This smart ring lets you write with simple gestures
Researchers at the University of Washington have developed a smart ring that could allow users to control other pieces of technology with just simple finger gestures.
AuraRing consists of a 3D-printed ring wrapped in a coil of wire and a wristband that contains three sensors. According to the university, the ring emits a signal that is picked up by the wristband, then identifies the location and orientation of the ring.
“AuraRing’s ring consumes only 2.3 milliwatts of power, which produces an oscillating magnetic field that the wristband can constantly sense,” Farshid Salemi Parizi, one of the researchers and a doctoral student in electrical and computer engineering, explained in a co-authored study. “In this way, there’s no need for any communication from the ring to the wristband.”
Because it regularly tracks the position of a finger, the ring can also pick up handwriting, allowing users to quickly respond to text messages using shorthand. Perhaps more impressive is the fact that AuraRing can track hands even when they’re out of sight since it uses magnetic fields.
“We can also easily detect taps, flicks or even a small pinch versus a big pinch,” Salemi Parizi noted. “This gives you added interaction space. For example, if you write ‘hello,’ you could use a flick or a pinch to send that data.”
Researchers said they developed the ring because they “wanted a tool that captures the fine-grain manipulation we do with our fingers — not just a gesture or where your finger’s pointed, but something that can track your finger completely.”
While the ring could prove particularly handy when playing games or using smartphones, researchers at the University of Washington believe AuraRing can be used in other settings as well.
“Because AuraRing continuously monitors hand movements and not just gestures, it provides a rich set of inputs that multiple industries could take advantage of,” Shwetak Patel, a professor and senior author of the study, wrote. “For example, AuraRing could detect the onset of Parkinson’s disease by tracking subtle hand tremors or help with stroke rehabilitation by providing feedback on hand movement exercises.”
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