Indutivo, at UIST’18

The Auracle team presented an innovative sensing technology for interacting with wearable devices, during the UIST 2018 in Berlin, Germany.

indutivoAbstract: We present Indutivo, a contact-based inductive sensing technique for contextual interactions. Our technique recognizes conductive objects (metallic primarily) that are commonly found in households and daily environments, as well as their individual movements when placed against the sensor. These movements include sliding, hinging, and rotation. We describe our sensing principle and how we designed the size, shape, and layout of our sensor coils to optimize sensitivity, sensing range, recognition and tracking accuracy. Through several studies, we also demonstrated the performance of our proposed sensing technique in environments with varying levels of noise and interference conditions. We conclude by presenting demo applications on a smartwatch, as well as insights and lessons we learned from our experience.

Read the full paper in ACM digital library:

Jun Gong, Xin Yang, Teddy Seyed, Josh Urban Davis, and Xing-Dong Yang. 2018. Indutivo: Contact-Based, Object-Driven Interactions with Inductive Sensing. In Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology (UIST ’18). ACM, pp.321-333. DOI:

Author: David Kotz

David Kotz is the Champion International Professor in the Department of Computer Science. He previously served as Interim Provost, as Associate Dean of the Faculty for the Sciences, as the Executive Director of the Institute for Security Technology Studies, and on the US Healthcare IT Policy Committee. His research interests include security and privacy, pervasive computing for healthcare, and wireless networks. He has published over 175 refereed journal and conference papers and obtained over $66m in grant funding. He is an Fellow of the IEEE, a Distinguished Member of the ACM, a 2008 Fulbright Fellow to India, and an elected member of Phi Beta Kappa. After receiving his A.B. in Computer Science and Physics from Dartmouth in 1986, he completed his Ph.D in Computer Science from Duke University in 1991 and returned to Dartmouth to join the faculty. For more information see

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