A Comprehensive Framework for Wearable Module for Prenatal Health Monitoring and Risk Detection

This paper proposes a modular health monitoring system for pregnant women, encompassing vital sign monitoring such as temperature, heart rate, oxygen saturation, blood pressure, and introduces a noninvasive Near-Infrared (NIR) blood glucose monitoring system, employing a 2nd order polynomial regression model for enhanced accuracy. Rigorous evaluation using commercially available devices validates the system's reliability. Leveraging Internet of Things (IoT) capabilities, the system enables remote monitoring, fostering real-time connectivity between healthcare providers and expectant mothers. An integrated SMS alert system enhances communication in critical situations. Addressing the challenge of differentiating between normal movements of mother and fetal kicks, the paper introduces a hybrid algorithm utilizing two Inertial Measurement Units (IMUs) for precise fetal kick detection. This comprehensive system offers a holistic solution to prenatal care, with potential implications for improving maternal and fetal health outcomes.