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Date of Award

8-2003

Degree Type

Thesis

Degree Name

Doctor of Philosophy (PhD)

Department

Kinesiology

Supervisor

Dr. James J. Dowling

Abstract

Calculating net joint forces and moments of force in the study of human movement requires accurate human body segment parameter (BSP) information. The purpose of this study was to investigate an approach for developing geometric models based on segment mass distribution (MD) information for BSP estimation. Study 1 investigated the MD properties of the human thigh for four human populations using dual energy x-ray absorptiometry (DEXA). Thigh mass, centre of mass in the longitudinal (CMx) and mediolateral (CMy) directions, and moment of inertia about the CM along an anteroposterior axis (IcMz) were determined using DEXA. Thigh MD properties of 20 subjects were used for model generation and the equations were validated on 80 subjects by comparing estimations with DEXA measurements. BSP estimations from 4 other models available in the literature were also examined. Study 2 followed the methodology of Study 1, using the forearm segment. Study 3 advanced on Studies 1 and 2 by adding a sagittal plane dimension to a lower leg model. Forty subjects underwent frontal and sagittal plane DEXA scans and models were validated using a split-half reliability method. The results of all three studies showed that mass and IcM estimates were not significantly better than the other models examined, however CM estimations were often improved. The models in Studies 1 and 2 may have been limited by the 2D nature of the methodology. The use of an elliptical model helped to account for the more posterior location of the CM in the lower leg, however insufficient statistical power may have prevented the detection of significant differences in mass and Icm estimates. The results of this study show promise for future modelling of human body segments. Modeling according to MD properties allows the assumption of constant density while accounting for inertial changes along the segment length. 3D model validation, greater sample sizes, and "the analysis of the remaining segments of the human body may lead us closer to understanding the kinetics of human movement.

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