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FingerPing: Recognizing Fine-Grained Hand Poses Using Active Acoustics Extraction from the Body  

Published on CHI'18

Cheng Zhang, Qiuyue Xue, Anandghan Waghmare, Ruichen Meng, Sumeet Jain, Yizeng Han, Xinyu Li, Kenneth Cunefare, Thomas Plötz, Thad Starner, Omer Inan, Gregory D. Abowd

FingerPing is a novel sensing technique that can recognize various fine-grained hand poses by analyzing acoustic resonance features. A surface-transducer mounted on a thumb ring injects acoustic chirps (20Hz to 6,000Hz) to the body. Four receivers distributed on the wrist and thumb collect the chirps. Different hand poses of the hand create distinct paths for the acoustic chirps to travel, creating unique frequency responses at the four receivers. We demonstrate how FingerSonar can differentiate up to 22 hand poses, including the thumb touching each of the 12 phalanges on the hand as well as 10 American sign language poses. A user study with 16 participants showed that our system can recognize these two sets of poses with an accuracy of 93.77% and 95.64%, respectively. We discuss the opportunities and remaining challenges for the widespread use of this input technique.

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