A novel method to evaluate error in anatomical marker placement using a modified generalized Procrustes analysis.

As biomechanical research evolves, a continuing challenge is the standardization of data collection and analysis techniques. In gait analysis, placement of markers to construct an anatomical model has been identified as the single greatest source of error; however, there is currently no standardized approach to quantifying these errors. The current study applies morphometric methods, including a generalized Procrustes analysis (GPA) and a nearest neighbour comparison to quantify discrepancies in marker placement, with the goal of improving reliability in gait analysis. An extensive data-set collected by an Expert (n = 340) was used to evaluate marker placements performed by a Novice (n = 55). Variances identified through principal component analysis were used to create a modified GPA to transform anatomical data, and scaled coordinates from the Novice data-set were then scored against the Expert subset. The results showed quantitative differences in marker placement, suggesting that, although training improved consistency, systematic biases remained.