A Multi-Population Biomechanical Investigation of Movement Strategy Classification via Force-Time Waveform Analysis

Abstract

Background: Traditional countermovement jump (CMJ) assessment relies on discrete metrics that potentially mask complex neuromuscular coordination strategies. This dissertation investigated whether continuous waveform analysis could reveal distinct movement phenotypes and their mechanistic basis across athletic populations. Methods: A sequential explanatory mixed-methods design was employed. Study 1 analyzed 17,767 CMJ trials from 448 NCAA Division I athletes using functional principal component analysis (fPCA) and k-means clustering on force-time waveforms. Study 2 collected synchronized kinematic-kinetic data from 34 recreationally active adults (150 trials) to elucidate joint-level mechanisms underlying force production strategies. Statistical parametric mapping and linear mixed-effects models evaluated continuous biomechanical differences between identified strategies. Results: Four orthogonal principal components explained 95.50% of force-time variance in elite athletes, substantially exceeding the 21 to 60% captured by discrete metrics. Five distinct movement strategies emerged with moderate between-athlete consistency (ICC = 0.66) but weak sport-specific clustering (Cramér's V < 0.14). Critical measurement discordance was identified where Strategies 2 and 3 achieved similar jump heights (45.7 vs. 48.4 cm) through fundamentally different force production patterns (peak force of 2.79 vs. 2.92 BW, p < 0.001, d = 0.47). Recreational athletes demonstrated population-specific patterns, with all trials mapping to the periphery of elite distributions (mean Euclidean distance of 4.66, exceeding the 95th percentile threshold of 2.31). Independent analysis revealed two recreational strategies differentiated primarily by force magnitude (PC1 = 84.5% variance) rather than the complex temporal-amplitude patterns characterizing elite athletes. Continuous kinematic analysis detected extensive strategic differences spanning 40 to 80% of the movement cycle, contrasting with minimal differences at discrete landmarks. Conclusions: CMJ performance emerges from stable neuromuscular phenotypes rather than sport-specific adaptations, with multiple coordination strategies achieving similar outcomes. The identification of measurement discordance challenges reliance on discrete metrics for performance monitoring. Population-specific force production capacities necessitate tailored assessment frameworks rather than universal standards. These findings advance biomechanical assessment methodology by demonstrating the superiority of continuous waveform analysis for detecting strategic variations invisible to traditional approaches. Implementation of strategy-specific training and monitoring protocols may optimize performance within individual neuromuscular constraints rather than forcing convergence toward presumed ideals. Significance: This work establishes a methodological framework for characterizing movement complexity applicable across fundamental athletic tasks, with implications for performance monitoring, talent identification, and individualized training prescription in sports biomechanics.