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Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model
BACKGROUND: The oscillometric method of measuring blood pressure with an automated cuff yields valid estimates of mean pressure but questionable estimates of systolic and diastolic pressures. Existing algorithms are sensitive to differences in pulse pressure and artery stiffness. Some are closely gu...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2012
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3541069/ https://www.ncbi.nlm.nih.gov/pubmed/22913792 http://dx.doi.org/10.1186/1475-925X-11-56 |
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author | Babbs, Charles F |
author_facet | Babbs, Charles F |
author_sort | Babbs, Charles F |
collection | PubMed |
description | BACKGROUND: The oscillometric method of measuring blood pressure with an automated cuff yields valid estimates of mean pressure but questionable estimates of systolic and diastolic pressures. Existing algorithms are sensitive to differences in pulse pressure and artery stiffness. Some are closely guarded trade secrets. Accurate extraction of systolic and diastolic pressures from the envelope of cuff pressure oscillations remains an open problem in biomedical engineering. METHODS: A new analysis of relevant anatomy, physiology and physics reveals the mechanisms underlying the production of cuff pressure oscillations as well as a way to extract systolic and diastolic pressures from the envelope of oscillations in any individual subject. Stiffness characteristics of the compressed artery segment can be extracted from the envelope shape to create an individualized mathematical model. The model is tested with a matrix of possible systolic and diastolic pressure values, and the minimum least squares difference between observed and predicted envelope functions indicates the best fit choices of systolic and diastolic pressure within the test matrix. RESULTS: The model reproduces realistic cuff pressure oscillations. The regression procedure extracts systolic and diastolic pressures accurately in the face of varying pulse pressure and arterial stiffness. The root mean squared error in extracted systolic and diastolic pressures over a range of challenging test scenarios is 0.3 mmHg. CONCLUSIONS: A new algorithm based on physics and physiology allows accurate extraction of systolic and diastolic pressures from cuff pressure oscillations in a way that can be validated, criticized, and updated in the public domain. |
format | Online Article Text |
id | pubmed-3541069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35410692013-01-11 Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model Babbs, Charles F Biomed Eng Online Research BACKGROUND: The oscillometric method of measuring blood pressure with an automated cuff yields valid estimates of mean pressure but questionable estimates of systolic and diastolic pressures. Existing algorithms are sensitive to differences in pulse pressure and artery stiffness. Some are closely guarded trade secrets. Accurate extraction of systolic and diastolic pressures from the envelope of cuff pressure oscillations remains an open problem in biomedical engineering. METHODS: A new analysis of relevant anatomy, physiology and physics reveals the mechanisms underlying the production of cuff pressure oscillations as well as a way to extract systolic and diastolic pressures from the envelope of oscillations in any individual subject. Stiffness characteristics of the compressed artery segment can be extracted from the envelope shape to create an individualized mathematical model. The model is tested with a matrix of possible systolic and diastolic pressure values, and the minimum least squares difference between observed and predicted envelope functions indicates the best fit choices of systolic and diastolic pressure within the test matrix. RESULTS: The model reproduces realistic cuff pressure oscillations. The regression procedure extracts systolic and diastolic pressures accurately in the face of varying pulse pressure and arterial stiffness. The root mean squared error in extracted systolic and diastolic pressures over a range of challenging test scenarios is 0.3 mmHg. CONCLUSIONS: A new algorithm based on physics and physiology allows accurate extraction of systolic and diastolic pressures from cuff pressure oscillations in a way that can be validated, criticized, and updated in the public domain. BioMed Central 2012-08-22 /pmc/articles/PMC3541069/ /pubmed/22913792 http://dx.doi.org/10.1186/1475-925X-11-56 Text en Copyright ©2012 Babbs; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Babbs, Charles F Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model |
title | Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model |
title_full | Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model |
title_fullStr | Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model |
title_full_unstemmed | Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model |
title_short | Oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model |
title_sort | oscillometric measurement of systolic and diastolic blood pressures validated in a physiologic mathematical model |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3541069/ https://www.ncbi.nlm.nih.gov/pubmed/22913792 http://dx.doi.org/10.1186/1475-925X-11-56 |
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