Scientists develop smart pyjamas to monitor sleep conditions at home
18 February 2025, 10:24
Researchers said the garment has an ‘ultrasensitive sensor array directly printed on the collar, capable of identifying multiple sleep patterns’.
Scientists are developing smart pyjamas which could monitor disorders such as sleep apnoea at home.
Cambridge University researchers said the garment has an “ultrasensitive sensor array directly printed on the collar, capable of identifying multiple sleep patterns”, which begins by detecting subtle vibrations.
They designed the smart pyjamas to be washable and to offer an alternative to traditional sleep monitoring systems that are “complex and inconvenient for daily use”.
Traditional means of monitoring include sticky patches, cumbersome equipment or a visit to a specialist sleep clinic.
The team behind the project said the “proposed smart garment has the potential to become a new benchmark in sleep monitoring technology”.
Professor Luigi Occhipinti, from the Cambridge Graphene Centre, who led the research, said: “Poor sleep has huge effects on our physical and mental health, which is why proper sleep monitoring is vital.
“However, the current gold standard for sleep monitoring – polysomnography or PSG – is expensive, complicated and isn’t suitable for long-term use at home.
“We need something that is comfortable and easy to use every night, but is accurate enough to provide meaningful information about sleep quality.”
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, according to the researchers.
The sensors embedded in the smart pyjamas were trained using an artificial intelligence (AI) algorithm and can identify six different sleep states with 98.6% accuracy, while ignoring regular sleep movements such as tossing and turning, according to the research.
The results were reported in the journal Proceedings of the National Academy of Sciences (PNAS).
Sleep behaviours such as mouth breathing, sleep apnoea and snoring are major contributors to poor sleep quality and can lead to chronic conditions such as cardiovascular disease, diabetes and depression.
Smart textile wearable sensor for continuous breath monitoring and accurate classification of sleep conditions. @Cambridge_Eng @cambridge_ee @GrapheneUCam #OcchipintiGroup #ChenyuTang #WentianYi https://t.co/l7FN8sCLPm
— Luigi Occhipinti (@locchipi) February 12, 2025
To develop the smart pyjamas, Prof Occhipinti and his colleagues re-designed graphene-based sensors from an earlier project for breath analysis during sleep.
They 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,” said Prof 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 most recent version of the smart pyjamas is 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,” said Prof 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 behaviours 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.
