Unveiling Heart Arrhythmias: ECG Signal Analysis - Kadiyala, Nikhil Sarma; Seshagiri, Vyshnavi Lalitha; G, Pradeepini; Melam, Phani; Vupputuri, Sandeep Kumar (International Journal of Membrane Science and Technology, 2023)
Cardiac arrhythmias, disruptions in heart rhythm, carry substantial health risks including heart failure and sud- den cardiac death. Detecting these irregularities promptly is crucial for effective intervention. This abstract highlight the significance of arrhythmia detection, achieved through inter- disciplinary research combining medical technologies, signal processing, and machine learning. Innovative techniques employ- ing electrocardiogram data and wearable devices have yielded accurate detection models like convolutional and recurrent neural networks. These advancements enable real-time monitoring, early intervention, and improved diagnostic precision, underscoring their potential to revolutionize cardiovascular care and enhance patient outcomes. This abstract emphasizes the pivotal role of cardiac arrhythmia detection in safeguarding patient health and preventing life-threatening complications. The convergence of medical expertise, technological innovation, and machine learning advancements has yielded promising results in the realm of arrhythmia detection. These findings hold immense potential for revolutionizing cardiovascular care by offering more accurate, timely, and personalized interventions for patients at risk of cardiac arrhythmias.