Wearable tech detects subtle signs of frailty in older adults

Researchers have developed a wearable device that uses artificial intelligence to detect subtle warning signs of frailty in older adults.
The device, which resembles a soft mesh sleeve worn around the lower thigh, monitors and analyzes leg acceleration, symmetry, and step variability to identify potential health risks.
Frailty affects 15% of US residents aged 65 and older, leading to costly and dangerous outcomes such as falls, disabilities, and hospitalization.
The wearable device allows clinicians to intervene early, potentially preventing these outcomes by sending only the results of the analysis via Bluetooth to a smart device.
The technology is ideal for remote patient monitoring in rural or under-resourced communities, where access to healthcare can be limited, and provides a more proactive approach to elderly care.

An older woman and man sit next to each other on a couch.

Researchers have developed a comfortable, easy-to-use wearable device that incorporates artificial intelligence to detect subtle warning signs of frailty, signifying a leap forward in elderly care.

“The current model of care is lagging behind,” says Philipp Gutruf, associate department head of biomedical engineering at the University of Arizona and senior author on the study.

“We are effectively putting a lab on the patient, no matter where they live.”

“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.”

The project study in Nature Communications introduces a soft mesh sleeve worn around the lower thigh that monitors and analyzes leg acceleration, symmetry, and step variability.

Frailty, which indicates greater susceptibility to falls, disabilities, and hospitalization, affects 15% of US residents 65 and older, according to a 2015 study in the Journals of Gerontology.

“This device allows clinicians to intervene early, potentially preventing costly and dangerous outcomes,” says Gutruf.

The associate professor has spent the last seven years developing technology that monitors biomarkers. His lab published a study in May on an adhesive-free wearable that measures water vapor and skin gases to track signs of stress.

Adapting and expanding on that technology, the approximately two-inch-wide, 3D-printed sleeve lined with tiny sensors is “designed to be invisible,” says Gutruf.

The sleeve simultaneously records and analyzes motion of the wearer and produces an AI analysis. With the device sending just the results, not the actual hundreds of hours of recorded data, transmission is reduced by 99% and the need for high-speed internet is eliminated. Results are transferred via Bluetooth to a smart device. And long-range wireless charging capabilities free the user from plugging in the device or swapping out a battery.

“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,” says Kevin Kasper, lead study author and biomedical engineering doctoral candidate.

The AI-enabled technology is “an ideal solution for remote patient monitoring in rural or under-resourced communities,” he adds.

“We are effectively putting a lab on the patient, no matter where they live.”

Source: University of Arizona

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Q. What is the current model of care for frailty in older adults?

A. The current model of care often waits for a fall or hospitalization before assessing a patient for frailty, which can be too late to prevent costly and dangerous outcomes.

Q. How does the new wearable device detect subtle signs of frailty?

A. The device uses artificial intelligence to analyze leg acceleration, symmetry, and step variability, allowing clinicians to intervene early and potentially prevent frailty-related outcomes.

Q. What percentage of US residents 65 and older are affected by frailty?

A. According to a 2015 study, 15% of US residents 65 and older are affected by frailty.

Q. How does the wearable device work?

A. The device is a soft mesh sleeve worn around the lower thigh that monitors and analyzes leg acceleration, symmetry, and step variability, producing an AI analysis that sends results to a smart device via Bluetooth.

Q. What technology was used to develop the wearable device?

A. The device uses Edge AI, which reduces transmission of recorded data by 99% and eliminates the need for high-speed internet.

Q. Why is the wearable device ideal for remote patient monitoring?

A. The device’s long-range wireless charging capabilities and reduced internet requirements make it an ideal solution for rural or under-resourced communities where access to healthcare resources may be limited.

Q. Who developed the wearable device?

A. Researchers at the University of Arizona, led by associate department head Philipp Gutruf and biomedical engineering doctoral candidate Kevin Kasper.

Q. What is the potential benefit of using this technology in elderly care?

A. The technology allows clinicians to intervene early, potentially preventing costly and dangerous outcomes associated with frailty.

Q. How does the device’s design contribute to its effectiveness?

A. The device is designed to be invisible, allowing it to be worn comfortably without restricting movement or causing discomfort.

Q. What was the inspiration behind developing this wearable device?

A. The researchers aimed to shift the paradigm from reactive to preventative care, recognizing that frailty often goes undetected until a fall or hospitalization occurs.