Automatic Detection of Cardiovascular Abnormalities in ECG Images: CNN and MobileNet

Aditi Jambotkar, Regina Fernandes, Shreya Arun Miskin, Prema T. Akkasaligar, Rajashri Khanai

2025

Abstract

Cardiovascular diseases are becoming a leading cause of death worldwide. Detection of irregular heart activities like arrhythmia and heart attacks are critical for timely treatment. Automation in detecting cardiovascular abnormalities is essential for providing timely diagnosis, especially in resource-limited settings where trained medical professionals may be scarce. The paper aims to detect cardiovascular abnormality in ECG images automatically using deep learning techniques. It uses a Convolutional Neural Network(CNN) and MobileNet for efficient and lightweight processing. The MobileNet model outperforms the CNN model, demonstrating superior accuracy, precision and recall. The results show the potential of deep learning models in enhancing the accuracy and automation of cardiovascular abnormality detection through ECG analysis. By automating ECG interpretation, it enables early detection of abnormalities, reduces diagnostic delays, and improves patient care, particularly in resource-constrained settings.

Paper Citation

in Harvard Style

Jambotkar A., Fernandes R., Miskin S., Akkasaligar P. and Khanai R. (2025). Automatic Detection of Cardiovascular Abnormalities in ECG Images: CNN and MobileNet. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 754-761. DOI: 10.5220/0013601600004664

in Bibtex Style

@conference{incoft25,
author={Aditi Jambotkar and Regina Fernandes and Shreya Miskin and Prema T. Akkasaligar and Rajashri Khanai},
title={Automatic Detection of Cardiovascular Abnormalities in ECG Images: CNN and MobileNet},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={754-761},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013601600004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Automatic Detection of Cardiovascular Abnormalities in ECG Images: CNN and MobileNet
SN - 978-989-758-763-4
AU - Jambotkar A.
AU - Fernandes R.
AU - Miskin S.
AU - Akkasaligar P.
AU - Khanai R.
PY - 2025
SP - 754
EP - 761
DO - 10.5220/0013601600004664
PB - SciTePress