Comprehensive pregnancy monitoring with a network of wireless, soft, and flexible sensors in high- and low-resource health settings
Vital signs monitoring is a fundamental component of ensuring the health and safety of women and newborns during pregnancy, labor, and childbirth. This monitoring is often the first step in early detection of pregnancy abnormalities, providing an opportunity for prompt, effective intervention to pre...
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Published in | Proceedings of the National Academy of Sciences - PNAS Vol. 118; no. 20; pp. 1 - 11 |
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Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
National Academy of Sciences
18.05.2021
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Subjects | |
Online Access | Get full text |
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Summary: | Vital signs monitoring is a fundamental component of ensuring the health and safety of women and newborns during pregnancy, labor, and childbirth. This monitoring is often the first step in early detection of pregnancy abnormalities, providing an opportunity for prompt, effective intervention to prevent maternal and neonatal morbidity and mortality. Contemporary pregnancy monitoring systems require numerous devices wired to large base units; at least five separate devices with distinct user interfaces are commonly used to detect uterine contractility, maternal blood oxygenation, temperature, heart rate, blood pressure, and fetal heart rate. Current monitoring technologies are expensive and complex with implementation challenges in low-resource settings where maternal morbidity and mortality is the greatest. We present an integrated monitoring platform leveraging advanced flexible electronics, wireless connectivity, and compatibility with a wide range of low-cost mobile devices. Three flexible, soft, and low-profile sensors offer comprehensive vital signs monitoring for both women and fetuses with time-synchronized operation, including advanced parameters such as continuous cuffless blood pressure, electrohysterography-derived uterine monitoring, and automated body position classification. Successful field trials of pregnant women between 25 and 41 wk of gestation in both high-resource settings (n = 91) and low-resource settings (n = 485) demonstrate the system’s performance, usability, and safety. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Contributed by John A. Rogers, March 29, 2021 (sent for review January 9, 2021; reviewed by Carmen Poon and Takao Someya) 1D.R., D.H.K., J.T.P., J.Y.L., and H.U.C. contributed equally to this work. Reviewers: C.P., GMed IT Ltd; and T.S., University of Tokyo. Author contributions: D.R., H.U.C., A.S.P., A.P., W.A.G., J.A.R., and S.X. designed research; D.R., H.U.C., E.A., R.L., K.L.M., and B.R.K. performed research; J.T.P., J.Y.L., H. Jeong, J.C., E. Kulikova, H.A.-Z., J.L., E. Kim, Y.P., H. Jang, H.A., C.L., M.C., B.V., N.S., M.B.S., A.S.P., A.P., W.A.G., and J.S.A.S. contributed new reagents/analytic tools; D.R., D.H.K., J.Y.L., E.A., M.Z., and M.H. analyzed data; and D.R., J.R.W., J.A.R., and S.X. wrote the paper. |
ISSN: | 0027-8424 1091-6490 1091-6490 |
DOI: | 10.1073/pnas.2100466118 |