Cuffless, calibration-free hemodynamic monitoring with physics-informed machine learning models

TL;DR

This paper introduces a physics-informed machine learning approach using bioimpedance signals from a smartwatch for cuffless, calibration-free blood pressure and blood velocity monitoring, validated in diverse clinical settings.

Contribution

It develops a novel BioZ-based method with a physics-informed neural network for accurate, calibration-free hemodynamic monitoring, overcoming limitations of existing cuffless devices.

Findings

Successful BP and blood velocity estimation in healthy and patient populations

Demonstrated robustness across rest, activity, and clinical conditions

Addressed key limitations of prior cuffless monitoring technologies

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.