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EarBuddy: Enabling On-Face Interaction via Wireless Earbuds

Authors:

Alex Mariakakis,

Jennifer Mankoff,

Anind K. DeyAuthors Info & Claims

CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

Pages 1 - 14

https://doi.org/10.1145/3313831.3376836

Published: 23 April 2020 Publication History

Abstract

Past research regarding on-body interaction typically requires custom sensors, limiting their scalability and generalizability. We propose EarBuddy, a real-time system that leverages the microphone in commercial wireless earbuds to detect tapping and sliding gestures near the face and ears. We develop a design space to generate 27 valid gestures and conducted a user study (N=16) to select the eight gestures that were optimal for both human preference and microphone detectability. We collected a dataset on those eight gestures (N=20) and trained deep learning models for gesture detection and classification. Our optimized classifier achieved an accuracy of 95.3%. Finally, we conducted a user study (N=12) to evaluate EarBuddy's usability. Our results show that EarBuddy can facilitate novel interaction and that users feel very positively about the system. EarBuddy provides a new eyes-free, socially acceptable input method that is compatible with commercial wireless earbuds and has the potential for scalability and generalizability

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Cited By

Sato YAmesaka TYamamoto TWatanabe HSugiura Y(2024)Exploring User-Defined Gestures as Input for Hearables and Recognizing Ear-Level Gestures with IMUsProceedings of the ACM on Human-Computer Interaction10.1145/36765038:MHCI(1-23)Online publication date: 24-Sep-2024
https://dl.acm.org/doi/10.1145/3676503
Gao XSun MZhao KKostakos VKay JHoang T(2024)Designing More Private and Socially Acceptable Hand-to-Face Gestures for Heads-Up ComputingCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3678994(637-639)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3678994
Zhang XWang YHan YLiang CChatterjee ITang JYi XPatel SShi Y(2024)The EarSAVAS DatasetProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36596168:2(1-26)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3659616
Show More Cited By

Index Terms

EarBuddy: Enabling On-Face Interaction via Wireless Earbuds
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction techniques
  2. Ubiquitous and mobile computing

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cover image ACM Conferences

CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

April 2020

10688 pages

ISBN:9781450367080

DOI:10.1145/3313831

General Chairs:
Regina Bernhaupt
Eindhoven University of Technology, Netherlands
,
Florian 'Floyd' Mueller
Monash University, Australia
,
David Verweij
Newcastle University, UK
,
Josh Andres
RMIT, Australia
,
Program Chairs:
Joanna McGrenere
University of British Columbia, Canada
,
Andy Cockburn
University of Canterbury, New Zealand
,
Ignacio Avellino
University of Maryland Baltimore County, USA
,
Alix Goguey
Grenoble Alpes University, France
,
Pernille Bjørn
University of Copenhagen, Denmark
,
Shengdong (Shen) Zhao
National University of Singapore, Singapore
,
Briane Paul Samson
Future University Hakodate, Japan & De La Salle University, Philippines
,
Rafal Kocielnik
University of Washington, USA

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Published: 23 April 2020

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the National Institute on Disability, Independent Living and Rehabilitation Research
the Natural Science Foundation of China
Beijing Key Lab of Networked Multimedia
the National Key Research and Development Plan
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CHI '20: CHI Conference on Human Factors in Computing Systems

April 25 - 30, 2020

HI, Honolulu, USA

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Cited By

Sato YAmesaka TYamamoto TWatanabe HSugiura Y(2024)Exploring User-Defined Gestures as Input for Hearables and Recognizing Ear-Level Gestures with IMUsProceedings of the ACM on Human-Computer Interaction10.1145/36765038:MHCI(1-23)Online publication date: 24-Sep-2024
https://dl.acm.org/doi/10.1145/3676503
Gao XSun MZhao KKostakos VKay JHoang T(2024)Designing More Private and Socially Acceptable Hand-to-Face Gestures for Heads-Up ComputingCompanion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/3675094.3678994(637-639)Online publication date: 5-Oct-2024
https://dl.acm.org/doi/10.1145/3675094.3678994
Zhang XWang YHan YLiang CChatterjee ITang JYi XPatel SShi Y(2024)The EarSAVAS DatasetProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36596168:2(1-26)Online publication date: 15-May-2024
https://dl.acm.org/doi/10.1145/3659616
Suzuki SAmesaka TWatanabe HShizuki BSugiura Y(2024)EarHover: Mid-Air Gesture Recognition for Hearables Using Sound Leakage SignalsProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676367(1-13)Online publication date: 13-Oct-2024
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