Feb 19, 2025 | Future of Sleep | 0 |
Summary: Researchers from the University of Cambridge have developed “smart pajamas” with printed fabric sensors and a lightweight AI model that can accurately monitor sleep disorders at home by detecting different sleep states and wirelessly transmitting data for potential long-term health monitoring.
Key Takeaways:
- The SleepNet AI model processes sensor data in real time, identifying sleep conditions like snoring, teeth grinding, central sleep apnea, and obstructive sleep apnea with minimal computational power.
- The pajamas can wirelessly transmit data to a smartphone or computer and operate with low energy consumption, making them practical for long-term use without requiring a hospital visit.
- Researchers aim to adapt the technology for other health monitoring uses, including baby monitoring and tracking additional respiratory or neurological conditions.
Researchers have developed comfortable, washable “smart pajamas” that can monitor sleep disorders such as sleep apnea at home.
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.
According to results reported in the Proceedings of the National Academy of Sciences, the smart pajamas 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 identify the difference between regular and disordered sleep.
“Poor sleep has huge effects on our physical and mental health, which is why proper sleep monitoring is vital,” says Luigi Occhipinti, CEng, PhD, SMIEEE, from the Cambridge Graphene Centre, who led the research, in a release. “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.”
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 re-designed 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, and obstructive sleep apnea.
SleepNet is a “lightweight” artificial intelligence (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%. By treating the smart pajamas with a special starching step, they improved the durability of the sensors so they can be run through a regular washing machine.
The most recent version of the smart pajamas can wirelessly transfer data, 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.
Read About Other Iterations of Smart Sleep-Tracking Clothing:
In a Few Years, ‘Smart Pajamas’ Could Monitor Sleep Breathing, Heartbeat, Posture at Home
