Z-Ring: Single-point Bio-impedance Sensing for Gesture, Touch, Object and User Recognition

要旨

We present Z-Ring, a wearable ring that enables gesture input, object detection, user identification, and interaction with passive user interface (UI) elements using a single sensing modality and a single point of instrumentation on the finger. Z-Ring uses active electrical field sensing to detect changes in the hand's electrical impedance caused by finger motions or contact with external surfaces. We develop a diverse set of interactions and evaluate them with 21 users. We demonstrate: (1) Single- and two-handed gesture recognition with up to 93\% accuracy (2) Tangible input with a set of passive touch UI elements, including buttons, a continuous 1D slider, and a continuous 2D trackpad with 91.8\% accuracy, <4.4 cm MAE, and <4.1cm MAE, respectively (3) Object recognition across six household objects with 94.5\% accuracy (4) User identification among 14 users with 99\% accuracy. Z-Ring's sensing methodology uses only a single co-located electrode pair for both receiving and sensing, lending itself well to future miniaturization for use in on-the-go scenarios.

著者
Anandghan Waghmare
University of Washington, Seattle, Washington, United States
Youssef Ben Taleb
University of Washington, Seattle, Washington, United States
Ishan Chatterjee
University of Washington, Seattle, Washington, United States
Arjun Narendra
University of Washington, Seattle, Seattle, Washington, United States
Shwetak Patel
University of Washington, Seattle, Washington, United States
論文URL

https://doi.org/10.1145/3544548.3581422

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Data Analyses and Representation

Hall F
6 件の発表
2023-04-25 18:00:00
2023-04-25 19:30:00