Artificial intelligence-assisted smart maternal health monitoring device for early prediction of high-risk pregnancy,maternal complications, andPersonalized nursing care

Abstract

Maternal health remains a major global public health concern despite remarkable advances in obstetric care and digital health technologies. Pregnancy is a dynamic physiological process that requires continuous monitoring to ensure maternal and fetal well-being. High-risk pregnancies, characterized by conditions such as hypertensive disorders, gestational diabetes mellitus, preterm labor, fetal growth restriction, maternal anemia, and cardiovascular complications, account for a significant proportion of maternal and neonatal morbidity and mortality worldwide. Conventional antenatal care relies heavily on periodic hospital visits, which may fail to identify subtle physiological changes occurring between appointments. Consequently, delayed diagnosis often results in preventable adverse maternal and fetal outcomes. Recent developments in Artificial Intelligence (AI), wearable biosensors, Internet of Medical Things (IoMT), cloud computing, and mobile health technologies have transformed maternal healthcare by enabling continuous physiological monitoring, real-time risk prediction, and personalized clinical decision-making. AI-assisted smart maternal health monitoring devices integrate multiple physiological sensors with advanced machine learning algorithms to continuously analyze maternal and fetal parameters. These systems facilitate early identification of pregnancy complications while supporting timely medical intervention and individualized nursing care. Artificial intelligence algorithms can analyze large volumes of maternal physiological data, identify hidden risk patterns, predict pregnancy-related complications, and provide automated alerts to healthcare professionals. Such technologies improve the accuracy of risk assessment while reducing unnecessary hospital admissions and enhancing patient engagement. Furthermore, AI-driven decision support systems assist nurses in developing individualized care plans, prioritizing high-risk mothers, promoting health education, and improving continuity of maternal care. This review discusses recent advances in AI-assisted smart maternal health monitoring devices, their applications in predicting maternal complications, their role in personalized nursing care, current challenges, ethical considerations, and future directions for integrating intelligent technologies into maternal healthcare systems. The review highlights the transformative potential of AI in reducing maternal mortality and improving pregnancy outcomes through early diagnosis and evidence-based nursing interventions (Topol et al., 2019; Rajpurkar et al., 2022; World Health Organization, 2023).