The prevalence of sleep disorders, like sleep apnea, is on the rise within the U.S., but current protocols to conduct clinically accepted assessments are expensive and inconvenient.

Georgia Tech researchers have created a wearable device to accurately measure obstructive sleep apnea -; when the body repeatedly stops and restarts respiration for a period -; in addition to the standard of sleep people get once they are at rest.

Under conventional methods, people who find themselves suspected of getting some sleep issue or disorder must go to a medical facility, where they’re monitored overnight and tethered to a series of wired probes that record brain, eye, and muscle activity.

The wearable sleep monitor patch developed by a team of researchers and clinicians, led by W. Hong Yeo, an associate professor and Woodruff Faculty Fellow in Georgia Tech’s George W. Woodruff School of Mechanical Engineering, is made from silicone and matches over the brow, with a second, smaller silicone attachment that molds to the chin.

Plenty of people have this disorder, but they do not understand it because it is very hard to diagnose immediately. Current smartphone apps don’t capture the precise data doctors and clinicians study to find out if a patient has apnea, rendering them useless.”

W. Hong Yeo, Associate Professor and Woodruff Faculty Fellow in Georgia Tech’s George W. Woodruff School of Mechanical Engineering

Conventional existing sleep testing is going on in sleep labs due to device limitations. This at-home wearable device might be the choice to the costlier medical procedures at sleep labs.

Yeo and his team, which included researchers from across Georgia Tech, Emory University School of Medicine, the University of Texas at Austin, the Icahn School of Medicine at Mount Sinai in Recent York, the Korea Institute of Materials Science, and the Korea Advanced Institute of Science and Technology, reported their findings in Science Advances in May.

Rising prevalence

While there are two additional sorts of sleep apnea -; central and complicated -; obstructive sleep apnea is essentially the most common, Yeo said, explaining that along with snoring and arrested respiration episodes, it’s generally characterised by waking up suddenly, gasping for air or choking, and hypertension.

Lack of quality sleep can exacerbate other health issues in individuals with existing illnesses reminiscent of heart disease or diabetes, Yeo said. But even those that haven’t got other health ailments can have serious complications from sleep apnea since the longer it goes undetected and untreated, the more it should affect their hearts and brains over time.

Seeing the toll sleep apnea was taking over the U.S. population, Yeo got down to apply his wearable device research to the industry with a wireless sleep monitoring patch system.

The patches -; which have an accuracy rate of 88.5% for sleep apnea detection -; have the thickness of an adhesive bandage. Three embedded electronic sensors send signals wirelessly via Bluetooth to record brain, eye, and muscle activity. That data is relayed to an app on a wise device reminiscent of a phone or tablet for further study and evaluation.

The device could be used at home, negating the necessity to go to a sleep center or medical facility for overnight monitoring.

“Plenty of people have this kind of sleep problem; they only don’t understand it,” said Yeo, whose research is centered primarily in advancing healthcare through the event of biosensors and bioelectronics. “Within the U.S., greater than 18 million people have this kind of sleep apnea. That is principally one out of each 15 Americans, and people numbers are increasing over time.”

Underlying health issues are partly behind the rise, he said, but key drivers are the sorts of food and portion sizes of the trendy American weight loss program in addition to stress.

There’s also an economic toll on the country. Poor sleep cost the U.S. economy $411 billion in lost productivity in 2015. That figure is projected to exceed $467 billion by 2030.

Predicting sleep apnea

Using artificial intelligence and machine learning, the technology behind the wearable device records the information to provide a sleep rating that determines if the patient has sleep apnea or in the event that they are getting enough quality sleep.

Within the study, when measured against a controlled group of eight sleep apnea patients whose issues were detected under conventional testing means, Yeo’s wireless patch detected sleep apnea with an accuracy rate of 88.5%. For comparison, an existing headband device available on the market had an accuracy rate of about 71% and can’t measure muscle activities.

What’s more, the technology Yeo and his team developed, and the machine learning algorithms used, can predict the likelihood that a one that doesn’t show any symptoms of sleep apnea will develop it sooner or later.

“By the information, we will say that, in the event you don’t change something immediately -; whether it’s weight loss program or sleeping behavior or anything like that -; you are prone to develop sleep apnea because your numbers are bad,” he said.

Solving an issue

The wireless patch solves a multipronged challenge to standard testing methodology by addressing current patient issues with comfort, time, access, and price.

The present process -; called a PSG or polysomnography test -; proves uncomfortable for some patients. That is because they need to sleep in a set position for fear of detaching any one in every of the 15 wired probes from their skin. Having any of those sensors detach from their bodies risks not capturing enough data for correct assessments.

It is also time consuming since the patient must go to a sleep center and spend the night being monitored by medical personnel. There can be a lag to even get tested. Patients who haven’t got severe symptoms or other high-risk, underlying aspects reminiscent of heart disease or hypertension, often must wait after getting a referral from a health care provider to be slotted for a bed at a sleep center, pending availability. Finally, the present detection method is dear to patients and insurance systems, tallying roughly $8,000 per person, per night.

“In order that testing barrier is actually high for normal people unless you’re already sick, then they are going to screen you to avoid any severe conditions,” Yeo said. “But for individuals who don’t show symptoms, you will not know whether you might have the sleep problem until it gets severe. We wish to stop sleep apnea before it starts.”

Source:

Georgia Institute of Technology

Journal reference:

Kwon, S., et al. (2023) At-home wireless sleep monitoring patches for the clinical assessment of sleep quality and sleep apnea. Science Advances. doi.org/10.1126/sciadv.adg9671.