Author:
Quan Xina,Liu Junjun,Roxlo Thomas,Siddharth Siddharth,Leong Weyland,Muir Arthur,Cheong So-Min,Rao Anoop
Abstract
This paper reviews recent advances in non-invasive blood pressure monitoring and highlights the added value of a novel algorithm-based blood pressure sensor which uses machine-learning techniques to extract blood pressure values from the shape of the pulse waveform. We report results from preliminary studies on a range of patient populations and discuss the accuracy and limitations of this capacitive-based technology and its potential application in hospitals and communities.
Funder
Eunice Kennedy Shriver National Institute of Child Health and Human Development
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Cited by
28 articles.
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