Smart Cardiac Monitoring System Using AI and Wearable Technology

Abstract

Cardiovascular diseases remain one of the world's top causes of death, making early identification and continuous monitoring essential for effective healthcare treatment. Conventional cardiac monitoring technologies are mostly limited to hospital settings and short-term diagnostic procedures, which restrict continuous patient health monitoring. Although physiological indicators such as heart rate and electrocardiogram (ECG) signals can be remotely monitored with wearable technology, many existing systems are focused solely on data collection and lack the ability to perform intelligent analysis and prediction. This work proposes a Smart Cardiac Monitoring System that integrates wearable biosensors with machine learning algorithms to enable continuous cardiac monitoring and early identification of cardiovascular diseases. The system collects physiological data via wearable sensors, preprocesses the information, and evaluates heart rhythms using AI-based algorithms to detect potential health risks. When abnormal situations are discovered, the system generates automatic alerts for patients and medical professionals. The proposed strategy aims to enhance remote healthcare monitoring and enable early identification of cardiovascular disease.