<p> Though many who walk along roadside cambers and hill edges may have an interest in making their travels sure and effective, those most concerned may be soldiers in the infantry. They need to be injury free and have as much energy as possible when they march into battle.</p><p> Walking on uneven ground without being injured by falling down (particularly with a heavy backpack) is generally accomplished by maintaining stability. This present study was conducted to determine an individual&rsquo;s most stable position (using a stability formula which compares dynamic center of mass with center of pressure) when wearing a backpack under differing load positions - low back, middle back or high back &ndash; and differing walking angles: level, as well as along a cross-sloped surface.</p><p> Furthermore, this study investigated the stability of persons walking along a cross-slope without a load.</p><p> Finally, this study attempted to determine which combination of backpack load location and slope tilt best conserved metabolic energy.</p><p> To carry out this backpack stability research, a group of 15 participants were asked to walk along an indoor track under the varying conditions mentioned (i.e., low to high backpack load positions and level to 10 degree tilted cross-slopes). The trials of their walks were performed randomly. The participants were recorded in a motion capture system and force plates documented their stepping times and locations.</p><p> Again, the same 15 participants walked along the track under the same conditions, but without the loads to determine the effect of different cross-slope angles on their stability.</p><p> Lastly, the same participants walked the track under the various conditions wearing portable oxygen sensors to analyze their energy expenditure. </p><p> The results of these limited tests indicate no significant stability differences between 0, 5 or 10 degree angles in cross-slope walking loaded or unloaded. Nor was any significant stability differences noted between the various load locations of the backpacks. Nor was there a significant energy difference between the conditions.</p>

<p> Image-based modeling and simulation has become an important analytic and predictive tool for patient-specific medical applications, including large-scale in silico patient studies, optimized medical device design, and custom surgical guides and implants via additive manufacturing. The pipeline for patient-specific modeling and simulation is: image acquisition, image segmentation, surface generation, mesh generation, physics-based modeling and simulation, and clinical application. This research establishes a semi-automatic workflow for these steps, which includes a novel image-based meshing tool <i> Shabaka.</i> The toolchain is demonstrated by modeling the mechanics of a beating human heart based on magnetic resonance imaging (MRI) data. </p><p> The Shabaka workflow ensures robust execution of each step of the pipeline. Medical images are processed and segmented using thresholding, region-growing, and manual techniques. Watertight surface meshes are extracted from image masks using a novel Voronoi-based algorithm. For scientific computing purposes, surface meshes are supplied either to tetrahedral meshing routines for conventional finite element approaches, or to a robust polyhedral mesh generation tool for a novel polyhedral finite element approach. A polyhedral finite element code is explored, that retains most of the favorable properties of conventional finite element methods, while reducing the system size by up to an order of magnitude compared to conventional techniques for the same input surface. </p><p> In conjunction with a cardiac simulation code, the workflow is utilized to model finite-deformation cardiac mechanics. A quadratic tetrahedral mesh is generated from MRI data of the human heart ventricles. The constitutive law is comprised of an incompressible orthotropic hyperelastic stress response for the myocardium, plus an electrical activation-dependent active stress for the muscle fibers. Muscle fiber orientations are generated using a rule-based approach. Electrical activation times are read from a coupled electrophysiology code. A lumped circulatory model is used to impose time-dependent ventricular volume constraints. Simulation results are presented. The same mechanics are also implemented for the polyhedral finite element mesh, and preliminary verification results are presented. </p><p> The toolchain used in performing image-based cardiac mechanics simulations makes important improvements to the speed and robustness of image-based modeling techniques. As efforts continue to mature, so too does the promise for simulation to impact and improve healthcare.</p><p>

