Reviewed by Lexie CornerMar 6 2025
A team of researchers from KAIST, led by Professor Keon Jae Lee, has developed a new theoretical framework and research strategies for AI-powered wearable blood pressure sensors. This advancement enhances continuous, non-invasive cardiovascular monitoring. Their study was published in Nature Reviews Cardiology.
Overview of wearable blood pressure sensor technologies for cardiovascular health care. Image Credit: Korea Advanced Institute of Science and Technology.
Hypertension, a chronic condition affecting over a billion people worldwide, is a major risk factor for serious cardiovascular diseases like strokes, heart attacks, and heart failure. Traditional blood pressure measurement methods, which rely on intermittent, cuff-based devices, are unable to capture real-time fluctuations and are not suitable for continuous monitoring.
Wearable blood pressure sensors offer a non-invasive, continuous monitoring solution, enabling real-time tracking and personalized management of cardiovascular health. However, existing technologies lack the accuracy and reliability needed for medical applications, limiting their practical use. To address these challenges, advancements in high-sensitivity sensor technology and AI-driven signal processing are essential.
Building on their previous study published in Advanced Materials (doi.org/10.1002/adma.202301627), which demonstrated the clinical feasibility of flexible piezoelectric blood pressure sensors, Professor Lee's team conducted a comprehensive review of the latest developments in cuffless wearable sensors. Their analysis covers key technical and clinical challenges, such as real-time data transmission, signal quality degradation, AI algorithm accuracy, and effective clinical implementation.
This paper systematically demonstrates the feasibility of medical-grade wearable blood pressure sensors, overcoming what was previously considered an insurmountable challenge. We propose theoretical strategies to address technical barriers, opening new possibilities for future innovations in this field. With continued advancements, we expect these sensors to gain trust and be commercialized soon, significantly improving quality of life.
Keon Jae Lee, Professor, Korea Advanced Institute of Science and Technology
Journal Reference:
Min, S., et al. (2025). Wearable blood pressure sensors for cardiovascular monitoring and machine learning algorithms for blood pressure estimation. Nature Reviews Cardiology. doi.org/10.1038/s41569-025-01127-0.