Singapore Institute of Manufacturing Technology, Agency for Science, Technology and Research (A*STAR), 5 Cleantech Loop, Singapore 636732, Singapore.
School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
Sensors (Basel). 2024 Oct 4;24(19):6426. doi: 10.3390/s24196426.
Pregnancy monitoring is always essential for pregnant women and fetuses. According to the report of WHO (World Health Organization), there were an estimated 287,000 maternal deaths worldwide in 2020. Regular hospital check-ups, although well established, are a burden for pregnant women because of frequent travelling or hospitalization. Therefore, home-based, long-term, non-invasive health monitoring is one of the hot research areas. In recent years, with the development of wearable sensors and related data-processing technologies, pregnancy monitoring has become increasingly convenient. This article presents a review on recent research in wearable sensors, physiological data processing, and artificial intelligence (AI) for pregnancy monitoring. The wearable sensors mainly focus on physiological signals such as electrocardiogram (ECG), uterine contraction (UC), fetal movement (FM), and multimodal pregnancy-monitoring systems. The data processing involves data transmission, pre-processing, and application of threshold-based and AI-based algorithms. AI proves to be a powerful tool in early detection, smart diagnosis, and lifelong well-being in pregnancy monitoring. In this review, some improvements are proposed for future health monitoring of pregnant women. The rollout of smart wearables and the introduction of AI have shown remarkable potential in pregnancy monitoring despite some challenges in accuracy, data privacy, and user compliance.
妊娠监测对于孕妇和胎儿来说至关重要。根据世界卫生组织(WHO)的报告,2020 年全球估计有 28.7 万名产妇死亡。尽管定期去医院检查已经得到广泛认可,但由于频繁的旅行或住院,这对孕妇来说是一种负担。因此,基于家庭的、长期的、非侵入性的健康监测是热门研究领域之一。近年来,随着可穿戴传感器和相关数据处理技术的发展,妊娠监测变得越来越便捷。本文对可穿戴传感器、生理数据处理以及人工智能(AI)在妊娠监测中的最新研究进行了综述。可穿戴传感器主要关注心电图(ECG)、子宫收缩(UC)、胎儿运动(FM)等生理信号,以及多模态妊娠监测系统。数据处理涉及数据传输、预处理以及基于阈值和基于 AI 的算法的应用。AI 在妊娠监测的早期检测、智能诊断和终身健康方面证明是一种强大的工具。在这篇综述中,针对未来孕妇的健康监测提出了一些改进措施。尽管在准确性、数据隐私和用户依从性方面存在一些挑战,但智能可穿戴设备的推出和 AI 的引入在妊娠监测中显示出了巨大的潜力。