Title: Detecting heart ailments by investigating ECG with neural networks

Authors: B. Prabadevi; N. Deepa; L.B. Krithika; Ravi Raj Gulati; R. Sivakumar

Addresses: School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India ' School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India ' School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India ' School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India ' School of Electronics Engineering, Vellore Institute of Technology, Vellore, India

Abstract: Heart ailments or cardiovascular diseases (CVD) are the diseases that incorporate the blood vessels or heart, which is common among various age groups. Though numerous techniques have been used to classify heart abnormalities, such as classification and regression trees (CART), they are less accurate. Therefore, a technique for early detection of heart ailments with more accuracy is mandatory. A model has been designed and proposed to detect the heart ailments using three-layered neural networks for better accuracy. Electrocardiogram (ECG or EKG) is used to identify arrhythmia (irregular heartbeat) accurately, and the UC Irvine (UCI) arrhythmia dataset of ECG reports are used to implement a classification for different types of heart abnormalities.

Keywords: cardiovascular disease; CVD; electrocardiogram; networks; arrhythmia; classification.

DOI: 10.1504/IJMEI.2022.125314

International Journal of Medical Engineering and Informatics, 2022 Vol.14 No.5, pp.414 - 423

Received: 30 May 2020
Accepted: 23 Nov 2020
Published online: 07 Sep 2022 *

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