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Advances in Non-Invasive Blood Pressure Monitoring
Quan, Xina Liu, Junjun Roxlo, Thomas Siddharth, Siddharth Leong, Weyland Muir, Arthur Cheong, So-Min Rao, Anoop
Quan, Xina
Liu, Junjun
Roxlo, Thomas
Siddharth, Siddharth
Leong, Weyland
Muir, Arthur
Cheong, So-Min
Rao, Anoop
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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.
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Date
2021-06-22
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MDPI
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Quan_2021.pdf
Adobe PDF, 2.41 MB
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Keywords
cNIBP, Neonate, NICU, Hypertension, Hypotension, Non-invasive blood pressure monitoring
Citation
Quan, X.; Liu, J.; Roxlo, T.; Siddharth, S.; Leong, W.; Muir, A.; Cheong, S.-M.; Rao, A. Advances in Non-Invasive Blood Pressure Monitoring. Sensors 2021, 21, 4273. https://doi.org/10.3390/s21134273