Cuffless, calibration-free hemodynamic monitoring with physics-informed machine learning models
Henry Crandall Tyler Schuessler Filip Bělík Albert Fabregas Barry M. Stults Alexandra Boyadzhiev Huanan Zhang Jim S. Wu Aylin R. Rodan Stephen P. Juraschek Ramakrishna Mukkamala Alfred K. Cheung Stavros G. Drakos Christel Hohenegger Braxton Osting Benjamin Sanchez
作者信息
Abstract
Wearable technologies have the potential to transform ambulatory and at-home hemodynamic monitoring by providing continuous assessments of cardiovascular health metrics and guiding clinical management. However, existing cuffless wearable devices for blood pressure (BP) monitoring often rely on methods lacking theoretical foundations, such as pulse wave analysis or pulse arrival time, making them vulnerable to physiological and experimental confounders that undermine their accuracy and clinical utility. Here, we developed a smartwatch device with real-time electrical bioimpedance (BioZ) sensing for cuffless hemodynamic monitoring. We elucidate the biophysical relationship between BioZ and BP via a multiscale analytical and computational modeling framework, and identify physiological, anatomical, and experimental parameters that influence the pulsatile BioZ signal at the wrist. A signal-tagged physics-informed neural network incorporating fluid dynamics principles enables calibration-free estimation of BP and radial and axial blood velocity. We successfully tested our approach with healthy individuals at rest and after physical activity including physical and autonomic challenges, and with patients with hypertension and cardiovascular disease in outpatient and intensive care settings. Our findings demonstrate the feasibility of BioZ technology for cuffless BP and blood velocity monitoring, addressing critical limitations of existing cuffless technologies.引用本文复制引用
Henry Crandall,Tyler Schuessler,Filip Bělík,Albert Fabregas,Barry M. Stults,Alexandra Boyadzhiev,Huanan Zhang,Jim S. Wu,Aylin R. Rodan,Stephen P. Juraschek,Ramakrishna Mukkamala,Alfred K. Cheung,Stavros G. Drakos,Christel Hohenegger,Braxton Osting,Benjamin Sanchez.Cuffless, calibration-free hemodynamic monitoring with physics-informed machine learning models[EB/OL].(2025-12-31)[2026-05-08].https://arxiv.org/abs/2601.00081.学科分类
基础医学/医学研究方法
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