Department of Computer Science, Wah Campus, COMSATS University Islamabad, Islamabad 45040, Pakistan.
School of Computing, Engineering and Physical Sciences, University of the West of Scotland, Glasgow G72 0LH, UK.
Sensors (Basel). 2022 Jun 9;22(12):4362. doi: 10.3390/s22124362.
Currently, information and communication technology (ICT) allows health institutions to reach disadvantaged groups in rural areas using sensing and artificial intelligence (AI) technologies. Applications of these technologies are even more essential for maternal and infant health, since maternal and infant health is vital for a healthy society. Over the last few years, researchers have delved into sensing and artificially intelligent healthcare systems for maternal and infant health. Sensors are exploited to gauge health parameters, and machine learning techniques are investigated to predict the health conditions of patients to assist medical practitioners. Since these healthcare systems deal with large amounts of data, significant development is also noted in the computing platforms. The relevant literature reports the potential impact of ICT-enabled systems for improving maternal and infant health. This article reviews wearable sensors and AI algorithms based on existing systems designed to predict the risk factors during and after pregnancy for both mothers and infants. This review covers sensors and AI algorithms used in these systems and analyzes each approach with its features, outcomes, and novel aspects in chronological order. It also includes discussion on datasets used and extends challenges as well as future work directions for researchers.
目前,信息和通信技术(ICT)使医疗机构能够利用传感和人工智能(AI)技术为农村地区的弱势群体提供服务。这些技术在母婴健康方面的应用更为重要,因为母婴健康对健康的社会至关重要。在过去的几年中,研究人员深入研究了用于母婴健康的传感和人工智能医疗保健系统。利用传感器来衡量健康参数,并研究机器学习技术来预测患者的健康状况,以协助医务人员。由于这些医疗保健系统处理大量数据,因此在计算平台方面也取得了重大发展。相关文献报告了 ICT 支持的系统在改善母婴健康方面的潜在影响。本文回顾了现有的基于可穿戴传感器和 AI 算法的系统,这些系统旨在预测母亲和婴儿在怀孕期间和之后的风险因素。本综述涵盖了这些系统中使用的传感器和 AI 算法,并按时间顺序分析了每种方法的特点、结果和新颖方面。它还包括对使用的数据集的讨论,并扩展了研究人员的挑战以及未来的工作方向。