血压
光容积图
卷积神经网络
深度学习
人工智能
计算机科学
子痫前期
医学
人工神经网络
内科学
怀孕
电信
生物
无线
遗传学
作者
Duc Huy Nguyen,Paul C.-P. Chao,Hiu Fai Yan,Tse-Yi Tu,Chin-Hung Cheng,Tan-Phat Phan
出处
期刊:IEEE Journal of Biomedical and Health Informatics
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:: 1-14
标识
DOI:10.1109/jbhi.2024.3386707
摘要
Blood pressure (BP) is predicted by this effort based on photoplethysmography (PPG) data to provide effective pre-warning of possible preeclampsia of pregnant women. Towards frequent BP measurement, a PPG sensor device is utilized in this study as a solution to offer continuous, cuffless blood pressure monitoring frequently for pregnant women. PPG data were collected using a flexible sensor patch from the wrist arteries of 194 subjects, which included 154 normal individuals and 40 pregnant women. Deep-learning models in 3 stages were built and trained to predict BP. The first stage involves developing a baseline deep-learning BP model using a dataset from common subjects. In the 2
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