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At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch
Obstructive sleep apnea (OSA) affects more than 900 million adults globally and can create serious health complications when untreated; however, 80% of cases remain undiagnosed. Critically, current diagnostic techniques are fundamentally limited by low throughputs and high failure rates. Here, we re...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8694628/ https://www.ncbi.nlm.nih.gov/pubmed/34936438 http://dx.doi.org/10.1126/sciadv.abl4146 |
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author | Zavanelli, Nathan Kim, Hojoong Kim, Jongsu Herbert, Robert Mahmood, Musa Kim, Yun-Soung Kwon, Shinjae Bolus, Nicholas B. Torstrick, F. Brennan Lee, Christopher S. D. Yeo, Woon-Hong |
author_facet | Zavanelli, Nathan Kim, Hojoong Kim, Jongsu Herbert, Robert Mahmood, Musa Kim, Yun-Soung Kwon, Shinjae Bolus, Nicholas B. Torstrick, F. Brennan Lee, Christopher S. D. Yeo, Woon-Hong |
author_sort | Zavanelli, Nathan |
collection | PubMed |
description | Obstructive sleep apnea (OSA) affects more than 900 million adults globally and can create serious health complications when untreated; however, 80% of cases remain undiagnosed. Critically, current diagnostic techniques are fundamentally limited by low throughputs and high failure rates. Here, we report a wireless, fully integrated, soft patch with skin-like mechanics optimized through analytical and computational studies to capture seismocardiograms, electrocardiograms, and photoplethysmograms from the sternum, allowing clinicians to investigate the cardiovascular response to OSA during home sleep tests. In preliminary trials with symptomatic and control subjects, the soft device demonstrated excellent ability to detect blood-oxygen saturation, respiratory effort, respiration rate, heart rate, cardiac pre-ejection period and ejection timing, aortic opening mechanics, heart rate variability, and sleep staging. Last, machine learning is used to autodetect apneas and hypopneas with 100% sensitivity and 95% precision in preliminary at-home trials with symptomatic patients, compared to data scored by professionally certified sleep clinicians. |
format | Online Article Text |
id | pubmed-8694628 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-86946282022-01-03 At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch Zavanelli, Nathan Kim, Hojoong Kim, Jongsu Herbert, Robert Mahmood, Musa Kim, Yun-Soung Kwon, Shinjae Bolus, Nicholas B. Torstrick, F. Brennan Lee, Christopher S. D. Yeo, Woon-Hong Sci Adv Physical and Materials Sciences Obstructive sleep apnea (OSA) affects more than 900 million adults globally and can create serious health complications when untreated; however, 80% of cases remain undiagnosed. Critically, current diagnostic techniques are fundamentally limited by low throughputs and high failure rates. Here, we report a wireless, fully integrated, soft patch with skin-like mechanics optimized through analytical and computational studies to capture seismocardiograms, electrocardiograms, and photoplethysmograms from the sternum, allowing clinicians to investigate the cardiovascular response to OSA during home sleep tests. In preliminary trials with symptomatic and control subjects, the soft device demonstrated excellent ability to detect blood-oxygen saturation, respiratory effort, respiration rate, heart rate, cardiac pre-ejection period and ejection timing, aortic opening mechanics, heart rate variability, and sleep staging. Last, machine learning is used to autodetect apneas and hypopneas with 100% sensitivity and 95% precision in preliminary at-home trials with symptomatic patients, compared to data scored by professionally certified sleep clinicians. American Association for the Advancement of Science 2021-12-22 /pmc/articles/PMC8694628/ /pubmed/34936438 http://dx.doi.org/10.1126/sciadv.abl4146 Text en Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Physical and Materials Sciences Zavanelli, Nathan Kim, Hojoong Kim, Jongsu Herbert, Robert Mahmood, Musa Kim, Yun-Soung Kwon, Shinjae Bolus, Nicholas B. Torstrick, F. Brennan Lee, Christopher S. D. Yeo, Woon-Hong At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch |
title | At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch |
title_full | At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch |
title_fullStr | At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch |
title_full_unstemmed | At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch |
title_short | At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch |
title_sort | at-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch |
topic | Physical and Materials Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8694628/ https://www.ncbi.nlm.nih.gov/pubmed/34936438 http://dx.doi.org/10.1126/sciadv.abl4146 |
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