An Automated Image-Based Method of 3D Subject Specific Body Segment Parameter Estimation

Recent studies have suggested that limb kinetics during swing or float phase movements are important for ACL injury analysis and injury prevention [1]. Kinetic (moment and force) calculations during swing phase can be sensitive to the accuracy of subject-specific body segment parameters (BSP) including mass and inertial properties. While numerous methods for estimating BSP have been implemented including regression equations [2,3], geometric body shape estimations, medical imaging and optimization approaches, they all have application specific limitations. Almost all of these BSP estimation approaches are limited by assumptions that: the mass center (CM) lies on the axis connecting the segment’s proximal and distal joint center, the body principle moments of inertia are aligned with the segment axes [4], and the right and left limbs are symmetric. These assumptions could introduce errors in 3D kinematic analysis. Non-invasive methods of measuring the exact geometry and volume of body segments have the potential to reduce most sources of error.