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A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device
Background: Uterine activity (UA) monitoring is an essential element of pregnancy management. The gold-standard intrauterine pressure catheter (IUPC) is invasive and requires ruptured membranes, while the standard-of-care, external tocodynamometry (TOCO)’s accuracy is hampered by obesity, maternal m...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343786/ https://www.ncbi.nlm.nih.gov/pubmed/35928952 http://dx.doi.org/10.3389/fbioe.2022.933612 |
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author | Mhajna, Muhammad Sadeh, Boaz Yagel, Simcha Sohn, Christof Schwartz, Nadav Warsof, Steven Zahar, Yael Reches, Amit |
author_facet | Mhajna, Muhammad Sadeh, Boaz Yagel, Simcha Sohn, Christof Schwartz, Nadav Warsof, Steven Zahar, Yael Reches, Amit |
author_sort | Mhajna, Muhammad |
collection | PubMed |
description | Background: Uterine activity (UA) monitoring is an essential element of pregnancy management. The gold-standard intrauterine pressure catheter (IUPC) is invasive and requires ruptured membranes, while the standard-of-care, external tocodynamometry (TOCO)’s accuracy is hampered by obesity, maternal movements, and belt positioning. There is an urgent need to develop telehealth tools enabling patients to remotely access care. Here, we describe and demonstrate a novel algorithm enabling remote, non-invasive detection and monitoring of UA by analyzing the modulation of the maternal electrocardiographic and phonocardiographic signals. The algorithm was designed and implemented as part of a wireless, FDA-cleared device designed for remote pregnancy monitoring. Two separate prospective, comparative, open-label, multi-center studies were conducted to test this algorithm. Methods: In the intrapartum study, 41 laboring women were simultaneously monitored with IUPC and the remote pregnancy monitoring device. Ten patients were also monitored with TOCO. In the antepartum study, 147 pregnant women were simultaneously monitored with TOCO and the remote pregnancy monitoring device. Results: In the intrapartum study, the remote pregnancy monitoring device and TOCO had sensitivities of 89.8 and 38.5%, respectively, and false discovery rates (FDRs) of 8.6 and 1.9%, respectively. In the antepartum study, a direct comparison of the remote pregnancy monitoring device to TOCO yielded a sensitivity of 94% and FDR of 31.1%. This high FDR is likely related to the low sensitivity of TOCO. Conclusion: UA monitoring via the new algorithm embedded in the remote pregnancy monitoring device is accurate and reliable and more precise than TOCO standard of care. Together with the previously reported remote fetal heart rate monitoring capabilities, this novel method for UA detection expands the remote pregnancy monitoring device’s capabilities to include surveillance, such as non-stress tests, greatly benefiting women and providers seeking telehealth solutions for pregnancy care. |
format | Online Article Text |
id | pubmed-9343786 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93437862022-08-03 A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device Mhajna, Muhammad Sadeh, Boaz Yagel, Simcha Sohn, Christof Schwartz, Nadav Warsof, Steven Zahar, Yael Reches, Amit Front Bioeng Biotechnol Bioengineering and Biotechnology Background: Uterine activity (UA) monitoring is an essential element of pregnancy management. The gold-standard intrauterine pressure catheter (IUPC) is invasive and requires ruptured membranes, while the standard-of-care, external tocodynamometry (TOCO)’s accuracy is hampered by obesity, maternal movements, and belt positioning. There is an urgent need to develop telehealth tools enabling patients to remotely access care. Here, we describe and demonstrate a novel algorithm enabling remote, non-invasive detection and monitoring of UA by analyzing the modulation of the maternal electrocardiographic and phonocardiographic signals. The algorithm was designed and implemented as part of a wireless, FDA-cleared device designed for remote pregnancy monitoring. Two separate prospective, comparative, open-label, multi-center studies were conducted to test this algorithm. Methods: In the intrapartum study, 41 laboring women were simultaneously monitored with IUPC and the remote pregnancy monitoring device. Ten patients were also monitored with TOCO. In the antepartum study, 147 pregnant women were simultaneously monitored with TOCO and the remote pregnancy monitoring device. Results: In the intrapartum study, the remote pregnancy monitoring device and TOCO had sensitivities of 89.8 and 38.5%, respectively, and false discovery rates (FDRs) of 8.6 and 1.9%, respectively. In the antepartum study, a direct comparison of the remote pregnancy monitoring device to TOCO yielded a sensitivity of 94% and FDR of 31.1%. This high FDR is likely related to the low sensitivity of TOCO. Conclusion: UA monitoring via the new algorithm embedded in the remote pregnancy monitoring device is accurate and reliable and more precise than TOCO standard of care. Together with the previously reported remote fetal heart rate monitoring capabilities, this novel method for UA detection expands the remote pregnancy monitoring device’s capabilities to include surveillance, such as non-stress tests, greatly benefiting women and providers seeking telehealth solutions for pregnancy care. Frontiers Media S.A. 2022-07-19 /pmc/articles/PMC9343786/ /pubmed/35928952 http://dx.doi.org/10.3389/fbioe.2022.933612 Text en Copyright © 2022 Mhajna, Sadeh, Yagel, Sohn, Schwartz, Warsof, Zahar and Reches. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioengineering and Biotechnology Mhajna, Muhammad Sadeh, Boaz Yagel, Simcha Sohn, Christof Schwartz, Nadav Warsof, Steven Zahar, Yael Reches, Amit A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device |
title | A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device |
title_full | A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device |
title_fullStr | A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device |
title_full_unstemmed | A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device |
title_short | A Novel, Cardiac-Derived Algorithm for Uterine Activity Monitoring in a Wearable Remote Device |
title_sort | novel, cardiac-derived algorithm for uterine activity monitoring in a wearable remote device |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343786/ https://www.ncbi.nlm.nih.gov/pubmed/35928952 http://dx.doi.org/10.3389/fbioe.2022.933612 |
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