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Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation

Pregnancy is a unique time when many mothers gain awareness of their lifestyle and its impacts on the fetus. High-quality care during pregnancy is needed to identify possible complications early and ensure the mother’s and her unborn baby’s health and well-being. Different studies have thus far prop...

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Autores principales: Sarhaddi, Fatemeh, Azimi, Iman, Labbaf, Sina, Niela-Vilén, Hannakaisa, Dutt, Nikil, Axelin, Anna, Liljeberg, Pasi, Rahmani, Amir M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036648/
https://www.ncbi.nlm.nih.gov/pubmed/33805217
http://dx.doi.org/10.3390/s21072281
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author Sarhaddi, Fatemeh
Azimi, Iman
Labbaf, Sina
Niela-Vilén, Hannakaisa
Dutt, Nikil
Axelin, Anna
Liljeberg, Pasi
Rahmani, Amir M.
author_facet Sarhaddi, Fatemeh
Azimi, Iman
Labbaf, Sina
Niela-Vilén, Hannakaisa
Dutt, Nikil
Axelin, Anna
Liljeberg, Pasi
Rahmani, Amir M.
author_sort Sarhaddi, Fatemeh
collection PubMed
description Pregnancy is a unique time when many mothers gain awareness of their lifestyle and its impacts on the fetus. High-quality care during pregnancy is needed to identify possible complications early and ensure the mother’s and her unborn baby’s health and well-being. Different studies have thus far proposed maternal health monitoring systems. However, they are designed for a specific health problem or are limited to questionnaires and short-term data collection methods. Moreover, the requirements and challenges have not been evaluated in long-term studies. Maternal health necessitates a comprehensive framework enabling continuous monitoring of pregnant women. In this paper, we present an Internet-of-Things (IoT)-based system to provide ubiquitous maternal health monitoring during pregnancy and postpartum. The system consists of various data collectors to track the mother’s condition, including stress, sleep, and physical activity. We carried out the full system implementation and conducted a real human subject study on pregnant women in Southwestern Finland. We then evaluated the system’s feasibility, energy efficiency, and data reliability. Our results show that the implemented system is feasible in terms of system usage during nine months. We also indicate the smartwatch, used in our study, has acceptable energy efficiency in long-term monitoring and is able to collect reliable photoplethysmography data. Finally, we discuss the integration of the presented system with the current healthcare system.
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spelling pubmed-80366482021-04-12 Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation Sarhaddi, Fatemeh Azimi, Iman Labbaf, Sina Niela-Vilén, Hannakaisa Dutt, Nikil Axelin, Anna Liljeberg, Pasi Rahmani, Amir M. Sensors (Basel) Article Pregnancy is a unique time when many mothers gain awareness of their lifestyle and its impacts on the fetus. High-quality care during pregnancy is needed to identify possible complications early and ensure the mother’s and her unborn baby’s health and well-being. Different studies have thus far proposed maternal health monitoring systems. However, they are designed for a specific health problem or are limited to questionnaires and short-term data collection methods. Moreover, the requirements and challenges have not been evaluated in long-term studies. Maternal health necessitates a comprehensive framework enabling continuous monitoring of pregnant women. In this paper, we present an Internet-of-Things (IoT)-based system to provide ubiquitous maternal health monitoring during pregnancy and postpartum. The system consists of various data collectors to track the mother’s condition, including stress, sleep, and physical activity. We carried out the full system implementation and conducted a real human subject study on pregnant women in Southwestern Finland. We then evaluated the system’s feasibility, energy efficiency, and data reliability. Our results show that the implemented system is feasible in terms of system usage during nine months. We also indicate the smartwatch, used in our study, has acceptable energy efficiency in long-term monitoring and is able to collect reliable photoplethysmography data. Finally, we discuss the integration of the presented system with the current healthcare system. MDPI 2021-03-24 /pmc/articles/PMC8036648/ /pubmed/33805217 http://dx.doi.org/10.3390/s21072281 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ).
spellingShingle Article
Sarhaddi, Fatemeh
Azimi, Iman
Labbaf, Sina
Niela-Vilén, Hannakaisa
Dutt, Nikil
Axelin, Anna
Liljeberg, Pasi
Rahmani, Amir M.
Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation
title Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation
title_full Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation
title_fullStr Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation
title_full_unstemmed Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation
title_short Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation
title_sort long-term iot-based maternal monitoring: system design and evaluation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036648/
https://www.ncbi.nlm.nih.gov/pubmed/33805217
http://dx.doi.org/10.3390/s21072281
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