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Research at Mass General
Research Roundup is a monthly column highlighting recent research studies from investigators at Massachusetts General Hospital. This month, we look at a new food allergen detector small enough to fit on a keychain, and a new system for measuring sleep that is wireless, portable and powered by artificial intelligence.
A team at Massachusetts General Hospital has created a new device small enough to fit on a keyring that costs only $40 and can accurately test for food allergens in less than ten minutes.
Developed by co-senior team leaders Ralph Weissleder, MD, PhD, Director of the Center for Systems Biology (CSB) at Mass General and Hakho Lee, PhD, Hostetter MGH Research Scholar and Director of the Biomedical Engineering Program at the CSB, the device, called integrated exogenous antigen testing (iEAT), consists of three components:
Testing performed by the research team showed that measurements of the concentration of the allergen is extremely accurate.
Consumers may be able to purchase the $40 iEAT device and corresponding app in the near future — the research team has granted a license to a local start-up company to make the system commercially available.
This research was recently highlighted in an NIH article and published in ACS Nano.
Sleep disorders are typically diagnosed by bringing a patient into an overnight sleep lab. However, individuals with sleep disorders may have even more difficulty sleeping when they are hooked up to wires and in the artificial setting of a sleep lab.
To make it easier to diagnose and study sleep problems at home, researchers at MIT and Mass General have created a new system for measuring sleep that is wireless, portable and powered by artificial intelligence.
The system consists of a laptop-sized device that emits low frequency radio waves while an individual is sleeping. The device then measures changes in those waves that are caused by shifts in movement and breathing patterns in sleeping individuals. The device then uses an advanced algorithm—powered by artificial intelligence—to translate these changes into the different stages of sleep.
In a test of 25 healthy volunteers, the new system proved to be 80 percent accurate in identifying sleep stages, which is comparable to the accuracy of a sleep specialist reading EEG measurements, according to the research team.
Their next step is to use the system to investigate how Parkinson’s disease affects sleep. Future research projects could look into common sleep disorders such as insomnia and sleep apnea, investigating how sleep is affected by Alzheimer’s disease, and detecting epileptic seizures that occur during sleep.
Matt Bianchi, chief of the Division of Sleep Medicine at Mass General, was a senior author on this work.
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