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Breathin : a breath pattern sensing approach for user computer interaction

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Cam_OzCHI_2019.pdf (1.469Mb)
Date
02/12/2019
Author
Hundia, Rohan
Quigley, Aaron
Keywords
Breath
BreathIn
Breath sensing
Exhale
QA75 Electronic computers. Computer science
QP Physiology
T Technology
NS
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Abstract
New interaction modalities in human computer interaction often explore common sensory inputs including touch, voice, gesture or motion. However, these modalities are not inclusive of the entire population type, and cannot be utilized by a group of people who suffer from any limitation of that sensory input. Here we propose BreathIn: an interface tool for enabling interaction with computer applications by using discreet exhalation patterns. The intent is that such patterns can be issued by anyone who can breathe. Our concept is based on detecting a user's forced exhalation patterns in a time duration using a MEMS microphone placed below the user's nose. We breakdown the signal into FFT components and identify peak frequencies for forced voluntary "breath events" and use that in real-time to distinguish between "exhalation events" and noise. We show two major applications of such an interaction tool: a) adaptation of computer applications using breath, b) using the breath interface as a discreet, emergency signal for prospective victims of crime.
Citation
Hundia , R & Quigley , A 2019 , Breathin : a breath pattern sensing approach for user computer interaction . in OZCHI'19 : Proceedings of the 31st Australian Conference on Human-Computer-Interaction . ACM , New York , pp. 581-584 , OZCHI'19 , Perth/Freemantle , Western Australia , Australia , 2/12/19 . https://doi.org/10.1145/3369457.3369536
 
conference
 
Publication
OZCHI'19
DOI
https://doi.org/10.1145/3369457.3369536
Type
Conference item
Rights
Copyright © 2019 the owner/author(s). This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1145/3369457.3369536
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/19289

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