Classification of ECG signals for detection of arrhythmia and congestive heart failure based on continuous wavelet transform and deep neural networks

• Main Authors: Funke Olanrewaju, Rashidah, Ibrahim, Siti Noorjannah, Asnawi, Ani Liza, Altaf, Hunain
• Format: Article
• Language: English; English
• Published: Institute of Advanced Engineering and Science (IAES) 2021
• Subjects: TK5101 Telecommunication. Including telegraphy, radio, radar, television; TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
• 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
• Institution: Universiti Islam Antarabangsa Malaysia

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...