Exploring Variation in Biomechanical Data

Exploring variation is often the goal when researchers apply the tools of functional data analysis to biomechanical data. This chapter describes functional summary statistics, such as the mean and covariance functions, as a first step for this purpose. Then, visualisation tools for functional data analysis, which are useful for understanding variability and structure in functional data, are reviewed. Finally, this chapter discusses functional principal components analysis, a method that is frequently applied to biomechanical data to explore variation, providing an in-depth overview of its use in biomechanics research and discussing its extensions for modern biomechanical data. The methods outlined in each section of this chapter are accompanied by practical example demonstrations on the GaitRec dataset.