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RESEARCHERS at MIT have developed a technology that can use reflections of wireless signals off the human body to identify, track and monitor people.
Researchers from MIT’s Computer Science and Artificial Intelligence Lab (CSAIL) have previously developed technologies that use wireless signals to track human motion. They found they could detect gestures and body movements as subtle as the rise and fall of a person’s chest from the other side of a house.
The team outlined a new technology called RF Capture that picks up wireless reflections off the human body to see the silhouette of a human standing behind a wall. RF Capture can track the silhouette in a precise manner. Using the shape of the silhouette to identify individuals, it can also distinguish between 15 different people through a wall with nearly 90 percent accuracy.
This ability to "see through walls" could have major implications for everything from gaming and filmmaking to emergency response and eldercare.
For example, motion capture in movie production may be able to do away with the special suits and markers and arrays of cameras. RF Capture could instead capture the motion of the body with minimal setup.
The device's motion-capturing technology makes it equally valuable for smart homes, according to MIT professor and paper co-author Dina Katabi.
“We’re working to turn this technology into an in-home device that can call 911 if it detects that a family member has fallen unconscious,” says Katabi, director of the Wireless@MIT center. “You could also imagine it being used to operate your lights and TVs, or to adjust your heating by monitoring where you are in the house.”
Future versions could be integrated into gaming interfaces, allowing interactions with games, much like the Microsoft Kinect, but freeing the user to enter another room and still have their actions detected. The possibilities for combinations with technologies like virtual reality are potentially endless.
RF Capture works by transmitting wireless signals that traverse the wall and reflect off a person’s body back to the device. These wireless signals do not have to be very strong: RF Capture emits radiation approximately 1/10,000 the amount given off by a standard cellphone.
The RF Capture device then captures these reflections and analyses them in order to see the person’s silhouette.
A key challenge is the data from the reflections are very minimal, since different individuals and body parts all reflect the same signal.
The researchers use a series of algorithms that help them extract meaningful signals from the random noise produced by the reflections.
The technology operates in two stages: First, it scans 3-D space to capture wireless reflections off objects in the environment, including the human body. However, since only a subset of body parts reflect the signal back at any given point in time, the device then monitors how these reflections vary as someone moves in the environment and intelligently stitches the person’s reflections across time to reconstruct his silhouette into a single image.
To differentiate between people, the team then repeatedly tested and trained the device on different subjects, using metrics such as height and body shape to create concrete “silhouette fingerprints” for each person.