Fighting reduction in global GDP with Smart Pyjamas
The smart pyjama can identify 6 different states of sleep – sleep disorders can cause a estimated one percent reduction in global GDP
Researchers, led by the University of Cambridge, have developed comfortable, washable ‘smart pyjamas’ that can monitor sleep disorders such as sleep apnoea at home, without the need for sticky patches, cumbersome equipment or a visit to a specialist sleep clinic.
They developed printed fabric sensors that can monitor breathing by detecting tiny movements in the skin, even when the pyjamas are worn loosely around the neck and chest.
The sensors embedded in the smart pyjamas were trained using a ‘lightweight’ AI algorithm and can identify six different sleep states with 98.6% 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.
Sleep is vital for human health, yet more than 60% 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
The researchers say that their smart pyjamas 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.
They also 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 apnoea (CSA), and obstructive sleep apnoea (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.
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