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Current state of in-vitro methods in Cardiovascular biomechanics
In-vitro mock circulation loops offer the advantage of directly testing medical devices and investigating physical phenomena that are not fully captured by simplified computational models. However, the ability of mock loops to model the dynamic closed-loop response of the heart remains limited, the challenges including difficulties in achieving realistic end-systolic and end-diastolic pressure-volume characteristics as well as the preload sensitivities of the heart chambers. Despite significant advances in computational and in-vitro methods for modeling different aspects of the cardiovascular system, the ability to capitalize these advances in a unified high-fidelity framework is still beyond reach.

The hardware-in-the-loop approach
The hardware-in-the-loop (HIL) approach combines an in-vitro experiment with a numerical simulation of physiology, possessing the potential to capitalize on the strengths of both in-vitro and numerical platforms in a hybrid model. Pillon et al. first suggested the HIL approach for cardiovascular modeling in 1992. Later, Hanson et al. constructed an HIL model containing a ventricle-mimicking actuator setup controlled based on the desired pressures calculated in real-time from a simple numerical lumped-parameter simulation.

The Physiology Simulation COuPled Experiment (PSCOPE)
the Physiology Simulation COuPled Experiment (PSCOPE) framework addresses the aforementioned limitations in previous cardiovascular HIL models. This framework utilizes an iterative method to mitigate the physical limitations in the hydraulic experiment such as signal noises and delays; furthermore, it allows for the direct evaluation of the solution quality, guaranteeing the convergence of the solution below a known residual. The PSCOPE’s main strength is the ability to experimentally investigate a scenario that is challenging for numerical simulations (i.e. fluid-structure interactions), and fully couple the experimental results with a physiology simulation (which is challenging to produce experimentally).