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The device — introduced by a project published in the scientific journal — is a “soft mesh sleeve worn around the lower thigh that monitors and analyzes leg acceleration, symmetry and step variability,� according to a UA news release.

“The current model of care is lagging behind,� said Philipp Gutruf, an associate department head of  at the UA and senior author on the study with the . “Right now, we often wait for a fall or hospitalization before we assess a patient for frailty. We wanted to shift the paradigm from reactive to preventative.�

A 2015 study in The said “frailty� is a sign of greater susceptibility to falls, disabilities and hospitalizations, and affects 15% of U.S. residents aged 65 or older.

Gutruf, who has spent the last seven years at the university developing a technology that monitors biomarkers, said this device will allow medical practitioners to intervene early and potentially prevent costly and dangerous outcomes. Last year, Gutruf’s lab published a study on an “adhesive-free wearable� that measures water vapor and skin gases to track signs of stress.

The approximately two-inch-wide, 3D-printed leg sleeve lined with tiny sensors is “designed to be invisible,� Gutruf said. The sleeve simultaneously records and analyzes the wearer's motion and produces an AI analysis, then sends just the results and not all the collected data through Bluetooth.

Long-range wireless charging capabilities mean the user doesn’t need to keep plugging in the device or changing the battery, the news release said.

“Continuous, high-fidelity monitoring creates massive datasets that would normally drain a battery in hours and require a heavy internet connection to upload. We solved this with Edge AI,� said Kevin Kasper, lead study author and a biomedical engineering doctoral candidate.

The AI-enabled technology is “an ideal solution for remote patient monitoring in rural or under-resourced communities,� he said. “We are effectively putting a lab on the patient, no matter where they live.