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

Abstract

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.

Trends in Heart Rate and Heart Rate Variability During Pregnancy and the 3-Month Postpartum Period: Continuous Monitoring in a Free-living Context

“…In this study, we continuously collected HRV data from pregnant women using an IoT-based maternal monitoring system [ 26 ]. The system could collect a considerable amount of HRV data.…”

“…The collected data were transferred to the cloud server for further analysis. The use of such a home-based system during pregnancy and postpartum period was evaluated in a previous study [ 26 ]. The findings of this pilot study indicated the feasibility of the study, robustness of the system, and reliability of the collected HRV parameters.…”

“…We used the smartwatch to collect 12 minutes of PPG signals every 2 hours at a sampling frequency of 20 Hz. The setup was selected to enable battery life of 2 to 3 days after each full recharge [ 26 ]. The collected data were stored on the internal storage of the smartwatch.…”

Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review

“…The various scientific applications apart from image analysis, text recognition and language processing include health care applications like drug activity designing, prediction of risk and gene mutation expression, medical outcomes, propose management in diabetes and mental health, and predict the progression of congestive heart failure, cardiac arrhythmia, bone disease, Alzheimer disease and benign and malignant tumor. 11 , 12 , 13 , 14 , 15 , 16 …”

A comprehensive accuracy assessment of Samsung smartwatch heart rate and heart rate variability

“…Recently, several PPG-based wearable devices have been proposed for health parameters monitoring in everyday life settings. Several studies leveraged different wearable devices, such as Samsung Gear Sport, Apple Watch, Fitbit, and Garmin Vivosmart, for health monitoring in different population-based groups [12][13][14]. With advancements in technology, it is expected that the use of such wearable devices will grow further as they become smaller and lighter with longer battery life.…”