Influence of proximal trunk borne load on lower limb countermovement joint dynamics

Abstract Vertical jumping involves coordinating the temporal sequencing of angular motion, moment, and power across multiple joints. Studying the biomechanical coordination strategies that differentiates loaded from unloaded vertical jumping may better inform training prescription for athletes needing to jump with load. Common multivariate methods (e.g. Principal Components Analysis) cannot quantify coordination in a dataset with more than two modes. This study aimed to identify coordinative factors across four modes of variation using Parallel Factor (Parafac2) analysis, which may differentiate unloaded (body weight [BW]) from loaded (BW + 20% BW) countermovement jump (CMJ). Thirty-one participants performed unloaded and loaded CMJ. Three-dimensional motion capture with force plate analysis was performed. Inverse dynamics was used to quantify sagittal plane joint angle, velocity, moment, and joint power across the ankle, knee, and hip. The four-mode data were as follows: Mode A was jump cycle (101 cycle points), mode B was participant (31 participants by two load), mode C was joint (two sides by three joints), and mode D was variable (angle, velocity, moment, power). Three factors were extracted, which explained 95.1% of the data’s variance. Only factors one (P = 0.001) and three (P