A Review of Shockable Arrhythmia Detection of ECG Signals Using Machine and Deep Learning Techniques
By:
Authors
Lakkakula Kavya
School of Electronics Engineering (SENSE), Vellore Institute of Technology, Vellore, India
Yepuganti Karuna
School of Electronics Engineering, VIT-AP University, Inavolu, Amaravati, India
Saladi Saritha
School of Electronics Engineering, VIT-AP University, Inavolu, Amaravati, India
Allam Jaya Prakash
School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology, Vellore, India
Kiran Kumar Patro
Department of Electronics and Communication Engineering, Aditya Institute of Technology and Management, Tekkali, India
Suraj Prakash Sahoo
School of Electronics Engineering (SENSE), Vellore Institute of Technology, Vellore, India
Ryszard Tadeusiewicz
Department of Biocybernetics and Biomedical Engineering, AGH University of Krakow, Kraków, Poland
Paweł Pławiak
Department of Computer Science, Cracow University of Technology, Kraków, Poland
Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Gliwice, Poland
Language: English
Page range: 485 - 511
Submitted on: Dec 11, 2023
Accepted on: May 29, 2024
Published on: Oct 1, 2024
Published by: Sciendo
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year
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© 2024 Lakkakula Kavya, Yepuganti Karuna, Saladi Saritha, Allam Jaya Prakash, Kiran Kumar Patro, Suraj Prakash Sahoo, Ryszard Tadeusiewicz, Paweł Pławiak, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.