Future Directions of FDA in Biomechanics

This chapter gives a snapshot of sub-fields of FDA that are well-suited to analysing modern biomechanical data. Functional mixed-effects models allow the complex grouping and dependence structures (e.g., induced by multiple subjects being measured for repeated trials/sessions) that arise in large biomechanical datasets to be modelled appropriately. Multivariate FDA techniques provide advantages in analysing human movement data over their univariate counterparts, as they can capture co-variation between multiple joints. Finally, FDA provides direct access to examining the relationships between derivatives of functions and this is another interesting area to explore.