So, what do horses and playing rock, paper, scissors have in common? Oddly enough, they're both situations where the ability to detect motion provides a very useful edge: early diagnosis of lameness, in the case of the horse, and the ability to always beat you, in the case of a roshambo-playing robot.
For both of these examples, the key point is that distinctive motions can tell us a surprising amount about a given situation. In the case of the horse, Kevin Keegan, who is a professor of equine surgery in the College of Veterinary Medicine at the University of Missouri in Columbia, MO, has used motion sensors to create a Lameness Locator. The basic idea is this: if you're very used to watching how healthy horses move, you can generally tell a horse is lame by performing a visual examination and noting the changes in its gait. The Lameness Locator places small motion sensors on the horse's head, front leg, and its croup (the high point of a horse's rump), records the data as the horse moves, and then compares it with data from healthy and lame horses to figure out whether lameness is present or not. It's not foolproof, by any means—when compared to vets using visual methods the system spotted lameness earlier more than 58% of the time and more than 67% of the time if the lameness was in the animal's hind legs. As the article, "Motion Sensors Detect Horse Lameness Earlier than Veterinarians, MU Study Finds" notes, it's all about the early detection.
High-speed cameras are interesting tools. You can use them to capture high-speed impacts and collisions and explore other high-speed events. (One of my favorite high-speed imaging stories concerns the MIT researchers who analyzed high-speed video of cats drinking and discovered that the cats actually pull the liquid into their mouths rather than scooping the liquid up with their tongues.) They can also be used to aid robot/human communication. Researchers at the Ishiwaka Oku Laboratory at the University of Tokyo coupled a high-speed vision system with a high-speed robotic hand and taught it to play rock, paper, scissors. The vision system recognizes the competitor's hand shape within 1 ms and provides visual feedback to the robot, allowing the robotic hand to display the winning move before the competitor's hand is finished moving into place. For more detail on the roshambo-playing robot, I refer you to Megan Garber's article in The Atlantic, "This Robot Will Beat You at Rock-Paper-Scissors 100 Percent of the Time". It's a clever demonstration of high-speed visual feedback, in response to human motion that is used to affect a robot's interaction with said human. With all the research into humanoid and human-helping robots, giving them better tools to interact with us is an important endeavor.
Right now, a lot of the press coverage of motion sensing is in the context of mobile devices. Stories like these remind us that the world of motion sensing is a much wider and richer one than we might have supposed.