Low back pain (LBP) is a common musculoskeletal condition that is both costly and disabling, with 3% of LBP-affected people not responding to treatment, and developing chronic LBP. This project aims to determine whether deficits in pelvic stability related to pelvic girdle pain (PGP) are also evident in chronic non-specific LBP and whether these pelvic stability variables are predictive of future PGP in healthy populations. During typical arthro-kinematic clinical assessments, we will measure indicators of pelvic stability such as muscle activation, joint coordination and mobility. With these measurements, we will use artificial neural networks to compare groups and individuals. This data analysis technique allows for analysis of complex multi-dimensional data. This study will identify potential predictors of low back and pelvic girdle pain in healthy populations. Such knowledge may improve diagnostic or treatment protocols for people with observed movement disorders.