Engineers have developed a next-generation wearable system that enables people to control machines using everyday gestures — even while running, riding in a car, or floating on turbulent ocean waves.
The system combines stretchable electronics with artificial intelligence to overcome a long-standing challenge in wearable technology: reliable recognition of gesture signals in real-world environments.
The device is a soft electronic patch that is glued onto a cloth armband. It integrates motion and muscle sensors, a Bluetooth microcontroller, and a stretchable battery into a compact, multilayered system. The system was trained from a composite dataset of real gestures and conditions, from running and shaking to the movement of ocean waves. Signals from the arm are captured and processed by a customized deep-learning framework that strips away interference, interprets the gesture, and transmits a command to control a machine — such as a robotic arm — in real time.
The technology could enable patients in rehabilitation or individuals with limited mobility, for example, to use natural gestures to control robotic aids without relying on fine motor skills. Industrial workers and first responders could potentially use the technology for hands-free control of tools and robots in high-motion or hazardous environments. (Image credit: David Baillot/UC San Diego Jacobs School of Engineering)
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