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Lookup NU author(s): Emeritus Professor Alan MurrayORCiD, Dr Dingchang Zheng, Dr Clive Griffiths, Dr Chengyu Liu, Dr David Graham, Professor Jeffrey Neasham
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2025. The Author(s). There is a well-accepted need for a new more accurate solution to automatic blood pressure measurement, in spite of clinical convenience continuing to encourage the adoption of oscillometric devices with their known poor accuracy throughout healthcare. Our solution avoids estimates, mathematical modelling, oscillometric algorithms, and inadequate calibration against numerous private clinical data sets. Here we show that our new technique detects, from an arm cuff, micropulses associated with arterial opening between systolic and diastolic pressures; hence detecting systole at the first micropulse and diastole at the last, during cuff deflation. Our technique has equivalent accuracy to the gold standard auscultatory method, and is significantly better than the requirements of the current international standard for blood pressure devices. Our results provide scientific evidence for the effectiveness of our technique, and demonstrate significant clinically important improvements. We anticipate that our technique can be automated easily and economically. We acknowledge that this early study is an initial manual evaluation, but expect this new technique to be an automated universal solution for true blood pressure measurement, and a vital step change in an important clinical measurement in healthcare of the worldwide population.
Author(s): Murray A, Zheng D, Griffiths CJ, Liu C, Graham DJ, Neasham J, Cossor AJ
Publication type: Article
Publication status: Published
Journal: Scientific Reports
Year: 2025
Volume: 15
Online publication date: 31/01/2025
Acceptance date: 22/01/2025
Date deposited: 24/02/2025
ISSN (electronic): 2045-2322
Publisher: Springer Nature
URL: https://doi.org/10.1038/s41598-025-87855-2
DOI: 10.1038/s41598-025-87855-2
Data Access Statement: The data that support the findings of this study are available in: https://doi.org/10.25405/data.ncl.27263892.
PubMed id: 39890950
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