Oscillometry-Based Blood Pressure Estimation Using Convolutional Neural Networks
Author:
Affiliation:
1. Digital Health Research Division, Korea Institute of Oriental Medicine, Daejeon, South Korea
2. InBody Company Ltd., Seoul, South Korea
Funder
Korea Medical Device Development Fund Grant through the Korea Government
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09780358.pdf?arnumber=9780358
Reference33 articles.
1. Improved Gaussian Mixture Regression Based on Pseudo Feature Generation Using Bootstrap in Blood Pressure Estimation
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3. The British hypertension society protocol for the evaluation of blood pressure measuring devices;o’brien;J Hypertension,1993
4. Influence of Build Orientation, Heat Treatment, and Laser Power on the Hardness of Ti6Al4V Manufactured Using the DMLS Process
5. Deep learning ensemble with asymptotic techniques for oscillometric blood pressure estimation
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