FingerIO: Using Active Sonar for Fine-Grained Finger Tracking
Tracking Fingers
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Nandakumar, Rajalakshmi
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Iyer, Vikram
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Tan, Desney
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Gollakota, Shyamnath
Proceedings of the ACM CHI'16 Conference on Human Factors in Computing
Systems
2016-05-07
v.1
p.1515-1525
© Copyright 2016 ACM
Summary: We present fingerIO, a novel fine-grained finger tracking solution for
around-device interaction. FingerIO does not require instrumenting the finger
with sensors and works even in the presence of occlusions between the finger
and the device. We achieve this by transforming the device into an active sonar
system that transmits inaudible sound signals and tracks the echoes of the
finger at its microphones. To achieve sub-centimeter level tracking accuracies,
we present an innovative approach that use a modulation technique commonly used
in wireless communication called Orthogonal Frequency Division Multiplexing
(OFDM). Our evaluation shows that fingerIO can achieve 2-D finger tracking with
an average accuracy of 8 mm using the in-built microphones and speaker of a
Samsung Galaxy S4. It also tracks subtle finger motion around the device, even
when the phone is in the pocket. Finally, we prototype a smart watch
form-factor fingerIO device and show that it can extend the interaction space
to a 0.5×0.25 m2 region on either side of the device and work even when
it is fully occluded from the finger.
