MIT, Mass General Aim Deep Learning at Study of Sleep Stages

One in three U.S. adults generally don’t sleep enough, according to the Center for Disease Control and Prevention, which defines healthy sleep as more than seven hours daily. Chest straps, nasal probes and head electrodes are among the traditional sensors routinely attached to patients needing their sleep patterns monitored. These uncomfortable methods can themselves cause sleeplessness, rendering data collected unrepresentative. Hoping to provide a better night’s sleep for these patients, researchers from MIT and Massachusetts General Hospital are studying the use of AI and a Wi-Fi-like signal that monitors a person without any sensors attached.