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DOI 10.1038/s41569-025-01127-0

Медицинская библиотека · Nature reviews. Cardiology · 2025

Wearable blood pressure sensors for cardiovascular monitoring and machine learning algorithms for blood pressure estimation.

Min Seongwook, An Jaehun, Lee Jae Hee, Kim Ji Hoon, Joe Daniel J, Eom Soo Hwan, Yoo Chang D, Ahn Hyo-Suk, Hwang Jin-Young, Xu Sheng, Rogers John A, Lee Keon Jae

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With advances in materials science and medical technology, wearable sensors have become crucial tools for the early diagnosis and continuous monitoring of numerous cardiovascular diseases, including arrhythmias, hypertension and coronary artery disease. These devices employ various sensing mechanisms, such as mechanoelectric, optoelectronic, ultrasonic and electrophysiological methods, to measure vital biosignals, including pulse rate, blood pressure and changes in heart rhythm. In this Review, we provide a comprehensive overview of the current state of wearable cardiovascular sensors, focusing particularly on those that measure blood pressure. We explore biosignal sensing principles, discuss blood pressure estimation methods (including machine learning algorithms) and summarize the latest advances in cuffless wearable blood pressure sensors. Finally, we highlight the challenges of and offer insights into potential pathways for the practical application of cuffless wearable blood pressure sensors in the medical field from both technical and clinical perspectives.

Для цитирования: Min Seongwook, An Jaehun, Lee Jae Hee, Kim Ji Hoon, Joe Daniel J, Eom Soo Hwan, Yoo Chang D, Ahn Hyo-Suk, Hwang Jin-Young, Xu Sheng, Rogers John A, Lee Keon Jae. Wearable blood pressure sensors for cardiovascular monitoring and machine learning algorithms for blood pressure estimation.. Nature reviews. Cardiology. 2025. DOI: 10.1038/s41569-025-01127-0.

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