<p> Due to the rising number of stroke victims, the demand for reduced cost and effective treatments for recovering patients increases. To offset this need, previous studies introduced robotic assistance to rehabilitation treatments. This study investigates how much robotic assistance affects the patient by analyzing the differences in muscle activity. From the collected experimental data of ten healthy subjects, the results initially inferred that the end position of the reaching movements affected the muscle activity in biceps and triceps only, while the deltoid was not affected. However, after applying ANOVA one-way analyses, robotic assistance was found to have an impact on the deltoid, triceps, and bicep muscles when subjects moved their hands along an indirect trajectory towards nine targets. Meanwhile, only the bicep was affected when subjects moved their arm in a direct path with assistance. Lastly, the impact that the trajectory of the hand movement had on muscle activity was undetermined.</p><p>

This research details a procedure for the systematic design of custom foot orthotics based on simulation models and their validation through experimental and clinical studies. These models may ultimately be able to replace the use of empirical tables for designing custom foot orthotics and enable optimal design thicknesses based on the body weight and activities of end-users. Similarly, they may facilitate effortless simulation of various orthotic and loading conditions, changes in material properties, and foot deformities by simply altering model parameters. Finally, these models and the corresponding results may also form the basis for subsequent design of a new generation of custom foot orthotics. Two studies were carried out, the first involving a methodical approach to development of engineering analysis models using the FEA technique. Subsequently, for model verification and validation purposes, detailed investigations were executed through experimental and clinical studies. The results were within 15% difference for the experimental studies and 26% for the clinical studies, and most of the probability values were greater than α = 0.05 accepting our null hypothesis that the FEA model data versus clinical trial data are not significantly different. The accuracy of the FEA model was further enhanced when the uniform loading condition was replaced with a more realistic pressure distribution of 70% of the weight in the heel and the rest in the front portion of the orthotic. This alteration brought the values down to within 22% difference of the clinical studies, with the P-values once again showed no significant difference between the modified FEA model and the clinical studies for most of the scenarios. The second study dealt with the development of surrogate models from FEA results, which can then be used in lieu of the computationally intensive FEA-based analysis models in the engineering design of CFO. Four techniques were studied, including the second-order polynomial response surface, Kriging, non-parametric regression and neural networking. All four techniques were found to be computationally efficient with an average of over 200% savings in time, and the Kriging technique was found to be the most accurate with an average % difference of below 0.30 for each of the loading conditions (light, medium and heavy). The two studies clearly indicate that engineering modeling, analysis and design using FEA techniques coupled with surrogate modeling methods offer a consistent, accurate and reliable alternative to empirical clinical studies. This powerful alternative simulation-based design framework can be a viable and valuable tool in the custom design of orthotics based on an individual’s unique needs and foot characteristics. With these capabilities, the CFO prescriber would be able to design and develop the best-fit CFO with the optimal design characteristics for each individual customer without relying upon extensive and expensive trial and error ad hoc approaches. Such a model could also facilitate the inspection of robustness of resulting designs, as well as enable visual inspection of the impact of even small changes on the overall performance of the CFO. By adding the results from these studies to the CFO community, the prescription process may become more efficient and therefore more affordable and accessible to all populations and groups.

