iBreath: Usage Of Breathing Gestures as Means of Interactions

TL;DR

This paper presents iBreath, a system that detects breathing gestures for hands-free interaction with high accuracy, user comfort, and practical guidelines for future development.

Contribution

It introduces a novel bio-impedance based breathing gesture detection system with high accuracy and provides design guidelines for future breathing gesture interfaces.

Findings

Detection accuracy > 95.2% F1-score

Users found gestures easy and comfortable

Robust performance with models trained on 21 participants

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.