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Models define a simplification of reality, which help to understand function. The arterial system has been modeled in many ways: lumped models, tube models and anatomically based distributed models. In this work, arterial segments were modeled as thin nonlinear elastic tubes filled with an incompressible fluid, whose governing dynamics were denoted by the Korteweg and DeVries equation. In order characterize the pressure pulse propagation, a discrete multi-segmented conduit was proposed. Arterial wall mechanical parameters were obtained from existing literature and assigned to each individual segment. The numerical model was developed starting in the aortic arch, and ending at the femoral artery. The main idea of this article was to perform a computational simulation of pressure wave propagation, considered as a solitons combination, along several segments of the arterial tree.

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Introduction: This study investigates a gait research protocol to assess the impact of a walker model with forearm supports on the kinematic parameters of the lower limb during locomotion. Methods: Thirteen healthy participants without any history of gait dysfunction were enrolled in the experimental procedure. Spatiotemporal and kinematic gait parameters were calculated by using wireless inertial sensors and analyzed with Principal Component Analysis (PCA). The PCA method was selected to achieve dimension reduction and evaluate the main effects in gait performance during walker-assisted gait. Additionally, the interaction among the variables included in each Principal Component (PCs) derived from PCA is exposed to expand the understanding of the main differences between walker-assisted and unassisted gait conditions. Results: The results of the statistical analysis identifi ed four PCs that retained 65% of the data variability. These components were associated with spatiotemporal information, knee joint, hip joint and ankle joint motion, respectively. Conclusion: Assisted gait by a walker model with forearm supports was characterized by slower gait, shorter steps, larger double support phase and lower body vertical acceleration when compared with normal, unassisted walking.

Arterial pressure waves have been described in one dimension using several approaches, such as lumped (Windkessel) or distributed (using Navier-Stokes equations) models. An alternative approach consists of modeling blood pressure waves using a Korteweg-de Vries (KdV) equation and representing pressure waves as combinations of solitons. This model captures many key features of wave propagation in the systemic network and, in particular, pulse pressure amplification (PPA), which is a mechanical biomarker of cardiovascular risk. The main objective of this work is to compare the propagation dynamics described by a KdV equation in a human-like arterial tree using acquired pressure waves. Furthermore, we analyzed the ability of our model to reproduce induced elastic changes in PPA due to different pathological conditions. To this end, numerical simulations were performed using acquired central pressure signals from different subject groups (young, adults, and hypertensive) as input and then comparing the output of the model with measured radial artery pressure waveforms. Pathological conditions were modeled as changes in arterial elasticity (E). Numerical results showed that the model was able to propagate acquired pressure waveforms and to reproduce PPA variations as a consequence of elastic changes. Calculated elasticity for each group was in accordance with the existing literature.

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Previous experiences in animals showed a different behavior between the variability of pressure, arterial diameter and elasticity when they were registered for a couple of hours. To better understand arterial mechanics variability, we propose to measure simultaneously aortic pressure and diameter during 24 hours in a sheep. For that purpose, we developed a portable prototype device. It allows continuously recording physiological signals throughout the day and storing them in a solid state memory for later analysis. Pulse wave velocity and Peterson modulus were assessed beat-to-beat as arterial stiffness indexes. We identified 53,762 heart beats during 24 hours that were separated into 2 groups: below or above median mean pressure (71 mmHg). Mean diameter, pulse wave velocity and Peterson modulus increased for higher pressure values (p<0.05) whereas heart rate slowed down (p<0.05). Pressure-diameter loops were successfully recreated all along the experience. This new methodology sets the basis for further experiences involving the estimation of 24 hours arterial mechanics variability.