<p> Artificial neural networks (ANNs) have been used successfully in various practical problems. Though extensive improvements on different types of ANNs have been made to improve their performance, each ANN design still experiences its own limitations. The existing digital human models are mature enough to provide accurate and useful results for different tasks and scenarios under various conditions. There is, however, a critical need for these models to run in real time, especially those with large-scale problems like motion prediction which can be computationally demanding. For even small changes to the task conditions, the motion simulation needs to run for a relatively long time (minutes to tens of minutes). Thus, there can be a limited number of training cases due to the computational time and cost associated with collecting training data. In addition, the motion problem is relatively large with respect to the number of outputs, where there are hundreds of outputs (between 500-700 outputs) to predict for a single problem. Therefore, the aforementioned necessities in motion problems lead to the use of tools like the ANN in this work. </p><p> This work introduces new algorithms for the design of the radial-basis network (RBN) for problems with minimal available training data. The new RBN design incorporates new training stages with approaches to facilitate proper setting of necessary network parameters. The use of training algorithms with minimal heuristics allows the new RBN design to produce results with quality that none of the competing methods have achieved. The new RBN design, called Opt_RBN, is tested on experimental and practical problems, and the results outperform those produced from standard regression and ANN models. In general, the Opt_RBN shows stable and robust performance for a given set of training cases. </p><p> When the Opt_RBN is applied on the large-scale motion prediction application, the network experiences a CPU memory issue when performing the optimization step in the training process. Therefore, new algorithms are introduced to modify some steps of the new Opt_RBN training process to address the memory issue. The modified steps should only be used for large-scale applications similar to the motion problem. The new RBN design proposes an ANN that is capable of improved learning without needing more training data. Although the new design is driven by its use with motion prediction problems, the consequent ANN design can be used with a broad range of large-scale problems in various engineering and industrial fields that experience delay issues when running computational tools that require a massive number of procedures and a great deal of CPU memory. </p><p> The results of evaluating the modified Opt_RBN design on two motion problems are promising, with relatively small errors obtained when predicting approximately 500-700 outputs. In addition, new methods for constraint implementation within the new RBN design are introduced. Moreover, the new RBN design and its associated parameters are used as a tool for simulated task analysis. This work initiates the idea that output weights (<i>W</i>) can be used to determine the most critical basis functions that cause the greatest reduction in the network test error. Then, the critical basis functions can specify the most significant training cases that are responsible for the proper performance achieved by the network. The inputs with the most change in value can be extracted from the basis function centers (<i>U</i>) in order to determine the dominant inputs. The outputs with the most change in value and their corresponding key body degrees-of-freedom for a motion task can also be specified using the training cases that are used to create the network's basis functions. </p>

<p> In this study a theoretical model is proposed for the buckling of a vein subjected to torsion, internal pressure, and axial tension using a formation of elasticity theory for shells. The vein is assumed to be an anisotropic hyperelastic cylindrical shell which obeys the Fung constitutive model. </p><p> The approach uses finite deformation theory for thick-walled blood vessels to characterize the vessel dilation in the pre-buckling state. The pre-buckling state is identified by its midpoint and then perturbed by a displacement vector field dependent on the circumferential and axial directions to define the buckled state. The buckling equations of static equilibrium are derived using the nominal stress measure and traction boundary conditions are applied. A side result is shown proving the existence of a moment traction although typically taken to be zero for torsional problems. Perturbational displacements raised to the power of two or greater are assumed negligible thereby linearizing the coupled partial differential equations of equilibrium. The coupled equations are solved by supposing first-order and single Fourier term trigonometric forms for the displacement field components. </p><p> The model and the assumptions used are validated by experimental data for five human great saphenous vein (GSV) samples taken from a previous study. The theoretical model is unstable but using an eigenvalue compatibility condition as a selection method yields strong quantitative results for three out of five GSVs in the entire tested pressure range (6-100 mmHg). The other two sampless showed excessive stiffening upon loading and may indicate limitations of the model although quantitative predictions were still moderately accurate. The strongest results are in the 6-20 mmHg pressure range where all vessels matched well with predicted values. In general the model showed increased error as pressure increased hinting that effects of vessel stiffening are poorly predicted. The eigenmodes predicted were consistently inaccurate indicating the assumptions used in this solution method are inadequate to characterize the buckling modes of a nonlinear material. It may suggest that nonlinear buckling conformation is determined by nonlinear perturbation terms.</p><p>

<p> Human upper limb motion analysis with sensing by way of consumer-off-the-shelf (COTS) devices presents a rich set of scientific, technological, and practical implementation challenges. The need for such systems is motivated by the popular trend toward the development of home based rehabilitative motor therapy systems in which patients perform therapy alone while a technological solution connects the patient to a therapist by performing data acquisition, analysis, and the reporting of evaluation results remotely. The choice to use COTS devices mirrors the reasons why they have become universally accepted in society in recent times. They are inexpensive, easy to use, manufactured to be deployable at large scale, and satisfactorily performant for their intended applications. These claims for the use of COTS devices also resound with requirements that make them suitable for use as low-cost equipment in academic research.</p><p> The focus of this work is on the development of a proof of concept human upper limb motion capture system using Myo and Sphero. The end-to-end development of the motion capture system begins with developing the software that is required to interact with these devices in MATLAB. Each of Myo and Sphero receive a fully-featured device interface that&rsquo;s easy to use in native MATLAB m-code. Then, a theoretical framework for upper limb motion capture and analysis is developed in which the devices&rsquo; inertial measurement unit data is used to determine the pose of a subject&rsquo;s upper limb. The framework provides faculties for model calibration, registration of the model with a virtual world, and analysis methods that enable successful validation of the model&rsquo;s correctness as well as evaluation of its accuracy as shown by the concrete example in this work.</p>

