Global sensitivity analysis of a wave propagation model for arm arteries
| Autor: | van de Fn Frans Vosse, Emh Mariëlle Bosboom, Apg Arnold Hoeks, Cad Carole Leguy, Asz Belloum |
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| Přispěvatelé: | Biomedische Technologie, RS: CARIM School for Cardiovascular Diseases, Cardiovascular Biomechanics, Computational Science Lab (IVI, FNWI), System and Network Engineering (IVI, FNWI) |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Accuracy and precision
Patient-specific modeling Blood Volume Wave propagation Flow (psychology) Biomedical Engineering Biophysics Monotonic function Blood Pressure Blood flow Arteries Spearman's rank correlation coefficient Models Biological Wave propagation model Arterial stiffness Global sensitivity analysis Statistics Arm Computer Graphics Waveform Humans Sensitivity (control systems) Monte Carlo Method Monte-Carlo study Mathematics |
| Zdroj: | Medical Engineering & Physics, 33(8), 1008-1016. ELSEVIER SCI LTD Medical Engineering & Physics, 33(8), 1008-1016. Elsevier |
| ISSN: | 1350-4533 |
| Popis: | Wave propagation models of blood flow and blood pressure in arteries play an important role in cardiovascular research. For application of these models in patient-specific simulations a number of model parameters, that are inherently subject to uncertainties, are required. The goal of this study is to identify with a global sensitivity analysis the model parameters that influence the output the most. The improvement of the measurement accuracy of these parameters has largest consequences for the output statistics. A patient specific model is set up for the major arteries of the arm. In a Monte-Carlo study, 10 model parameters and the input blood volume flow (BVF) waveform are varied randomly within their uncertainty ranges over 3000 runs. The sensitivity in the output for each system parameter was evaluated with the linear Pearson and ranked Spearman correlation coefficients. The results show that model parameter and input BVF uncertainties induce large variations in output variables and that most output variables are significantly influenced by more than one system parameter. Overall, the Young's modulus appears to have the largest influence and arterial length the smallest. Only small differences were obtained between Spearman's and Pearson's tests, suggesting that a high monotonic association given by Spearman's test is associated with a high linear corelation between the inputs and output parameters given by Pearson's test. |
| Databáze: | OpenAIRE |
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