Artificial Intelligence-Driven Wearable Sensors for Cardiovascular Health Monitoring

Wearable sensing technologies hold great promise for continuous and non-invasive monitoring of cardiovascular health, offering new avenues for early detection and effective management of cardiovascular diseases. Despite these advances, several critical challenges remain, including inefficiencies in sensor design, the degradation of calibration model accuracy over time, and difficulties in processing complex physiological signals under real-world conditions. The integration of artificial intelligence (AI) into wearable cardiovascular monitoring systems presents transformative solutions to these limitations by improving system performance, adaptability, and clinical applicability. In this review, we provide an overview of current wearable technologies for cardiovascular monitoring, including their mechanisms, characteristics, and limitations. An in-depth discussion is subsequently presented on AI-driven wearable cardiovascular monitoring, encompassing five critical facets: sensor design, sensor calibration, signal processing, pattern recognition, and disease management. Furthermore, we analyze the challenges associated with the widespread use of AI-based wearable systems and provide insights into potential strategies for addressing these challenges. This review is expected to serve as a roadmap for future research and development in the rapidly evolving field of intelligent cardiovascular health monitoring.