The involvement of the Internet of Things (IoT) technology and artificial intelligence (AI) in the matter of maternal healthcare has allowed monitoring pregnant women in real-time and predicting poor pregnancy outcomes, including stillbirth and premature birth. Nevertheless, to diminish the risks of devices, the introduction of such technologies has to be accompanied by harsh safety monitoring programs. Materiovigilance, as the systematic sensing and monitoring of adverse events associated with medical instruments, is also crucial to patient safety in high-risk obstetric environments. Wearable sensors, e.g., fetal Dopplers, smart fabrics, and adhesive patches, have enhanced the prediction of stillbirth by offering continuous acquisition of physiological data but presents a hazard of ill effects if not controlled adequately. The AI introduction into the sphere of Materiovigilance enhances regulatory conformity, real-time decision-making, and raises the possibility of risk identification. Despite the massive potential, issues such as inaccurate data, poor infrastructure, and underreporting persist, particularly in low- and middle-income countries. In such circumstances, the Materiovigilance Programme of India is another staged effort to enhance the device safety supervision and reporting systems. Engagement of different stakeholders such as clinicians, engineers, regulatory agencies, and technology developers provides an opportunity to secure the safety and efficacy of AI-equipped medical devices. Enhancement of Materiovigilance systems is required to preserve proper maternal-fetal health and sustain clinics in digital obstetrics, as any error in maternal-fetal monitoring may lead to preventable death.
Pramanik et al. (Mon,) studied this question.