Scientists Develop ‘Smart Pajamas’ to Monitor Sleep Disorders

University of Cambridge, Cambridge, UK

Comfortable, washable smart pajamas 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. (Credit: University of Cambridge)

Researchers 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 team, led by the University of Cambridge, developed printed 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.

The sensors embedded in the smart pajamas were trained using a lightweight AI algorithm and can identify six different sleep states with 98.6 percent accuracy, while ignoring regular sleep movements such as tossing and turning. The energy-efficient sensors only require a handful of examples of sleep patterns to successfully identify the difference between regular and disordered sleep.

The researchers say that their smart pajamas could be useful for the millions of people in the UK who struggle with disordered sleep to monitor their sleep, and how it might be affected by lifestyle changes. The results are reported in the Proceedings of the National Academy of Sciences (PNAS).¹

Sleep is vital for human health, yet more than 60 percent of adults experience poor sleep quality, leading to the loss of between 44 and 54 annual working days, and an estimated one percent reduction in global GDP. Sleep behaviors such as mouth breathing, sleep apnea, and snoring are major contributors to poor sleep quality, and can lead to chronic conditions such as cardiovascular disease, diabetes, and depression.

“Poor sleep has huge effects on our physical and mental health, which is why proper sleep monitoring is vital,” says Prof. Luigi Occhipinti from the Cambridge Graphene Centre, who led the research. “However, the current gold standard for sleep monitoring — polysomnography or PSG — is expensive, complicated, and isn’t suitable for longterm use at home.”

Home devices that are simpler than PSG, such as home sleep tests, typically focus on a single condition and are bulky or uncomfortable. Wearable devices such as smartwatches, while more comfortable to wear, can only infer sleep quality, and are not effective for accurately monitoring disordered sleep.

“We need something that is comfortable and easy to use every night but is accurate enough to provide meaningful information about sleep quality,” says Occhipinti.

To develop the smart pajamas, Occhipinti and his colleagues built on their earlier work on a smart choker for people with speech impairments. The team redesigned the graphene-based sensors for breath analysis during sleep and made several design improvements to increase sensitivity.

“Thanks to the design changes we made, the sensors are able to detect different sleep states, while ignoring regular tossing and turning,” says Occhinpinti. “The improved sensitivity also means that the smart garment does not need to be worn tightly around the neck, which many people would find uncomfortable. As long as the sensors are in contact with the skin, they provide highly accurate readings.”

The researchers designed a machine learning model, called SleepNet, that uses the signals captured by the sensors to identify sleep states including nasal breathing, mouth breathing, snoring, teeth grinding, central sleep apnea (CSA), and obstructive sleep apnea (OSA). SleepNet is a lightweight AI network that reduces computational complexity to the point where it can be run on portable devices, without the need to connect to computers or servers.

“We pruned the AI model to the point where we could get the lowest computational cost with the highest degree of accuracy,” says Occhinpinti. “This way we are able to embed the main data processors in the sensors directly.”

The smart pajamas were tested on healthy patients and those with sleep apnea, and were able to detect a range of sleep states with an accuracy of 98.6 percent. By treating the smart pajamas with a special starching step, they were able to improve the durability of the sensors so they can be run through a regular washing machine.

The most recent version of the smart pajamas is also capable of wireless data transfer, meaning the sleep data can be securely transferred to a smartphone or computer.

“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. Sleep behaviors such as nasal versus mouth breathing are not typically picked up in an NHS sleep analysis, but it can be an indicator of disordered sleep.”

The researchers are hoping to adapt the sensors for a range of health conditions or home uses, such as baby monitoring, and have been in discussions with different patient groups. They are also working to improve the durability of the sensors for long-term use.

The research was supported in part by the EU Graphene Flagship, Haleon, and the Engineering and Physical Sciences Research Council (EPSRC), part of UK Research and Innovation (UKRI).

Reference

Chenyu Tang, Wentian Yi, et al., “A deep learning-enabled smart garment for accurate and versatile monitoring of sleep conditions in daily life,” PNAS (2025), DOI: 10.1073/pnas.2420498122.

For more information, contact Prof. Luigi G. Occhipinti This email address is being protected from spambots. You need JavaScript enabled to view it. visit here .