Researchers at the Massachusetts Institute of Technology (MIT) and Massachusetts General Hospital have developed a sleep monitoring system that uses an artificial intelligence algorithm to analyze radio signals around subjects and translate those measurements into sleep stages.
The research team previously developed radio-based sensors for remotely measuring vital signs and other health behaviors, built from a wireless device that emits low-power radio frequency signals.
The algorithm is based on deep neural networks, and is designed to eliminate unwanted noise while preserving the sleep signals.
"Our device allows you not only to remove all of these sensors that you put on the person, and make it a much better experience that can be done at home, it also makes the job of the doctor and the sleep technologist much easier," says MIT professor Dina Katabi.
The approach determined the technique was about 80% accurate, which is comparable to the accuracy of ratings ascertained by sleep specialists based on electroencephalogram measurements.
From MIT News
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