Georgia Researchers Develop Wearable Device to Detect Sleep Apnea

As reported in Science Advances, researchers from the Georgia Institute of Technology (Georgia Tech) developed a wearable device that attaches to the forehead and chin to accurately detect obstructive sleep apnea.

Sleep apnea is a common medical condition among Americans, many of whom are unaware they may have it. According to the American Academy of Sleep Medicine (AASM), a study known as the National Healthy Sleep Awareness Project indicated that at least 25 million adults in the US were experiencing sleep apnea in 2014. AASM also noted that the prevalence of this condition led to compromises on public health and safety.  

“A lot of people have this type of sleep disorder; they just don’t know it,” said W. Hong Yeo, PhD, an associate professor and Woodruff Faculty Fellow in Georgia Tech’s George W. Woodruff School of Mechanical Engineering, in a press release. “In the U.S., more than 18 million people have this type of sleep apnea. That’s basically one out of every 15 Americans, and those numbers are increasing over time.”

Known as a polysomnography test (PSG), the current sleep apnea testing method has various flaws. These include low patient comfort levels, high time consumption, limited accessibility, and high costs.

Thus, Yeo and a team of researchers and clinicians aimed to determine the efficacy of wearable devices in detecting sleep apnea. Instead of requiring patients to visit a sleep care facility and remain there overnight while engaging with various wired probes, this wearable consists of two sensors: one on the forehead and the other on the chin.

The former measures electroencephalograms (EEGs) and electrooculograms (EOGs), and the latter measures electromyograms (EMGs). Both sensors are silicone, have a thickness comparable to an adhesive bandage, and use Bluetooth to transmit signals recording brain, eye, and muscle activity.

This device also uses artificial intelligence and machine learning to determine a sleep score based on data gathered by the wearable. This score indicates potential sleep apnea or whether a patient is getting enough good-quality sleep.

The research team tested the device in a study. They compared the use of the wearable device among eight patients to controls who underwent traditional sleep apnea testing. They found that the device had an accuracy rate of 88.52 percent.

Researchers also noted that this technology could predict sleep apnea among those without symptoms. This benefit is not typically associated with PSG tests, which often result in delays prior to testing because those without symptoms must wait for a bed at a sleep center following a referral from a doctor.

“So that testing barrier is really high for regular people unless you are already sick, then they will screen you to avoid any severe conditions,” said Yeo. “But for people who don’t show symptoms, you won’t know whether you have the sleep disorder until it gets severe. We want to stop sleep apnea before it starts.”

Prior research has described efforts that leverage technology to treat sleep apnea.

In December 2022, researchers from the University of Chicago Medicine and Northwestern University created an mHealth tool to track sleep apnea treatment. Considering patient needs, the use of continuous positive airway pressure (CPAP) machines, and risk behaviors, the application aims to help patients achieve progress in their subjective treatment plans.

Although CPAP machines can assist patients in maintaining open airways during sleep, many patients do not use them consistently. The app tracks a new adherence metric, however, the share of time that a patient uses the CPAP. Tracking this metric could assist in developing customized treatments.