Use of Body Composition Imaging to Calculate 3-D Inertial Parameters for Inverse Dynamic Analysis of Youth Pitching Arm Kinetics

<p>The objectives of this study were to 1) calculate participant-specific segment inertial parameters using dual energy X-ray absorptiometry (DXA) data (referred to as full DXA-driven parameters) and compare the pitching arm kinetic predictions using full DXA-driven inverse dynamics vs scaled, DXA mass-driven (using DXA masses but scaled centers of mass and radii of gyration), and DXA scaled inverse dynamics(ID) (using the full DXA-driven inertial parameters averaged across all participants), 2) examine associations between full DXA-driven kinetics and body mass index (BMI) and 3) examine associations between full DXA-driven kinetics and segment mass index (SMI). Eighteen 10- to 11- year-olds pitched 10 fastballs. DXA scans were conducted and examined to obtain 3D inertial parameters of the upper arm, forearm, and hand. Full DXA-driven and scaled inertial parameters were compared using paired t-tests. Pitching arm kinetic predictions calculated with the four methods (i.e. scaled ID, DXA mass-driven ID, full DXA-driven ID, and DXA scaled ID) were compared using a repeated measures ANOVA with Tukey post-hoc tests. The major results were that 1) full DXA-driven participant specific inertial parameters differed from scaled inertial parameters 2) kinetic predictions significantly varied by method and 3) full DXA-driven ID predictions for shoulder compression force and shoulder internal rotation torque were significantly associated with BMI and/or SMI.</p>

Name thesis:degree_name

MS in Biomedical Engineering

Discipline thesis:degree_discipline

Biomedical and General Engineering

Year dc:date.available

2020

Author dc:creator

• Jennings, Dalton James

Contributors dc:contributor

• Stephen Klisch
• Mechanical Engineering
• College of Engineering

• baseball
• DXA
• biomechanics
• motion analysis
• body mass index
• Matlab
• Biomechanical Engineering

Identifier

10.15368/theses.2020.13

OAI identifier oai:identifier

oai:digitalcommons.calpoly.edu:theses-3584