FingerOrbits: Interaction with Wearables Using Synchronized Thumb Movements 

Published on 2017 international symposium on wearable computers/ISWC’17.

Cheng Zhang, Xiaoxuan Wang, Anandghan Waghmare, Sumeet Jain, Thomas Ploetz, Omer T.Inan, Thad E. Starner, Gregory D. Abowd

We introduce FingerSound, an input technology to recognize unistroke thumb gestures, which are easy to learn and can be performed through eyes-free interaction. The gestures are performed using a thumb-mounted ring comprising a contact microphone and a gyroscope sensor. A K-Nearest-Neighbor(KNN) model with a distance function of Dynamic Time Warping (DTW) is built to recognize up to 42 common unistroke gestures. A user study, where the real-time classification results were given, shows an accuracy of 92%-98% by a machine learning model built with only 3 training samples per gesture. Based on the user study results, we further discuss the opportunities, challenges and practical limitations of FingerSound when deploying it to real-world applications in the future.

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