Predicting Blood Pressures for Pregnant Women by PPG and Personalized Deep Learning.

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Tác giả: Paul C-P Chao, Chin-Hung Cheng, Duc Huy Nguyen, Tan-Phat Phan, Tse-Yi Tu, Hiu Fai Yan

Ngôn ngữ: eng

Ký hiệu phân loại: 439.827009 Danish and Norwegian

Thông tin xuất bản: United States : IEEE journal of biomedical and health informatics , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 719268

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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