iBreath: Usage Of Breathing Gestures as Means of Interactions
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916828970745856 |
|---|---|
| author | Liu, Mengxi Geißler, Daniel Gurung, Deepika Bello, Hymalai Zhou, Bo Bian, Sizhen Lukowicz, Paul Elagroudy, Passant |
| author_facet | Liu, Mengxi Geißler, Daniel Gurung, Deepika Bello, Hymalai Zhou, Bo Bian, Sizhen Lukowicz, Paul Elagroudy, Passant |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_04162 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | iBreath: Usage Of Breathing Gestures as Means of Interactions Liu, Mengxi Geißler, Daniel Gurung, Deepika Bello, Hymalai Zhou, Bo Bian, Sizhen Lukowicz, Paul Elagroudy, Passant Human-Computer Interaction 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. |
| title | iBreath: Usage Of Breathing Gestures as Means of Interactions |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2507.04162 |