Available maternity care in hospitals not only does not provide continues monitoring for women during the pregnancy but also causes inconvenience for families by increasing the pregnancy costs and forcing them to visit medical experts frequently. Therefore, there exists a need to establish a feasible remote monitoring to collect adequate information from the mothers and share them with medical experts continuously.
The aim of this project is to utilize an IoT-based smartband to develop a remote pregnancy monitoring. The system acquires adequate data from the pregnant women’s daily activities 24/7 and extracts useful information using machine learning and data analysis algorithms. In this project, we consider three monitoring approaches, each of which is essential in pregnancy monitoring. The first approach is activity monitoring specified the activity level and daily steps of pregnant women. The second one is sleep quality monitoring. Analyzing movements during sleep and medical parameters such as heart rate indicate the sleep levels (i.e., light sleep and deep sleep) of pregnant women. Finally, the third approach is medical parameters monitoring. It provides continues data collection and analysis of parameters such as vital signs (e.g., heart rate and temperature) in order to extract valuable information from the mother’s medical state.
Monitoring mother and newborn baby are also very important after delivery. It has been shown that parental closeness and skin-to-skin contact can improve the neurological and neurobehavioural outcomes of infants. An IoT-based closeness sensor is our solution to find and report the gap between baby and mother after birth. For this purpose, an automatic distance measurement system has developed which can detect and report the distance continuously. The proposed solution is a pair of wearable devices that send measure and send distance data to the web cloud wirelessly.