TRing: Instant and Customizable Interactions with Objects Using an Embedded Magnet and a Finger-Worn Device

by | Oct 16, 2016

Authors: Sang Ho Yoon, Yunbo Zhang, Ke Huo, Karthik Ramani
In Proceedings of the 29th Annual ACM Symposium on User Interface Software & Technology (UIST'16) , Tokyo, Japan, 2016 (Acceptance Rate: 20.6%)

We present TRing, a finger-worn input device which provides instant and customizable interactions. TRing offers a novel method for making plain objects interactive using an embedded magnet and a finger-worn device. With a particle filter integrated magnetic sensing technique, we compute the fingertip’s position relative to the embedded magnet. We also offer a magnet placement algorithm that guides the magnet installation location based upon the user’s interface customization. By simply inserting or attaching a small magnet, we bring interactivity to both fabricated and existing objects. In our evaluations, TRing shows an average tracking error of 8.6 mm in 3D space and a 2D targeting error of 4.96 mm, which are sufficient for implementing average-sized conventional controls such as buttons and sliders. A user study validates the input performance with TRing on a targeting task (92% accuracy within 45 mm distance) and a cursor control task (91% accuracy for a 10 mm target). Furthermore, we show examples that highlight the interaction capability of our approach.

Sang Ho Yoon

Sang Ho Yoon

Sang Ho Yoon is currently working at Microsoft, Seattle, WA. He received his PhD at Purdue University and his B.S & M.S degrees from Carnegie Mellon University in 2008 with major in Mechanical Engineering and minor in Robotics. He worked at Research Department in LG Display & LG Electronics for 5 years. There, he involved in product development for consumer electronics as well as the futuristic products including 'Transparent & Public Display', 'Assistive/Rehabilitation Robot', and 'Smart Car User Interface'. He is particularly interested in applying novel sensing techniques to bring the new forms of input metaphor for Human-computer interaction. Areas of interest include wearable/tangible interface, sensing techniques & fabrication, and novel input device. Currently, his research aims at combining the state-of-art machine learning approaches with novel sensing technique to better support natural human-computer interaction. [Personal Website][LinkedIn]