classification%20of%20ECG%20signals%20for%20detection%20of%20arrhythmia_SCOPUS.pdf http://irep.iium.edu.my/98795/8/98795_Classification%20of%20ECG%20signals%20for%20detection%20of%20arrhythmia.pdf http://irep.iium.edu.my/98795/ https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25236/15081 http://doi.org/10.11591/ijeecs.v22.i3.pp1520-1528 |
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http://irep.iium.edu.my/98795/7/98795_Classification%20of%20ECG%20signals%20for%20detection%20of%20arrhythmia_SCOPUS.pdfhttp://irep.iium.edu.my/98795/8/98795_Classification%20of%20ECG%20signals%20for%20detection%20of%20arrhythmia.pdf
http://irep.iium.edu.my/98795/
https://ijeecs.iaescore.com/index.php/IJEECS/article/view/25236/15081
http://doi.org/10.11591/ijeecs.v22.i3.pp1520-1528