Researchers from the Georgia Institute of Technology have reportedly created a wearable ring and wristband that can easily control mobile applications.
The new technology makes use of acoustic chirps from a wearable ring that is then received by a wristband resembling a smartwatch. The system can reportedly recognize about 22 different “micro finger gestures” that can be programmed to several commands. These commands reportedly include a T9 keyboard interface, a set of numbers, and application commands like playing or stopping music.
“Some interaction is not socially appropriate,” said Cheng Zhang, a PH. D. student in the School of Interactive Computing who led the project.
“A wearable is always on you, so you should have the ability to interact through that wearable at any time in an appropriate and discreet fashion. When we’re talking, I can still make some quick reply that doesn’t interrupt our interaction.”
According to Zhang, their system is a preliminary step in recognizing ASL as a translator in the future. To date, other techniques rely on cameras to recognize hand gestures. However, Zhang believes that such technology could be obtrusive and can’t be carried anywhere.
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Dubbed as FingerPing, Zhang and his team’s wearable ring and wristband produce acoustic chirps that travel through the hand which is then picked up by the watch. The system takes advantage of the specific patterns in which sound waves go through structures like our hand.
These soundwave patterns can be altered by hand poses which in turn can be pre-programmed to execute commands.
“The receiver recognizes these tiny differences,” Zhang explained.
“The injected sound from the thumb will travel at different paths inside the body with different hand postures. For instance, when your hand is open, there is only one direct path from the thumb to the wrist. Any time you do a gesture where you close a loop, the sound will take a different path, and that will form a unique signature.”
The new technology is considered a proof of concept that could be expanded and improved in the future. It was presented by Zhang and his team last month during the 2018 ACM Conference on Human Factors in Computing Systems (CHI).