Publications

IllumiWear: A Bendable Interactive Fiber-Optic eTextile for Audio and Visual Interactions

Published in NIME, 2019

We present IllumiWear, a novel eTextile prototype that uses fiber optic cables as interactive input and visual output. Fiber optic cables are separated into bundles and then woven like a basket into a bendable glowing fabric. By equipping light emitting diodes to one side of these bundles and photodiode light intensity sensors to the other, loss of light intensity can be measured when the fabric is bent. The sensing technique of IllumiWear is not only able to discriminate between discreet touch, slight bends, and harsh bends, but also recover the location of deformation. In this way, our computational fabric prototype uses it’s intrinsic means of visual output (light) as a tool for interactive input. We provide design and implementation details for our prototype as well as a technical evaluation of it’s effectiveness and limitations as an interactive computational textile. In addition, we examine the potential of this prototypes interactive capabilities by extending our eTextile to create a tangible user interface for audio and visual manipulation.Download paper here

Recommended citation: Josh Urban Davis “IllumiWear: A Bendable Interactive Fiber-Optic eTextile for Audio and Visual Interactions.” ; Proc of New Interfaces in Music Expression (NIME). Porto Alegre, Brazil 2019. /files/Illumiwear_NIME_2018.pdf

Indutivo: Contact-Based Object-Driven Interactions with Inductive Sensing.

Published in User Interface Software Technology (UIST18), 2018

Watch Indutivo Demo Video 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.

Recommended citation: Jun Gong, Xin Yang, Teddy Sayed, Josh Urban Davis, Xing-Dong Yang. “Indutivo: Contact-Based Object-Driven Interactions with Inductive Sensing.” ; Proc of User Interface Software Technology (UIST). Berlin, Germany 2018. http://home.cs.dartmouth.edu/~jungong/pdfs/Indutivo.pdf