Li Yongming, Zhang Yuanfan, Ye Changrong, Wang Pin, Zeng Xiaoping
School of microelectronics and communication engineering, Chongqing University, Chongqing 400044, P.R.China.
College of Optoelectronic Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, P.R.China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2020 Oct 25;37(5):910-917. doi: 10.7507/1001-5515.201912011.
The monitoring of pregnant women is very important. It plays an important role in reducing fetal mortality, ensuring the safety of perinatal mother and fetus, preventing premature delivery and pregnancy accidents. At present, regular examination is the mainstream method for pregnant women's monitoring, but the means of examination out of hospital is scarce, and the equipment of hospital monitoring is expensive and the operation is complex. Using intelligent information technology (such as machine learning algorithm) can analyze the physiological signals of pregnant women, so as to realize the early detection and accident warning for mother and fetus, and achieve the purpose of high-quality monitoring out of hospital. However, at present, there are not enough public research reports related to the intelligent processing methods of out-of-hospital monitoring for pregnant women, so this paper takes the out-of-hospital monitoring for pregnant women as the research background, summarizes the public research reports of intelligent processing methods, analyzes the advantages and disadvantages of the existing research methods, points out the possible problems, and expounds the future development trend, which could provide reference for future related researches.
对孕妇进行监测非常重要。它在降低胎儿死亡率、确保围产期母婴安全、预防早产和妊娠意外方面发挥着重要作用。目前，定期检查是孕妇监测的主流方法，但院外检查手段匮乏，且医院监测设备昂贵、操作复杂。利用智能信息技术（如机器学习算法）可以分析孕妇的生理信号，从而实现对母婴的早期检测和事故预警，达到高质量院外监测的目的。然而，目前关于孕妇院外监测智能处理方法的公开研究报道不足，因此本文以孕妇院外监测为研究背景，总结智能处理方法的公开研究报道，分析现有研究方法的优缺点，指出可能存在的问题，并阐述未来发展趋势，可为未来相关研究提供参考。
