Advancements in ECG Heartbeat Classification: A Comprehensive Review of Deep Learning Approaches and Imbalanced Data Solutions
Abstract
This systematic literature review critically examines developments in electrocardiogram (ECG) heartbeat classification, focusing on the utilization of deep learning techniques and addressing challenges associated with imbalanced datasets. Covering articles published between 2012 and 2021, The primary objective is to uncover challenges related to imbalanced data in predicting heart diseases, specifically through the lens of machine learning applications utilizing ECG and patient data. The paper discusses the types of heart diseases, algorithms, applications, and solutions, shedding light on limitations and gaps in current approaches.
Keywords:
ECG Signal Processing, Convolutional Neural Network (CNN), AAMI Standard, MIT-BIH Dataset, INCART Dataset, Deep Learning, R-peak Detection, Electrocardiogram (ECG) Abnormalities, Machine Learning, Medical Signal Processing, RR Time Interval, Explainable AI
Published
Issue
Section
License
Copyright (c) 2023 International Journal on Emerging Research Areas
This work is licensed under a Creative Commons Attribution 4.0 International License.
All published work in this journal is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
How to Cite
Similar Articles
- Thomas Mathew Jose, Mathew Abraham, Sebastian Biju , Samuel Michael , Minu Cherian , Canine Dermal Analyser: Harnessing Artificial Intelligence and Deep Learning to Revolutionize Canine Skin Disease Detection , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Devika R Nilackal, Resmara S, Greeshma R, Griesh R, Joice P Abraham, Najma Najeeb, Shehanas K Salim, CARDAMOM PLANT DISEASE DETECTION USING ROBOT , International Journal on Emerging Research Areas: Vol. 3 No. 1 (2023): IJERA
- Sebastian Biju, Samuel Michael, Thomas Mathew Jose, Mathew Abraham, Minu Cherian, A Review of Machine Learning Approaches for Canine Skin Disease Detection Using Image Processing Techniques , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Jincy Lukose, Anita Ann Joseph, Meenakshy BR , Nevin Siby, Rosaine P Lal , ENHANCED PNEUMONIA DETECTION IN CHEST X-RAYS USING ATTENTION AND FNMS , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Nehala Noushad, Nikhitha Thomas, Reema Maria Suresh, Rehan T Raj , Resmipriya M G, AI-Based Analysis of Road Congestion Causes Using Real-Time Traffic Camera Data , International Journal on Emerging Research Areas: Vol. 5 No. 1 (2025): IJERA
- Asha Joseph, Deep Learning for Cyber Threat Detection , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Nikita Niteen , Juby Mathew, Securing AI: Understanding and Defending Against Adversarial Attacks in Deep Learning Systems , International Journal on Emerging Research Areas: Vol. 3 No. 2 (2023): IJERA
- Fabeela Ali Rawther, Abhinay A K, Anagha Tess B, Alan Joseph, Adham Saheer, Survey of Machine Learning and Deep Learning Approaches for Automated Hate Speech Detection and Sentiment Analysis in Multilingual Contexts , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
- Lis Jose , Achyuth P Murali, Christin Joseph Shaji, Christy Kunjumon Peter , Multiple Detection and Diagnosis of Skin Diseases using CNN , International Journal on Emerging Research Areas: Vol. 4 No. 1 (2024): IJERA
- Elisabeth Thomas, Arjun Saji, Aswin M S, Augustine Salas, Emil Viju, A Comprehensive Review of Advancing Cattle Monitoring and Behavior Classification using Deep Learning , International Journal on Emerging Research Areas: Vol. 4 No. 2 (2024): IJERA
You may also start an advanced similarity search for this article.