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Postural Control Adaptations in Trampoline Athletes of Different Competitive Levels: Insights from COP Linear and Nonlinear Measures.

Mengzi Sun | Fangtong Zhang | Xinglong Zhou | Feng Qu | Wenhui Mao | Li Li
Entropy (Basel, Switzerland) | 2025

Balance is a fundamental quality for trampoline athletes, the basis for completing complex skills. We aimed to compare balance control strategies between elite trampolinists (ETs) and sub-elite trampolinists (Sub-ET) by integrating linear and nonlinear center of pressure (COP) measures across stable and unstable surfaces. Twenty-four male athletes (12 ET, 12 Sub-ET) participated. Each participant performed 15-s static standing trials with eyes closed on a firm surface (FI) and a foam surface (FO). COP parameters were extracted, including ellipse area, sway velocity, sway range, and sample entropy (SampEn) in the medio-lateral (ML) and antero-posterior (AP) directions. Repeated-measures ANOVA was applied to examine the effects of group and surface condition. Linear analyses indicated that ET athletes exhibited greater sway amplitudes and faster velocities than Sub-ET athletes, with both groups showing larger sway on FO compared with FI. Nonlinear analyses revealed that ET athletes demonstrated lower SampEn, suggesting more structured and automatized control strategies. ET athletes maintained consistent entropy across both conditions, reflecting stronger adaptability to unstable surfaces. These results emphasize the importance of combining linear and nonlinear measures in balance assessment and suggest that incorporating unstable or trampoline-like surfaces into training may enhance adaptability, improve performance, and reduce injury risk.

Pubmed ID: 41440384

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RRID:SCR_001622

Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.

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