Experiment for validation of fluid-structure interaction models and algorithms.

In this paper a fluid-structure interaction (FSI) experiment is presented. The aim of this experiment is to provide a challenging yet easy-to-setup FSI test case that addresses the need for rigorous testing of FSI algorithms and modeling frameworks. Steady-state and periodic steady-state test cases with constant and periodic inflow were established. Focus of the experiment is on biomedical engineering applications with flow being in the laminar regime with Reynolds numbers 1283 and 651. Flow and solid domains were defined using computer-aided design (CAD) tools. The experimental design aimed at providing a straightforward boundary condition definition. Material parameters and mechanical response of a moderately viscous Newtonian fluid and a nonlinear incompressible solid were experimentally determined. A comprehensive data set was acquired by using magnetic resonance imaging to record the interaction between the fluid and the solid, quantifying flow and solid motion.

A technical assessment of pulse wave velocity algorithms applied to non-invasive arterial waveforms.

Non-invasive assessment of arterial stiffness through pulse wave velocity (PWV) analysis is becoming common clinical practice. However, the effects of measurement noise, temporal resolution and similarity of the two waveforms used for PWV calculation upon accuracy and variability are unknown. We studied these effects upon PWV estimates given by foot-to-foot, least squared difference, and cross-correlation algorithms. We assessed accuracy using numerically generated blood pressure and flow waveforms for which the theoretical PWV was known to compare with the algorithm estimates. We assessed variability using clinical measurements in 28 human subjects. Wave shape similarity was quantified using a cross correlation-coefficient (CCCoefficient), which decreases with increasing distance between waveform measurements sites. Based on our results, we propose the following criteria to identify the most accurate and least variable algorithm given the noise, resolution and CCCoefficient of the measured waveforms. (1) Use foot-to-foot when the noise-to-signal ratio ≤10%, and/or temporal resolution ≥100 Hz. Otherwise (2) use a least squares differencing method applied to the systolic upstroke.