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The objective of this study was to investigate associations between injury-related kinematic parameters and overweight measures for youth baseball pitchers. The injury-related kinematic parameters considered were measurements 1) at foot contact: stride length, front foot position, shoulder external rotation, shoulder abduction, and elbow flexion; 2) between FC and ball release: peak knee extension; and 3) at BR: shoulder abduction. Data from three separate collection sites examined pitching mechanics of 18 10- to 11-year-old pitchers, 11 14- to 16-year-old pitchers, and 104 16- to 18-year-old pitchers Linear regression analyses were performed to determine significant correlations between kinematic parameters and body mass index (BMI) for each of the three age groups (10- to 11-year-olds, 14- to 16-year-olds, 16- to 18-year-olds). The significant findings were 1) for 10- to 11-year-old pitchers, stride length was negatively correlated with BMI and front foot position was positively correlated with BMI and 2) for 16- to 18-year-old pitchers, shoulder external rotation was negatively correlated with BMI and elbow flexion was positively correlated with BMI. A key clinical implication of this study is that select kinematic parameters have been identified that could guide coaches and trainers when working with overweight pitchers. In addition, select kinematic parameters of concern have been identified for different age ranges.

The nanoscale dimension known as D-spacing describes the staggering of collagen molecules, which are fundamental to the biphasic makeup of bone tissue. This dimension was long assumed to be constant, but recent studies have shown that the periodicity of collagen is variable. Given that the arrangement of collagen molecules is closely related to the degree of bone mineralization, recent studies have begun to look at D-spacing as a potential factor in the ongoing effort to battle postmenopausal osteoporosis. The theoretical models presented by previous studies have only opted to model a single collagen-hydroxyapatite period, so the creation of an intricate computational approach that more exhaustively models a network of collagen and mineral is well-warranted. Sheep present an excellent opportunity to examine metabolic disorders, as their bone structure similar to that of the human skeleton. Six Rambouillet-cross ewes were used for the purpose of gathering experimental data. Three ewes underwent a sham surgery (controls), while an ovariectomy (OVX) was performed on the remaining three sheep. Each sheep was sacrificed after 12 months and their radius and ulna were harvested for atomic force microscopy and mechanical testing. Each sheep bone produced up to 25 beam samples that were available for analysis, and two were randomly selected from each test sheep. The cranial anatomical sector was selected for testing as it replicates the tensile loading condition characteristically experienced by collagen molecules and its exclusive examination removes any unintended variation due to bone section. Experimental D-spacing measurements were used in a finite element software, Abaqus, to create the ``Complex Model'': a large-scale, 2-D staggered array representation of collagen and hydroxyapatite periodicity. D-spacings intrinsic variability was mimicked through a Gaussian distribution that randomly determined periodic lengths based on provided experimental data. The model was generated with these random conditions for 2 x 100 units. Safeguards were implemented to ensure appropriate ratios of collagen to hydroxyapatite throughout the randomization. Collagen was assigned viscoelastic material properties originally developed by Dr. Frank Richter and modified by Miguel Mendoza. Hydroxyapatite was modeled as an elastic isotropic material. Four models were created using randomized D-spacings from control sheep and four separate models were created based on OVX sheep. Tangent delta--a damping characteristic--was recorded to evaluate bone viscoelasticity across four test frequencies: 1, 3, 9, and 15 Hz. Results strongly suggest that the Complex Model matches experimental findings more accurately than previous computational approaches. These results indicate the complicated network of many collagen units is an essential parameter of adequate modeling. A repeated measures analysis of variance was performed to examine the differences between control and OVX sheep. After adjusting for all other predictors, at the 1% significance level, after adjusting for all other variables, there is not enough evidence to convince this study that the Surgical Treatment alone has a significant impact on output tangent delta. This finding leads this study to conclude that OVX is fully accounted for within the Complex Model through the inclusion of its D-spacing, and the answers to bone's complicated mechanical properties during estrogen loss may lie in how OVX changes collagen viscoelasticity. Significant interactions were found between the Model Type and the Test Frequency. A Tukey-Kramer pairwise comparison was performed between Complex and Experimental data, which determined the Complex Model did not behave statistically differently from experimental findings at 15 Hz. This result suggests the Complex Model may begin to be validated to experimental results in a statistically meaningfully way that is a first for this style of FEA approach. The flexibility implemented in the randomization of the Complex Model welcomes refinement primarily in modeling viscoelasticity and fine-tuning the representation of mineralization. Through adjusting these material characteristics, the Complex Model may become an even more powerful tool in examining bone viscoelasticity and metabolic disorders.

