A drop landing screening approach to monitor an individual using functional data analysis: An ACL injury case study

Abstract

ObjectivesTo explore the practicality of using functional principal components analysis (fPCA) and intra-athlete z-score changes for individual athlete monitoring post-ACL injury and surgery. DesignA single athlete case study using within-athlete repeated measures in the context of applied athlete monitoring. MethodsUsing single leg (left) drop landing (3 landings per session) onto a force plate, the athlete completed 6 sessions prior (healthy) and 3 sessions post-ACL injury/surgery. Maximum vertical ground reaction force (vGRF), time to stabilisation (TTS) and outputs from fPCA (fPC scores) for the healthy sessions were used to develop intra-athlete means and standard deviations for each variable. Post-surgery measures were given z-scores relative to the healthy mean and standard deviation for each variable. The standard normal deviate (z = 1.96) was used as a threshold to flag landings that could be indicative of changes in movement behaviour. ResultsMaximum vGRF revealed no post-surgery trials that exceeded the standard normal deviate threshold based on the healthy data. TTS identified one landing post-surgery that exceeded the threshold. Scores for fPC2, fPC3 and fPC4 revealed landings that exceeded the threshold, with fPC4 demonstrating landings greater than the threshold for every trial (except two) post-surgery. ConclusionsIncluding fPCA identified significant and stable changes to the landing strategy (particularly within fPC4). When used in conjunction with other measures such as maximum vGRF and TTS, fPCA has the potential to provide meaningful insights into athlete monitoring models regarding changes to movement characteristics after injury.