Since 2013, researchers at MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) have been developing technologies that use wireless signals to track human motion. The team has shown that it can detect gestures and body movements as subtle as the rise and fall of a person’s chest from the other side of a house, allowing a firefighter to determine if there are survivors inside a burning building. Now, by testing different human subjects and using metrics such as height and body shape to create concrete “silhouette fingerprints” for each person, researchers can use wireless reflections to differentiate between individuals from the other side of wall. By tracking the silhouette, the device can trace a person’s hand as he writes in the air and even distinguish between 15 different people through a wall with nearly 90 percent accuracy. The device works by transmitting wireless signals that traverse the wall and reflect off a person’s body back to the device. The device captures these reflections and analyzes them in order to see the person’s silhouette.