BudsID: Mobile-Ready and Expressive Finger Identification Input for Earbuds

要旨

Wireless earbuds are an appealing platform for wearable computing on-the-go. However, their small size and out-of-view location mean they support limited different inputs. We propose finger identification input on earbuds as a novel technique to resolve these problems. This technique involves associating touches by different fingers with different responses. To enable it on earbuds, we adapted prior work on smartwatches to develop a wireless earbud featuring a magnetometer that detects fields from a magnetic ring. A first study reveals participants achieve rapid, precise earbud touches with different fingers, even while mobile (time: 0.98s, errors: 5.6%). Furthermore, touching fingers can be accurately classified (96.9%). A second study shows strong performance with a more expressive technique involving multi-finger double-taps (inter-touch time: 0.39s, errors: 2.8%) while maintaining high accuracy (94.7%). We close by exploring and evaluating the design of earbud finger identification applications and demonstrating the feasibility of our system on low-resource devices.

著者
Jiwan Kim
KAIST, Daejeon, Korea, Republic of
Mingyu Han
UNIST, Ulsan, Korea, Republic of
Ian Oakley
KAIST, Daejeon, Korea, Republic of
DOI

10.1145/3706598.3714133

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714133

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Earable and Hearable

Annex Hall F206
5 件の発表
2025-04-28 20:10:00
2025-04-28 21:40:00
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