Sensitivity of principal component analysis outcomes to data pre-processing conditions when quantifying trial-to-trial variability in whole-body kinematics.

This study investigated whether modes of variance in trial-to-trial whole-body kinematic variability identified by principal component analysis (PCA) were consistent across data pre-processing conditions generated from a common dataset. Comparisons made included 1) when trajectory data was expressed in a global vs. local reference frame; 2) when the number of landmarks used to represent whole-body motion differed, and; 3) whether input trajectory data were normalized to participant stature. Varying data pre-processing conditions prior to PCA does not bias the total variance identified. However, it can influence how modes of variance are dispersed across PCs, which in turn, can influence interpretation.