Comprehensive Monitoring System for High-Risk Pregnancies

Abstract Prenatal care protects the Health of both mother and baby, influencing the development and well-being of the mother-child duo. Risks during pregnancy, such as preeclampsia or gestational diabetes, can have long-term effects on the mother’s Health. Effective monitoring of pregnancy risks is essential for improving health outcomes. Therefore, we propose the development of an integrated high-risk pregnancy monitoring mobile application incorporating IoT sensors (smartwatches) to monitor critical biomedical variables. This allows healthcare professionals to collect and analyze data, reducing prenatal risks and improving maternal and fetal health outcomes. Functional and non-functional requirements were gathered and refined through continuous support and iterative meetings with an experienced gynecologist. We identified multiple functional requirements through user stories. Non-functional requirements were also collected to design the proposed architecture and comply with current legislation, prioritizing the security and privacy of biomedical data. We conducted Load tests on the proposed architecture, verifying the system’s quality attributes. Additionally, we carried out usability tests through interviews with a sample of ten pregnant women. Participants found the application intuitive and essential for monitoring their Health, and it could provide a constant source of confidence throughout their pregnancy. The proposed system could be a valuable tool for high-risk pregnancy monitoring. However, large and intensive clinical trials are essential to validate its effectiveness in real-life scenarios.

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Institutions

Publication Details

Journal
SN Computer Science
Published
2024-12-06
DOI
https://doi.org/10.1007/s42979-024-03342-x
Citations
1
Primary Topic
Mobile Health and mHealth Applications
Type
article
Field-Weighted Citation Impact
0.85

Funders

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article

Comprehensive Monitoring System for High-Risk Pregnancies

Germán A. Montoya, Carlos Lozano-Garzón, Silvia González
1 citations
SN Computer Science
Mobile Health and mHealth Applications
0.85
article

Comprehensive Monitoring System for High-Risk Pregnancies

Germán A. Montoya, Carlos Lozano-Garzón, Silvia González
article en
1 citations

Abstract

Abstract Prenatal care protects the Health of both mother and baby, influencing the development and well-being of the mother-child duo. Risks during pregnancy, such as preeclampsia or gestational diabetes, can have long-term effects on the mother’s Health. Effective monitoring of pregnancy risks is essential for improving health outcomes. Therefore, we propose the development of an integrated high-risk pregnancy monitoring mobile application incorporating IoT sensors (smartwatches) to monitor critical biomedical variables. This allows healthcare professionals to collect and analyze data, reducing prenatal risks and improving maternal and fetal health outcomes. Functional and non-functional requirements were gathered and refined through continuous support and iterative meetings with an experienced gynecologist. We identified multiple functional requirements through user stories. Non-functional requirements were also collected to design the proposed architecture and comply with current legislation, prioritizing the security and privacy of biomedical data. We conducted Load tests on the proposed architecture, verifying the system’s quality attributes. Additionally, we carried out usability tests through interviews with a sample of ten pregnant women. Participants found the application intuitive and essential for monitoring their Health, and it could provide a constant source of confidence throughout their pregnancy. The proposed system could be a valuable tool for high-risk pregnancy monitoring. However, large and intensive clinical trials are essential to validate its effectiveness in real-life scenarios.

SN Computer ScienceVol. 5(8)
Universidad de Los Andes (CO)
Universidad de los Andes
Good health and well-being
Openalex Percentile: Top 19%
Mobile Health and mHealth Applications
0.85
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Comprehensive Monitoring System for High-Risk Pregnancies — Germán A. Montoya, Carlos Lozano-Garzón, et al. · SN Computer Science (2024) | TGRS Research Map | TGRS