<p> Understanding human movement requires that biomechanists have knowledge of the kinematics and kinetics of the motion. Calculating the internal kinetics of a movement requires the input of segment inertial characteristics. Errors in the estimations of these body segment parameters (BSPs) may have detrimental effects on segmental kinetic calculations. </p> <p> The purposes of this study were to use i) investigate a new technique for measuring BSPs using dual photon absorptiometry (DPX) and ii) to investigate population differences in BSP values, develop geometric models to predict BSPs and compare geometric predictions with other prediction methods. </p> <p> In study 1, DPX measured whole body mass of humans with a group mean percent difference of -1.05% from criterion measurements. DPX also measured mass, centre of mass along a transverse axis (CM) and moment of inertia about the centre of mass (ICG) of a homogeneous object and a human cadaver leg with percent errors less than 4% from criterion measurements. </p> <p> In Study 2, 1 00 subjects were selected from four subpopulation groups according to gender (males/females) and age (19-30/ 55+ years). Using DPX, six body segments were measured for mass (forearm, hand, thigh, leg, foot, head) and four were measured for CM and radius of gyration (forearm, thigh, leg, head). Linear regression equations were developed and compared with geometric predictions and prediction equations from a popular literature source (Winter, 1990). </p> <p> Population differences were statistically significant for all body segments and all segment parameters except hand mass. Large segmental differences between individuals of similar size were also observed. The results showed the linear regression equations to provide the best estimations of BSPs. The geometric models and the predictions from Winter (1990) were poor for most segments. </p> <p> This study provided the foundation for a new method of BSP prediction. The population specific linear regression equations developed in this study should be used to predict BSPs for individuals similar to those examined in this experiment. While geometric models provided poor predictions, future improvements may increase their performance. </p> / Thesis / Candidate in Philosophy

<p> An accurate estimation of Body Segment Parameters (BSPs) is needed to understand human movement. These include segment mass, centre of mass, and moment of inertia about the centre of mass. Bone density scanners, such as DPX, can measure BSPs, but are limited to only two dimensions. MRI produces images in three dimensions, but cannot directly measure mass. For this study, MRI was used in conjunction with a DPX scan of the human body. The result was the development of a method to estimate mass, and subsequently, centre of mass, and moment of inertia from MRI images. Next, ellipses were created from the dimensions of transverse plane slices (produced from MRI). Three different density profiles were applied to the ellipses, and mass, centre of mass and moment of inertia about the centre of mass of each slice was calculated. It was found that constant density transverse plane ellipses could be used to estimate BSPs for most regions of the body. Photogrammetry can also be used to generate the dimensions of ellipses that represent transverse plane slices. Therefore, the suitability of photogrammetry to estimate slice BSPs was tested. It was found that depending on the density profile used, photogrammetry is an effective method for estimating BSPs. An exception to this estimation was in the chest, where ellipses may not be representative of the body. </p> / Thesis / Master of Science (MSc)