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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.

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There is a need for standardized clinically accessible measurements that would enable detection of the primary underlying deficit and a patient’s rehabilitation capacity after stroke. While a multitude of measures of neuromotor control exist, there is not a unified perspective on their complementarity versus redundancy for identifying the stroke-related impairments. This dissertation evaluates four measures of neuromotor control: the lower extremity portion of the Fugl-Meyer Assessment (FM-LE), plantarflexor central drive, the number of muscle synergies, and the dynamic motor control index. The first aim was to assess if the dynamic motor control index, which has not previously been used in a post-stroke population, could identify stroke-related impairments in neuromotor control, and how it compared to the number of muscle synergies. The second aim evaluated which measure(s) of neuromotor control were most indicative of biomechanics and functional outcomes. Twenty-two individuals post-stroke (60 ± 8 years old, chronicity 6 ± 4 years, 16 male, 10 right paretic) completed clinical assessments of the FM-LE and six-minute walk test, 90 seconds of fast treadmill walking during which force and muscle activity data were collection, and three burst-superimposition tests on the paretic limb for the calculation of central drive. The results of the first study concluded the dynamic motor control index was able to identify stroke-related impairments and may do so better than the discrete number of muscle synergies. The second study determined that the FM-LE, paretic central drive, and paretic dynamic motor control index are individually the best neuromotor indicator of propulsion asymmetry, endurance, and step time asymmetry, respectively, suggesting these measures are complementary for explaining post-stroke deficits. A multi-modal evaluation approach that combines these measures of neuromotor control with clinical and biomechanical evaluations provides the best opportunity to understand post-stroke walking impairment. Future work should focus on developing a single measure of neuromotor control that fully explains locomotor compensations and the primary underlying impairment, further enabling clinical accessibility and standardized assessments. / 2024-09-08T00:00:00Z

Fractures of the lower leg are common during frontal automotive collisions and military blasts. These two scenarios cause injury via a similar axial loading mechanism. The majority of previous studies that have conducted axial impact tests to determine the injury limits of the lower leg have simulated automotive impacts; however, due to the viscoelastic nature of bone, it remains unclear whether limits from automotive experiments can be applied to higher-rate blasts. The purpose of this work was to study the effect of load rate on the fracture tolerance of the tibia during these two scenarios. The instrumentation required to quantify impacts to lower leg specimens using a pneumatic impactor was developed, and included capturing synchronized load, acceleration, velocity, strain, and high-speed video data. Subsequently, impact testing was performed on twelve human cadaveric tibias. Velocities and impact durations were matched to literature values to simulate an automotive collision and a military blast. Force and impulse were found to significantly differ between the two conditions, while kinetic energy did not. Specimens impacted at higher rates required greater forces to achieve fracture, which suggests that load rate needs to be accounted for in future injury criteria. Two commonly used anthropomorphic test device lower legs were tested under similar loading conditions, and new thresholds were developed for these devices. Finally, a finite element model was tested for its ability to simulate loading of the tibia during varied impacts. This model can be used to assess injury risk and protective measures for the leg. Understanding the effect of load rate on the tibia’s fracture tolerance is essential when developing injury thresholds that can be applied to impacts of various rates. The results of this work can be used in the future to design and evaluate improved protective systems to be implemented in vehicles. / Thesis / Master of Applied Science (MASc) / Fractures of the lower leg are common during frontal automotive collisions and military blasts. Due to the viscoelastic nature of bone, it remains unclear whether safety limits from automotive experiments can be applied to higher-rate blasts. The purpose of this work was to study the effect of load rate on the fracture tolerance of the tibia during these two scenarios. Impact testing was performed on twelve human cadaveric tibias. Specimens impacted at higher rates required greater forces to achieve fracture, which suggests that load rate needs to be accounted for in future injury criteria. Two commonly used crash test dummy lower legs were tested under similar loading conditions, and a finite element model was developed and tested to simulate loading of the tibia during high-rate impacts. The results of this work can be used to design and evaluate improved protective systems to be implemented in vehicles.

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