MIT researchers looking to wirelessly monitor sleep patterns

The setup includes a device that beams radio waves off a sleeping subject while changes in the body are detected when they bounce back.

MIT researchers looking to wirelessly monitor sleep patterns

MIT researchers have unveiled a new method for wirelessly monitoring sleep. The setup includes a device that beams radio waves off a sleeping subject while changes in the body are detected when they bounce back.

Also on the receiving end, the AI technology is able to translate subtle movement into meaningful information about the subject's sleep patterns, including sleep stages (light/deep/R.E.M.), movement and breathing rate.

Initial tests, conducted on 25 volunteers over 100 nights of sleep, have found that the system was able to detect sleep patterns with around an 80 percent accuracy rate, which is roughly the same as industry-standard EEG sleep tests.

In comparison, most of today's wrist-worn activity trackers such as those made by Fitbit as well as the Apple Watch rely almost exclusively on movement detected by an accelerometer to determine sleep patterns.

"Wearables are great, but our vision was to have something we call 'invisibles,'" says study lead professor Dina Katabi. "It's a device that disappears into the background of your home, but at the same time, monitors any sort of health problems, just using wireless signals."

The wireless system takes into account a variety of factors, including movement, breathing and pulse rate. It does all that while staying out of the way, placed on a shelf or mounted on a wall a few meters away from the sleeper.

Power-wise, the system is more efficient than Wi-Fi though it is robust enough to be used in different locations with different patients, without requiring any recalibration. All of that means it could be ideal for use in monitoring patients at home in their natural sleep setting.

Speaking of which, going forward researchers plan to use the technology to figure out the ways in which sleep patterns impact diseases like Parkinson's and Alzheimer's, both of which are linked closely to various sleep disorders.

Nevertheless, we are looking at something that is in early stages and which at some point will need FDA's seal of approval to be used for monitoring of patients. Still, these early results seem promising.

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