A New Tool Can Track Your Sleep Without Ever Touching You

Every year, tens of millions of Americans toss and turn with chronic sleep disorders. But diagnosis isn’t easy: It usually means sleeping in a lab entangled in gadgets that track breathing, heart rate, movement, and brain activity, followed by expert analysis of the data. Now, a new technique that uses machine learning and radio signals can get rid of the sleep lab—and the expert. First, an in-home device bounces radio waves—similar to those in cellphones and WiFi routers—off the sleeper, measuring the returning signal. Then, the system builds on previous radio-frequency sleep monitoring by using three machine learning algorithms to analyze breathing and pulse and identify the stage of sleep: light, deep, REM, or wakefulness. Measured against an EEG system that was about as proficient as humans, the system identified sleep stages with 80% accuracy, versus 64% for the previous best radio frequency method.

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