A NOVEL METHOD TO DETERMINE STATISTICAL EFFECT MAGNITUDE USING SPM FOR GAIT ANALYSIS

The purpose of this research was to extend the typical SPM analysis of time varying human movement gait. We focused on the magnitude of statistical effect, with colour maps used to identify regions of high and low effect at the three-component vector level (3D joint kinematics and kinetics). Conceptually similar to a multivariate ANOVA, users can easily identify joints with the highest statistical effect, then probe the scalar components to determine which is most contributing to this effect. Though the analysis can be applied to any human movement biomechanics (i.e., running, walking, landing etc.), the example presented here is walking gait. Though only the kinetics from a single joint are presented, our goal is to build a user-friendly GUI capable of analysing the kinematics and kinetics of all joints and degrees of freedom in the kinematic and kinetic chain.