iBreath: Usage of Breathing Gestures as Means of Interactions MHCI016

Breathing is a spontaneous but controllable body function that can be used for hands-free interaction. Our work introduces “iBreath”, a novel system to detect breathing gestures similar to clicks using bio-impedance. We evaluated iBreath’s accuracy and user experience using two lab studies (n=34). Our results show high detection accuracy (F1-scores > 95.2%). Furthermore, the users found the gestures easy to use and comfortable. Thus, we developed eight practical guidelines for the future development of breathing gestures. For example, designers can train users on new gestures within just 50 seconds (five trials), and achieve robust performance with both user-dependent and user-independent models trained on data from 21 participants, each yielding accuracies above 90%. Users preferred single clicks and disliked triple clicks. The median gesture duration is 3.5-5.3 seconds. Our work provides solid ground for researchers to experiment with creating breathing gestures and interactions.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-09-09
DOI
https://doi.org/10.1145/3743710
Primary Topic
Gaze Tracking and Assistive Technology
Type
article
Field-Weighted Citation Impact
0.00
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article

iBreath: Usage of Breathing Gestures as Means of Interactions MHCI016

Bo Zhou, Paul Lukowicz, Daniel Geißler, Sizhen Bian et al.
Proceedings of the ACM on Human-Computer Interaction
Gaze Tracking and Assistive Technology
article

iBreath: Usage of Breathing Gestures as Means of Interactions MHCI016

Bo Zhou, Paul Lukowicz, Daniel Geißler, Sizhen Bian, Passant Elagroudy, Hymalai Bello, Mengxi Liu, Deepika Gurung
article en

Abstract

Breathing is a spontaneous but controllable body function that can be used for hands-free interaction. Our work introduces “iBreath”, a novel system to detect breathing gestures similar to clicks using bio-impedance. We evaluated iBreath’s accuracy and user experience using two lab studies (n=34). Our results show high detection accuracy (F1-scores > 95.2%). Furthermore, the users found the gestures easy to use and comfortable. Thus, we developed eight practical guidelines for the future development of breathing gestures. For example, designers can train users on new gestures within just 50 seconds (five trials), and achieve robust performance with both user-dependent and user-independent models trained on data from 21 participants, each yielding accuracies above 90%. Users preferred single clicks and disliked triple clicks. The median gesture duration is 3.5-5.3 seconds. Our work provides solid ground for researchers to experiment with creating breathing gestures and interactions.

Proceedings of the ACM on Human-Computer InteractionVol. 9(5)
University of Kaiserslautern (DE), University of Koblenz and Landau (DE), German Research Centre for Artificial Intelligence (DE), Embedded Systems (United States) (US)
Openalex Percentile: Top 76%
Gaze Tracking and Assistive Technology
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iBreath: Usage of Breathing Gestures as Means of Interactions MHCI016 — Bo Zhou, Paul Lukowicz, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS