The thought of spending the night in a sleep clinic with several electrodes affixed to their skin can’t be appealing to anyone. For this reason, researchers have created a smart pajama top that can detect sleep issues while its user sleeps soundly at home.

A procedure called polysomnography is the gold standard for diagnosing sleep issues. The patient is usually linked up with electrodes that track bodily processes like muscle activity, heart rate, eye movements, and brain activity as they sleep through the night on a bed in a lab.

Now, University of Cambridge professor Luigi Occhipinti and colleagues have developed comfortable, washable "smart pajamas" that can monitor sleep disorders such as sleep apnea at home, without the need for sticky patches, cumbersome equipment or a visit to a specialist sleep clinic. The smart pajamas utilize fabric sensors that can monitor breathing by detecting tiny movements in the skin, even when the pajamas are worn loosely around the neck and chest, reports NewAtlas.

That data is wirelessly transmitted to a nearby device such as a smartphone, where it's processed by the machine-learning-based SleepNet program.

The program can then distinguish between six types of sleep patterns: central sleep apnea, obstructive sleep apnea, snoring, teeth grinding, nasal breathing, and mouth breathing. SleepNet demonstrated 98.6% accuracy in identifying the various sleep phases when it processed pajama-top data collected from two individuals with sleep apnea and seven healthy subjects.

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Importantly, wearers' frequent tossing and turning movements during the night do not interfere with the system. Furthermore, its collar is not uncomfortable because it fits around the neck somewhat loosely.

"Sleep is so important to health, and reliable sleep monitoring can be key in preventative care," says Occhipinti. "Since this garment can be used at home, rather than in a hospital or clinic, it can alert users to changes in their sleep that they can then discuss with their doctor."

A paper on the research, which also involved scientists from Capital Medical University (Beijing) and Beihang University, was recently published in the journal PNAS.