Our two demonstrations showcase millimeter wave's ability to provide a unique sensing data set-- range, velocity, and angle-- and how that data set can be used to enable applications in contact-less gesture recognition. Our first demonstration shows how the angle of detection for millimeter wave can be used to determine where the hand is relative to the sensor. We use this data output from an IWR 1443 in order to recognize a swipe gesture and then trigger a video player to move to the next video.

Our second demonstration shows how the unique velocity detection for a millimeter wave can be used to determine the rotation direction of a twirling finger. We use this data from an IWR 1443 in order to traverse the slice level of an MRI image stack, zooming up and zooming down. This demonstration is even possible through material such as drywall, plywood, glass, and plastic.

Imagine you're a surgeon working on a patient. You can't touch or use electronics, because you're in a clean environment, or imagine you're in a dusty factory where gloves and dust prevent you from interacting with control panels. These are examples of where millimeter wave's unique data set and robustness to the environment can help enable new applications for gesture recognition. To learn more about millimeter wave sensors and access the EVM source codes and algorithms used to replicate this example, please click on the link below. Thanks for watching.