Tooth cusp radius of curvature (RoC) has been hypothesized to play an important role in food item breakdown, but has remained largely unstudied due to difficulties in measuring and modeling RoC in multicusped teeth. We tested these hypotheses using a parametric model of a four cusped, maxillary, bunodont molar in conjunction with finite element analysis. When our data failed to support existing hypotheses, we put forth and tested the Complex Cusp Hypothesis which states that, during brittle food items breakdown, an optimally shaped molar would be maximizing stresses in the food item while minimizing stresses in the enamel. After gaining support for this hypothesis, we tested the effects of relative food item size on optimal molar morphology and found that the optimal set of RoCs changed as relative food item size changed. However, all optimal morphologies were similar, having one dull cusp that produced high stresses in the food item and three cusps that acted to stabilize the food item. We then set out to measure tooth cusp RoC in several species of extant apes to determine if any of the predicted optimal morphologies existed in nature and whether tooth cusp RoC was correlated with diet. While the optimal morphologies were not found in apes, we did find that tooth cusp RoC was correlated with diet and folivores had duller cusps while frugivores had sharper cusps. We hypothesize that, because of wear patterns, tooth cusp RoC is not providing a mechanical advantage during food item breakdown but is instead causing the tooth to wear in a beneficial fashion. Next, we investigate two possible relationships between tooth cusp RoC and enamel thickness, as enamel thickness plays a significant role in the way a tooth wears, using CT scans from hundreds of unworn cusps. There was no relationship between the two variables, indicating that selection may be acting on both variables independently to create an optimally shaped tooth. Finally, we put forth a framework for testing the functional optimality in teeth that takes into account tooth strength, food item breakdown efficiency, and trapability (the ability to trap and stabilize a food item).

Flatfoot is often asymptomatic but sometimes presents with symptoms, even in children. This thesis aimed to discover if there was a difference between children with and without symptoms, in the hope that this might aid treatment decisions. Firstly, an audit was performed to discover the prevalence and type of symptoms, as well as current treatment protocols. Secondly, 107 volunteers from the general population and 20 patients were assessed in more detail. The participants were divided into groups and ANOVA tests were used to find the significant differences. Pain and parental concern were frequently reported in the audit population. The majority of this population had moderate bilateral flexible flatfoot with an active Windlass mechanism and static heel valgus. Treatment was dependent on department. The symptomatic group displayed reduced passive ankle dorsiflexion indicating tightness of the tendo-Achilles, as well as increased frequency of severe knee hyperextension and knee valgus upon clinical examination. During static stance, three differences were found between symptomatic and asymptomatic groups, two differences between flat feet and neutral feet. During dynamic trials, the symptomatic group showed reduced stride length and percentage time spent in swing. The ground reaction profiles showed differences in early and late stance. Further investigation supported the idea that decreased late stance vertical ground reaction force peak was evidence of instability in the symptomatic group. Four kinematic parameters demonstrated significant differences at foot strike, five at midstance, and seven at foot off. In terms of kinetics, after controlling for relative stride length, four differences were found, but none between the asymptomatic and symptomatic flat feet. Plantar pressure was successfully used to estimate truncated foot length. The flat feet did not display increased peak midfoot pressure; it was actually lower in flat footed groups. Arch Index and Modified Arch Index were successfully used for instantaneous and continuous assessment of foot posture over stance. The differences found between symptomatic and asymptomatic flat feet (particularly at foot off) shed some light upon the potential causes of symptoms.