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### Research Papers

J Biomech Eng. 2017;140(1):011001-011001-11. doi:10.1115/1.4037791.

Stair ascent is an activity of daily living and necessary for maintaining independence in community environments. One challenge to improving an individual's ability to ascend stairs is a limited understanding of how lower-limb muscles work in synergy to perform stair ascent. Through dynamic coupling, muscles can perform multiple functions and require contributions from other muscles to perform a task successfully. The purpose of this study was to identify the functional roles of individual muscles during stair ascent and the mechanisms by which muscles work together to perform specific subtasks. A three-dimensional (3D) muscle-actuated simulation of stair ascent was generated to identify individual muscle contributions to the biomechanical subtasks of vertical propulsion, anteroposterior (AP) braking and propulsion, mediolateral control and leg swing. The vasti and plantarflexors were the primary contributors to vertical propulsion during the first and second halves of stance, respectively, while gluteus maximus and hamstrings were the primary contributors to forward propulsion during the first and second halves of stance, respectively. The anterior and posterior components of gluteus medius were the primary contributors to medial control, while vasti and hamstrings were the primary contributors to lateral control during the first and second halves of stance, respectively. To control leg swing, antagonistic muscles spanning the hip, knee, and ankle joints distributed power from the leg to the remaining body segments. These results compliment previous studies analyzing stair ascent and provide further rationale for developing targeted rehabilitation strategies to address patient-specific deficits in stair ascent.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2017;140(1):011002-011002-14. doi:10.1115/1.4037857.

Computational fluid dynamics (CFD) provides a noninvasive method to functionally assess aortic hemodynamics. The thoracic aorta has an anatomically complex inlet comprising of the aortic valve and root, which is highly prone to different morphologies and pathologies. We investigated the effect of using patient-specific (PS) inflow velocity profiles compared to idealized profiles based on the patient's flow waveform. A healthy 31 yo with a normally functioning tricuspid aortic valve (subject A), and a 52 yo with a bicuspid aortic valve (BAV), aortic valvular stenosis, and dilated ascending aorta (subject B) were studied. Subjects underwent MR angiography to image and reconstruct three-dimensional (3D) geometric models of the thoracic aorta. Flow-magnetic resonance imaging (MRI) was acquired above the aortic valve and used to extract the patient-specific velocity profiles. Subject B's eccentric asymmetrical inflow profile led to highly complex velocity patterns, which were not replicated by the idealized velocity profiles. Despite having identical flow rates, the idealized inflow profiles displayed significantly different peak and radial velocities. Subject A's results showed some similarity between PS and parabolic inflow profiles; however, other parameters such as Flowasymmetry were significantly different. Idealized inflow velocity profiles significantly alter velocity patterns and produce inaccurate hemodynamic assessments in the thoracic aorta. The complex structure of the aortic valve and its predisposition to pathological change means the inflow into the thoracic aorta can be highly variable. CFD analysis of the thoracic aorta needs to utilize fully PS inflow boundary conditions in order to produce truly meaningful results.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2017;140(1):011003-011003-8. doi:10.1115/1.4037854.

Pedestrians represent one of the most vulnerable road users and comprise nearly 22% the road crash-related fatalities in the world. Therefore, protection of pedestrians in car-to-pedestrian collisions (CPC) has recently generated increased attention with regulations involving three subsystem tests. The development of a finite element (FE) pedestrian model could provide a complementary component that characterizes the whole-body response of vehicle–pedestrian interactions and assesses the pedestrian injuries. The main goal of this study was to develop and to validate a simplified full body FE model corresponding to a 50th male pedestrian in standing posture (M50-PS). The FE model mesh and defined material properties are based on a 50th percentile male occupant model. The lower limb-pelvis and lumbar spine regions of the human model were validated against the postmortem human surrogate (PMHS) test data recorded in four-point lateral knee bending tests, pelvic\abdomen\shoulder\thoracic impact tests, and lumbar spine bending tests. Then, a pedestrian-to-vehicle impact simulation was performed using the whole pedestrian model, and the results were compared to corresponding PMHS tests. Overall, the simulation results showed that lower leg response is mostly within the boundaries of PMHS corridors. In addition, the model shows the capability to predict the most common lower extremity injuries observed in pedestrian accidents. Generally, the validated pedestrian model may be used by safety researchers in the design of front ends of new vehicles in order to increase pedestrian protection.

Commentary by Dr. Valentin Fuster
J Biomech Eng. 2017;140(1):011004-011004-12. doi:10.1115/1.4037916.

This paper is concerned with proposing a suitable structurally motivated strain energy function, denoted by $Weelastin network$, for modeling the deformation of the elastin network within the aortic valve (AV) tissue. The AV elastin network is the main noncollagenous load-bearing component of the valve matrix, and therefore, in the context of continuum-based modeling of the AV, the $Weelastin network$ strain energy function would essentially serve to model the contribution of the “isotropic matrix.” To date, such a function has mainly been considered as either a generic neo-Hookean term or a general exponential function. In this paper, we take advantage of the established structural analogy between the network of elastin chains and the freely jointed molecular chain networks to customize a structurally motivated $Weelastin network$ function on this basis. The ensuing stress–strain (force-stretch) relationships are thus derived and fitted to the experimental data points reported by (Vesely, 1998, “The Role of Elastin in Aortic Valve Mechanics,” J. Biomech., 31, pp. 115–123) for intact AV elastin network specimens under uniaxial tension. The fitting results are then compared with those of the neo-Hookean and the general exponential models, as the frequently used models in the literature, as well as the “Arruda–Boyce” model as the gold standard of the network chain models. It is shown that our proposed $Weelastin network$ function, together with the general exponential and the Arruda–Boyce models provide excellent fits to the data, with R2 values in excess of 0.98, while the neo-Hookean function is entirely inadequate for modeling the AV elastin network. However, the general exponential function may not be amenable to rigorous interpretation, as there is no structural meaning attached to the model. It is also shown that the parameters estimated by the Arruda–Boyce model are not mathematically and structurally valid, despite providing very good fits. We thus conclude that our proposed strain energy function $Weelastin network$ is the preferred choice for modeling the behavior of the AV elastin network and thereby the isotropic matrix. This function may therefore be superimposed onto that of the anisotropic collagen fibers family in order to develop a structurally motivated continuum-based model for the AV.

Commentary by Dr. Valentin Fuster