A wearable eddy current based pulmonary function sensor for continuous non-contact point-of-care monitoring during the COVID-19 pandemic
Creators
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1.
California Institute of Technology
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2.
University of Southern California
Abstract
Pulmonary function testing (PFT) allows for quantitative analysis of lung function. However, as a result of the coronavirus disease 2019 (COVID-19) pandemic, a majority of international medical societies have postponed PFTs in an effort to mitigate disease transmission, complicating the continuity of care in high-risk patients diagnosed with COVID-19 or preexisting lung pathologies. Here, we describe the development of a non-contact wearable pulmonary sensor for pulmonary waveform analysis, pulmonary volume quantification, and crude thoracic imaging using the eddy current (EC) phenomenon. Statistical regression analysis is performed to confirm the predictive validity of the sensor, and all data are continuously and digitally stored with a sampling rate of 6,660 samples/second. Wearable pulmonary function sensors may facilitate rapid point-of-care monitoring for high-risk individuals, especially during the COVID-19 pandemic, and easily interface with patient hospital records or telehealth services.
Additional Information
© The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Received 29 December 2020; Accepted 29 September 2021; Published 11 October 2021. Parts of Figures 1, 2, and 6, and Supplementary Figures 1, 2, and 3 were created using Biorender.com. This study was funded by the Merkin COVID-19 Challenge Grant. Institutional Review Board approval was obtained prior to data collection. All patient identifiers have been removed, and measures were taken to keep data de-identified and ensure privacy throughout the course of the study. There are no conflicts of interest in this study. Author Contributions: S.S. designed experiments, conducted analysis, wrote manuscript, revised manuscript. T.C., G.Z., Z.B., and A.P.R. helped with IRB approval and edited the manuscript. K.M.S. helped with revisions. Y.T. designed experiments, guided direction of research, and edited the manuscript. The authors declare no competing interests.Attached Files
Published - s41598-021-99682-2.pdf
Supplemental Material - 41598_2021_99682_MOESM1_ESM.docx
Files
s41598-021-99682-2.pdf
Additional details
Identifiers
- PMCID
- PMC8505507
- Eprint ID
- 111355
- Resolver ID
- CaltechAUTHORS:20211011-193517859
Funding
- Caltech Merkin Institute for Translational Research
Dates
- Created
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2021-10-11Created from EPrint's datestamp field
- Updated
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2021-10-15Created from EPrint's last_modified field
Caltech Custom Metadata
- Caltech groups
- COVID-19 , Richard N. Merkin Institute for Translational Research