Bracelet for early detection of heart attack: Innovations in wearable cardiac monitoring and artificial intelligence integration

Abstract

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, accounting for nearly 18 million deaths annually. Among them, heart attacks (myocardial infarctions, MIs) are the most prevalent and catastrophic, often resulting from undetected ischemic events or delayed clinical response. Early detection of cardiac distress is thus critical for reducing mortality and improving survival outcomes. Recent advances in wearable technology and artificial intelligence (AI) have enabled the creation of bracelet type monitoring devices capable of detecting physiological anomalies such as abnormal electrocardiogram (ECG) patterns, pulse irregularities, and blood oxygen fluctuations indicative of impending cardiac events. This review examines the global landscape of AI driven wearable bracelets for early heart attack detection, focusing on their technological architecture, biosensing mechanisms, and clinical validation. It discusses the pathophysiology of heart attacks, the functioning of the human heart, existing diagnostic modalities, and the evolution of smart wearable sensors designed for continuous cardiac surveillance. The integration of AI algorithms into wearable devices has transformed cardiac monitoring from reactive to proactive healthcare, potentially saving millions of lives through real time risk prediction and alert systems. The review concludes with an analysis of clinical implications, ethical considerations, and the future of AI assisted cardiac care.