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Robust computation of pulse pressure variations

Soltesz, Kristian LU (2017) In Biomedical Signal Processing and Control 39. p.197-203
Abstract
Evidence of arterial pulse pressure variations caused by cardio-pulmonary interactions, and their connection to volume status via the Frank–Starling relationship, are well documented in the literature. Computation of pulse pressure variations from arterial pressure measurements is complicated by the fact that systolic and diastolic peaks are not evenly spaced in time. A robust, structurally uncomplicated, and computationally cheap algorithm, specifically addressing this fact, is presented. The algorithm is based on the Lomb–Scargle spectral density estimator, and ordinary least squares fitting. It is introduced using illustrative examples, and successfully demonstrated on a challenging porcine data set.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
epub
subject
keywords
Pulse pressure variation, Arterial blood pressure, Nonuniform sampling, Frequency estimation
in
Biomedical Signal Processing and Control
volume
39
pages
197 - 203
publisher
Elsevier
ISSN
1746-8094
DOI
10.1016/j.bspc.2017.07.021
language
English
LU publication?
yes
id
f5b25306-d012-43f3-9c17-662f8f655e5e
date added to LUP
2017-08-04 06:32:00
date last changed
2017-08-23 11:46:33
@article{f5b25306-d012-43f3-9c17-662f8f655e5e,
  abstract     = {Evidence of arterial pulse pressure variations caused by cardio-pulmonary interactions, and their connection to volume status via the Frank–Starling relationship, are well documented in the literature. Computation of pulse pressure variations from arterial pressure measurements is complicated by the fact that systolic and diastolic peaks are not evenly spaced in time. A robust, structurally uncomplicated, and computationally cheap algorithm, specifically addressing this fact, is presented. The algorithm is based on the Lomb–Scargle spectral density estimator, and ordinary least squares fitting. It is introduced using illustrative examples, and successfully demonstrated on a challenging porcine data set.},
  author       = {Soltesz, Kristian},
  issn         = {1746-8094},
  keyword      = { Pulse pressure variation,Arterial blood pressure,Nonuniform sampling, Frequency estimation},
  language     = {eng},
  pages        = {197--203},
  publisher    = {Elsevier},
  series       = {Biomedical Signal Processing and Control},
  title        = {Robust computation of pulse pressure variations},
  url          = {http://dx.doi.org/10.1016/j.bspc.2017.07.021},
  volume       = {39},
  year         = {2017},
}