Pregnant women with obesity have indisputably increased risk for gestational diabetes mellitus, depression, miscarriage, and preterm birth, just to mention few. These pregnancy complications clearly have negative effects on their unborn children. Due to the magnitude of this global challenge it calls for immediate action. During the course of this project, an Internet-of-Things-based intelligent monitoring system will be developed to detect and predict obesity-related pregnancy complications as early as possible. Cybernetic health concept will be utilized by intertwining lifestyle and environmental data together with bio-signals associated with medical knowledge to develop a closed-loop system to make maternity care more effective, dynamic and end-user driven. This is done via a platform that leverages portable devices and inexpensive wearable sensors, coupled with a multimodal event modeling, activity recognition, and life-logging engine. This research will deliver a ubiquitous pregnancy monitoring service to end-users, mothers, and healthcare providers, enabling pregnancy events detection, prediction, assessment, and prevention.

Funded by Academy of Finland