ArticleBiomedical engineering online2012
Algorithmic processing of pressure waveforms to facilitate estimation of cardiac elastance.
Article in Biomedical engineering online, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- First-phase ejection fraction and ventricular-arterial coupling across the lifespan: An in silico analysis.Physiological reports · 2026Article
- Artifact management methodologies for arterial blood pressure signals: A systematic scoping review of human and animal literature.Physiological reports · 2025Article
- An algorithm to detect dicrotic notch in arterial blood pressure and photoplethysmography waveforms using the iterative envelope mean method.Computer methods and programs in biomedicine · 2024Article
- Accurate end systole detection in dicrotic notch-less arterial pressure waveforms.Journal of clinical monitoring and computing · 2021Article
- Minimally invasive, patient specific, beat-by-beat estimation of left ventricular time varying elastance.Biomedical engineering online · 2017Article
- Minimally invasive estimation of ventricular dead space volume through use of Frank-Starling curves.PloS one · 2017Article
- Simulation of left atrial function using a multi-scale model of the cardiovascular system.PloS one · 2014Article
- Evaluation of a model-based hemodynamic monitoring method in a porcine study of septic shock.Computational and mathematical methods in medicine · 2013Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCardiac elastances are highly invasive to measure directly, but are clinically useful due to the amount of information embedded in them. Information about the cardiac elastance, which can be used to estimate it, can be found in the downstream pressure waveforms of the aortic pressure (P(ao)) and the pulmonary artery (P(pa)). However these pressure waveforms are typically noisy and biased, and require processing in order to locate the specific information required for cardiac elastance estimations. This paper presents the method to algorithmically process the pressure waveforms.
methodsA shear transform is developed in order to help locate information in the pressure waveforms. This transform turns difficult to locate corners into easy to locate maximum or minimum points as well as providing error correction.
resultsThe method located all points on 87 out of 88 waveforms for Ppa, to within the sampling frequency. For Pao, out of 616 total points, 605 were found within 1%, 5 within 5%, 4 within 10% and 2 within 20%.
conclusionsThe presented method provides a robust, accurate and dysfunction-independent way to locate points on the aortic and pulmonary artery pressure waveforms, allowing the non-invasive estimation of the left and right cardiac elastance.
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