![]() The team succeeded in teaching the algorithm to recognize 21 individual hand gestures, including a thumbs-up, a fist, a flat hand, holding up individual fingers and counting numbers. ![]() The electrical signals then feed into an electrical chip, programmed with an AI algorithm capable of associating these signal patterns in the forearm with specific hand gestures. To create the hand gesture recognition system, the team collaborated with Ana Arias, a professor of electrical engineering, to design a flexible armband that can read the electrical signals at 64 different points on the forearm. And, while there are other ways of doing that, by, for instance, using cameras and computer vision, this is a good solution that also maintains an individual’s privacy.” “Reading hand gestures is one way of improving human-computer interaction. Moin is co-first author of the study in Nature Electronics. ![]() “ Prosthetics are one important application of this technology, but besides that, it also offers a very intuitive way of communicating with computers.” says Ali Moin, who helped design the device as a doctoral student in the electrical engineering and computer sciences department at the University of California, Berkeley. That’s the goal researchers envision for the system, which couples wearable biosensors with artificial intelligence (AI) and could one day control prosthetics or to interact with almost any type of electronic device. Imagine typing on a computer without a keyboard, playing a video game without a controller, or driving a car without a wheel. University University of California, BerkeleyĪ new device can recognize hand gestures based on electrical signals it detects in the forearm.
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