The objectives of this study were to (1) develop a non-invasive method (referred to as Smart Photo-Tape) to calculate participant-specific upper arm, forearm, and hand segment inertial properties (SIPs) (e.g. mass, center of mass, and radii of gyration) and (2) use those Smart Photo-Tape properties in inverse dynamics (ID) analyses to calculate injury-related pitching arm kinetics. Five 20- to 23- year-old baseball pitchers were photographed holding a baseball and analyzed using the Smart Photo-Tape method to obtain 3-D inertial properties for their upper arm, forearm, and hand. The upper arm and forearm segments were modelled as stacked elliptic cylinders and the hand was modelled as an ellipsoid. One participant received a dual energy x-ray absorptiometry (DXA) scan and conducted a motion analysis study, pitching 10 fastballs. Scaled SIPs from cadaver studies and Smart Photo-Tape SIPs were compared using one sample t-tests. Pitching arm kinetic predictions were calculated and compared using scaled inverse dynamics (ID), Smart Hand ID (a combination of scaled SIPs for the upper arm and forearm and Smart Photo-Tape SIPs for the hand), and Smart Photo-Tape ID. The major result was that the Smart Photo-Tape SIPs were significantly different when compared to their respective scaled inertial properties, with the hand segment producing the largest difference between the scaled SIPs and Smart Photo-Tape SIPs. The implication of this study is that researches or coaches can use the Smart Photo-Tape method to calculate participant specific SIPs for pitching arm kinetic analysis.

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The recent emergence of electric scooter (e-scooter) ride share companies has greatly increased the use of e-scooters in cities around the world. In this thesis, firstly, e-scooter injuries reported in the current literature as well as an overview of current e-scooter company policies, state laws, and local laws are reviewed. The most injured regions of the body were the head and extremities. These injuries are generally minor to moderate in severity and commonly include fractures and lacerations. A primary cause of e-scooter accidents is front wheel collisions with a vertical surface such as a curb or object, generically referred to as a "stopper." Therefore, various e-scooter-stopper crashes were simulated numerically across different impact speeds, approach angles, and stopper heights to characterize their influence on rider injury risk during falls. A finite element (FE) model of a standing Hybrid III anthropomorphic test device was used as the rider model after being calibrated against certification test data. The angle of approach was found to have the greatest effect on injury risk to the rider, and it was shown to be positively correlated with injury risk. Smaller approach angles were shown to cause the rider to land on their side, while larger approach angles caused the rider to land on their head and chest. Additionally, arm bracing was shown to reduce the risk of serious injury in two thirds of the impact scenarios. The majority of e-scooter rider fatalities (about 80%) are recorded in collisions between a car and an e-scooter. Therefore, crashes between an e-scooter and a sedan (FCR) and a sports utility vehicle (SUV) were simulated using finite element models. The vehicles impacted the e-scooter at a speed of 30 km/hr in a perpendicular collision and at 15 degrees towards the vehicle, to simulate a rider being struck by a turning vehicle. The risks of serious injury to the rider were low for the head, brain, and neck, but femur/tibia fractures were observed in all simulations. The primary cause of head and brain injuries was found to be the head-ground impact if such an impact occurred. / Master of Science / The recent emergence of electric scooter (e-scooter) ride share companies has greatly increased the use of e-scooters in cities around the world. In this thesis, firstly, e-scooter injuries reported in the current literature as well as an overview of current e-scooter company policies, state laws, and local laws are reviewed. The most injured regions of the body were the head and extremities. These injuries are generally minor to moderate in severity and commonly include fractures and lacerations. A primary cause of e-scooter accidents is front wheel collisions with a vertical surface such as a curb or object, generically referred to as a "stopper." Therefore, various e-scooter-stopper crashes were simulated numerically across different impact speeds, approach angles, and stopper heights to characterize their influence on rider injury risk during falls. A finite element (FE) model of a standing Hybrid III anthropomorphic test device was used as the rider model after being calibrated against certification test data. The angle of approach was found to have the greatest effect on injury risk to the rider, and it was shown to be positively correlated with injury risk. Smaller approach angles were shown to cause the rider to land on their side, while larger approach angles caused the rider to land on their head and chest. Additionally, arm bracing was shown to reduce the risk of serious injury in two thirds of the impact scenarios. The majority of e-scooter rider fatalities (about 80%) are recorded in collisions between a car and an e-scooter. Therefore, crashes between an e-scooter and a sedan (FCR) and a sports utility vehicle (SUV) were simulated using finite element models. The vehicles impacted the e-scooter at a speed of 30 km/hr in a perpendicular collision and at 15 degrees towards the vehicle, to simulate a rider being struck by a turning vehicle. The risks of serious injury to the rider were low for the head, brain, and neck, but femur/tibia fractures were observed in all simulations. The primary cause of head and brain injuries was found to be the head-ground impact if such an impact occurred.

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No description available.