DETERMINISTIC COMPONENT EXTRACTION USING PCA FOR EVALUATION OF ROWING DATA

##article.abstract##

INTRODUCTION: Human movement is intrinsically variable, both within and between individuals (Newell & Corcos, 1993). Kinematic rowing data is no different. It is believed that there is a need to separate the random elements of the rowing stroke from the deterministic components. Principle Component Analysis (PCA) may be used both as a filter to separate these components and as a method of analysis of the entire movement waveform, retaining potentially valuable temporal information (Deluzio et al, 1999). This research aims to analyse the use of PCA in the analysis of rowing kinematic data, utilising the entire waveform.