Members of the elderly population is disproportionately prone to experiencing mobility impairment due to their aging bodies and as a result have frail bodies that are at a higher risk of grave injury due to falling. In order to combat this assistive mobility devices such as exoskeletons have been developed to help patients enhance their range of motion. With additive manufacturing techniques, such as fused deposition modeling (FDM), becoming a more mainstream form of design, the inclusion of lightweight polymers such as nylon 12 as primary construction materials for these devices has increased. In this thesis computer aided design (CAD) software was used to design a prototype lower body exoskeleton and simulation software was used to give the device the characteristics of Stratasys' nylon 12 carbon fiber FDM material to verify it if could be used as the primary construction material for this device when extruded from a FDM printer on either the XZ or ZX printing plane. From the simulations it was found that the material printed along the XZ plane could create a device that could withstand the weight of an average elderly male patient (200 lbs.) as well as the 35 lbs. of force applied to the …

Parkinson's disease (PD) is a neurodegenerative disease that affects motor abilities with increasing severity as the disease progresses. Traditional methods for diagnosing PD require specialists scoring qualitative symptoms using the motor subscale of the Unified Parkinson's Disease Rating Scale (UPDRS-III). Using force-plate data during quiet standing (QS), this study uses machine learning to target the characterization and prediction of PD and UPDRS-III. The purpose of predicting different subscores of the UPDRS-III is to give specialists more tools to help make an informed diagnosis and prognosis. The classification models employed classified PD with a sensitivity of 87.5% and specificity of 83.1%. Stepwise forward regression indicated that features correlated with base of support were most useful in the prediction of head rigidity (r-square = .753). Although there is limited data, this thesis can be used as an exploratory study that evaluates the predictability of UPDRS-III subscores using QS data. Similar prediction models can be implemented to a home setting using low-cost force plates as a novel telemedicine technique to track disease progression.

Sprint acceleration training has been highly researched and found that resistance sleds are one of the most effective tools for maximizing training adaptations. The resistance sled is being used by many of the world leaders in athletic training but has yet to be researched for the kinetic and kinematic effects some of its key components cause. The aim of this study was to better understand the effects of the attachment height on the sled and sled rail material on the user's trunk lean and jerking effect caused by the sled. This was done because it was hypothesized that the attachment height has a direct impact on trunk lean and sled rail material has a direct impact on jerk caused by the sled. To test these assumptions, experimental and theoretical data was collected using a single subject study analyzing trunk lean and acceleration values of the sled. The results presented a significant decrease in trunk lean (more horizontal line of action) when the attachment height was raised. Additionally, no significant values were attained to support the assumption that by modifying the sled rail material, jerking effects will decrease. The results indicate that there is a direct correlation between attachment height and …