Wearable sensors and AI could monitor blood pressure in ICU
Wearable sensors coupled with AI can generate blood pressure readings nearly as accurately as the invasive and risky arterial lines relied on in intensive care units and operating rooms, new work by Johns Hopkins University researchers demonstrates.
Researchers at Johns Hopkins University have developed a wearable sensor system that can generate blood pressure readings with near-invasive accuracy, potentially revolutionizing monitoring in intensive care units and beyond. The system, called MOSAIC, consists of two sensors—one placed on the chest and another on the finger—that track the heart's electrical activity and blood flow.
A deep learning model then reconstructs these signals into a continuous waveform of blood pressure over time. Initial tests on 28 ICU patients showed the MOSAIC system produced waveforms nearly identical to those from traditional arterial catheters, suggesting it could reduce risks such as bleeding, clotting, and infection associated with invasive monitoring.
The technology could enable continuous blood pressure tracking for hypertensive patients, monitor healthy individuals' daily fluctuations, and provide insights into blood pressure patterns in everyday life. Validation in larger patient groups is ongoing before wider clinical or home use.
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