Congestive Heart Failure Detection Based on Electrocardiomatrix Method with ECG Signal - Rao, B. Mohan; Kumar, Aman (Computer Assisted Methods in Engineering and Science; Vol 30 No 3 (2023), 2023)
Congestive heart failure (CHF) is a prevalent, expensive to treat, and dangerous disease in which the pumping capacity of the heart muscle is reduced due to injury or stress. It causes major medical problems in humans and contribute to many diseases, thus increasing the mortality rate. In a world with a growing population, there is a need for more precise and simpler approaches to detect such conditions, which can prevent many diseases and lead to a lower mortality rate. The main goal here is to use electrocardiomatrix (ECM) approach to perform the task of detecting CHF. It is detected quickly and accurately with this approach, as ECM converts 2D electrocardiogram (ECG) data into a 3D-colored matrix. The approach is tested using ECG readings from the Beth Israel Deaconess Medical Center (BIDMC) CHF Database on the Internet (Physionet.org). The ECM outcomes of are then compared to manual readings of ECG data. The ECM results achieved the accuracy of 96.89%, the sensitivity of 97.53%, the precision of 99.1%, the F1-score of 97.76%, and the specificity of 96.02% for CHF. This research shows that the ECM approach is a good way for machines and practitioners to interpret long-term ECG readings while maintaining accuracy.