Robust computation of pulse pressure variations
•A method for robust, fast computation of arterial pulse pressure variations, is presented.•The method is based on the Lomb–Scargle periodogram and least squares regression.•The algorithm is particularly suitable for closed-loop control, and other time-critical applications.•A porcine dataset with s...
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| Published in | Biomedical signal processing and control Vol. 39; pp. 197 - 203 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.01.2018
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| Subjects | |
| Online Access | Get full text |
| ISSN | 1746-8094 1746-8108 1746-8108 |
| DOI | 10.1016/j.bspc.2017.07.021 |
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| Abstract | •A method for robust, fast computation of arterial pulse pressure variations, is presented.•The method is based on the Lomb–Scargle periodogram and least squares regression.•The algorithm is particularly suitable for closed-loop control, and other time-critical applications.•A porcine dataset with sudden hemodynamic changes is used to demonstrate feasibility.
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. |
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| AbstractList | •A method for robust, fast computation of arterial pulse pressure variations, is presented.•The method is based on the Lomb–Scargle periodogram and least squares regression.•The algorithm is particularly suitable for closed-loop control, and other time-critical applications.•A porcine dataset with sudden hemodynamic changes is used to demonstrate feasibility.
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. 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 |
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| Cites_doi | 10.1213/ANE.0b013e3182937d61 10.1016/S0002-9149(99)80086-1 10.1007/BF00648343 10.3121/cmr.2009.850 10.1109/TBME.2004.834295 10.1007/s10877-010-9229-1 10.1088/0967-3334/37/4/610 10.1213/ANE.0b013e318230e9e0 10.1213/ane.0b013e318167ab1f 10.1097/00000542-200508000-00026 |
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| Keywords | Nonuniform sampling Frequency estimation Pulse pressure variation Arterial blood pressure |
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| SubjectTerms | Arterial blood pressure Control Engineering Electrical Engineering, Electronic Engineering, Information Engineering Elektroteknik och elektronik Engineering and Technology Frequency estimation Nonuniform sampling Pulse pressure variation Reglerteknik Teknik |
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