Longitudinal Monitoring of Biomechanical and Psychological State in Collegiate Female Basketball Athletes Using Principal Component Analysis

Figure 2

Use-case example of weekly changes in biomechanical principal component scores and self-reported pain in a collegiate female basketball athlete across the 2022-2023 competitive season. Specifically, jump asymmetry-specific minimum detectable change (MDC) upper and lower bounds are depicted for red-flagging biomechanical fluctuations above and beyond the measurement error of the system, which were paralleled, to some extent, by seasonal changes in self-reported levels of pain. The MDC statistics are derived based on five weeks of preseason training and normative biomechanical patterns exhibited at the cohort level, with this MDC value applied (±) to the average value that this subject displayed across the same timeframe to calculate individualized bounds by which their jump asymmetry fluctuated from their normative patterns. However, this “unperturbed” baseline period was confounded by high levels of self-reported pain in this athlete, suggesting that our normative biomechanical patterns might not necessarily indicate what we would expect in this athlete. It is important to note that this figure underrepresents the amount of data that was collected per participant over the two-year study period, as (i) only data from the 2022-2023 season are presented, as the first season (2021-2022) was only used to train the PCA model and (ii) only weeks in which all three forms of data (i.e., on-court biomechanics, CMJ biomechanics, and psychological state) were concurrently collected are visually represented for simplicity sake and interpretability.