By Omar Kardoudi / New Atlas
Imagine learning to operate a piece of machinery you've never previously touched, not through a tutorial, but through your own hands, electrically guided through the right motions. That's the core idea behind an AI-powered suit created by researchers from the University of Chicago.
The system was developed by PhD students Yun Ho and Romain Nith under researcher Pedro Lopes at the University of Chicago's Human Computer Integration Lab (HCintegration). It combines a wearable electrode suit, smart glasses with a built-in camera, a motion-tracking layer, and a multimodal AI model capable of processing both vision and language, the same class of technology as GPT-4.1. The suit physically moves a user's muscles in real time, adapting to whatever task is in front of them, with no pre-programmed routine required.
"This could be a game-changer, not only for tasks that are highly physical (such as learning physical skills required for working with manufacturing and materials or learning musical instruments) but also in situations where users might be situationally impaired," said Lopes.
The technology is built on electrical muscle stimulation (EMS), a technique that sends low-level electrical pulses to specific muscles to trigger movement. EMS has been used for years in physical rehabilitation, teaching piano sequences, and sign language training. But earlier systems were essentially fixed scripts. Program one to shake a spray can, and it would do it reliably. Show it a cooking oil spray that doesn't need shaking, and it would shake it anyway. Context was invisible.
The new system can reason about context. Smart glasses capture what's in front of the user, the motion-tracking suit reads their posture in real time, and the AI processes all of that to generate movement instructions tailored to the specific moment. It decides which joint to move, in which direction, and in what order.