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A summary of research progress on intelligent information processing methods for pregnant women's remote monitoring / 生物医学工程学杂志
Article in Chinese | WPRIM (Western Pacific) | ID: wpr-879220
Responsible library: WPRO
ABSTRACT
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.
Subject(s)

Full text: Available Health context: SDG3 - Health and Well-Being Health problem: Target 3.1: Reduce maternal mortality Database: WPRIM (Western Pacific) Main subject: Pregnant Women / Fetus Type of study: Screening study Limits: Female / Humans / Pregnancy Language: Chinese Journal: Journal of Biomedical Engineering Year: 2020 Document type: Article
Full text: Available Health context: SDG3 - Health and Well-Being Health problem: Target 3.1: Reduce maternal mortality Database: WPRIM (Western Pacific) Main subject: Pregnant Women / Fetus Type of study: Screening study Limits: Female / Humans / Pregnancy Language: Chinese Journal: Journal of Biomedical Engineering Year: 2020 Document type: Article
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