Wearable Smartwatch Offers Continuous, Cuffless Blood Pressure Monitoring

A new study shows how a smartwatch can track blood pressure and blood flow continuously—without the need for an inflatable cuff.

"Blood pressure isn't two numbers; it's a function of time."
— Braxton Osting, Professor of Mathematics, University of Utah

The Breakthrough

Published in Nature Communications, the study introduces a wearable smartwatch that measures blood pressure and blood flow continuously. Unlike standard monitors that provide only occasional "snapshots" (systolic and diastolic values), this technology aims to capture the full waveform of blood pressure over time—what researchers describe as a "movie" instead of a single image.

The device uses bioimpedance, a measure of how easily an imperceptible electrical current flows through blood and tissue at the wrist. This allows for continuous monitoring without the discomfort or inconvenience of a traditional cuff.

How It Works

The system embeds core physics principles—specifically fluid dynamics and electromagnetism—directly into its machine learning models. This hybrid approach improves both accuracy and interpretability, making the device more reliable than purely data-driven methods.

"This work shows how combining machine learning with physics can fundamentally change what's possible."
— Christel Hohenegger, Associate Professor of Mathematics, University of Utah

Testing and Validation

The study tested the smartwatch on 150 individuals, including patients in intensive care units and those in outpatient settings. This broad testing helps validate the device's performance across real-world medical environments.

A Silent Killer

Elevated blood pressure is considered the silent killer—a global healthcare burden and a 'Holy Grail' problem in medicine, said Benjamín Sánchez Terrones, associate professor at the University of Illinois, Chicago, who led the research.

Sánchez Terrones (formerly at the University of Utah, now at the University of Illinois, Chicago) worked with a team of mathematicians and engineers from both institutions.

Next Steps

The University of Utah holds the intellectual property for this technology and is currently exploring licensing opportunities.

Funding Support

The research was made possible through grants from:

• University of Utah (seed grant)
• B-Secur, Ltd
• National Science Foundation
• National Institutes of Health