Poster: Noninvasive Respirator Fit Factor Inference by Semi-Supervised Learning
Authors: 
Jinmiao Chen, Zhaohe Zhang, Shangqing Zhao, Song Fang, Thomas M. Peters, Evan L. Floyd, Changjie CaiAuthors Info & Claims
Pages 200 - 202
Abstract
The need for personal protective equipment, such as respirators, has been emphasized by pandemics as they provide protection against infectious diseases. Adequate protection is only possible when respirators fit properly and are worn correctly. Therefore, it is especially critical to closely monitor and ensure respirator fit, particularly during a pandemic. To ensure proper fit and continuous monitoring, we propose a new noninvasive method that uses speech signals to measure the attenuation of sound caused by the respirator. This method provides a quantitative measure of respirator Fit Factor (FF, the ratio of the concentration of a substance in ambient air to its concentration inside the respirator). This method is also cost-effective and easy to implement. By collecting limited labeled and unlabeled speech data, augmenting labeled data, extracting time and frequency domain features, we achieved up to 86.24% accuracy in respirator fit detection using semi-supervised learning model.
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Index Terms
- Poster: Noninvasive Respirator Fit Factor Inference by Semi-Supervised Learning
Index terms have been assigned to the content through auto-classification.
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Information
Published In
June 2023
232 pages
ISBN:9798400701023
DOI:10.1145/3580252
- Chair:
- Shiwen Mao,
- Proceedings Editor:
- Shuangquan Wang,
- Program Chairs:
- Hua Fang,
- Wei Gao,
- Gang Zhou
Copyright © 2023 Owner/Author(s).
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).
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- SIGBED: ACM Special Interest Group on Embedded Systems
- IEEE Computer Society
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 22 January 2024
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- Poster
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CHASE '23
Sponsor:
CHASE '23: 8th ACM/IEEE International Conference on Connected Health: Applications, Systems and Engineering Technologies
June 21 - 23, 2023
FL, Orlando, USA
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