Frontiers in physiology · 2025
Lower-limb surface electromyographic differences in roundhouse kicks between elite and sub-elite taekwondo athletes: a functional principal component analysis.
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Sun Jianbo, Wang Yifei, Sun Jingyuan, Dong Delong, Shaharudin Shazlin
Аннотация
PURPOSE: This study aimed to investigate the functional characteristics and distinctions in lower-limb electromyography (EMG) time-series data during roundhouse kicks performed by elite (n = 10) and sub-elite (n = 10) Taekwondo athletes, using Functional Principal Component Analysis (FPCA) to extract key parameters and identify critical phases of movement.
METHODS: EMG signals from 16 lower-limb muscles were collected via a Noraxon system synchronized with Vicon 3D motion capture. Group differences in integrated EMG (iEMG) were assessed using ANOVA, and muscles showing significant differences were further analyzed with FPCA (smoothing parameter e-7; eigenvalues >1; cumulative variance >85%).
RESULTS: Elite athletes demonstrated significantly higher iEMG values in specific muscles of both the supporting and kicking legs (p < 0.05). FPCA revealed higher scores for selected muscle components in the supporting and kicking legs among elite athletes (p < 0.05, ES = 0.64, R 2 = 92.6%; p < 0.05, ES = 0.66, R 2 = 88.8%; p < 0.01, ES = 0.53, R 2 = 94.8%). Notably, PC5 of the biceps femoris in the kicking leg was prominent during the kicking phase, while PC 4 of the gluteus maximus and biceps femoris in the supporting leg was critical during the recovery and end phases.
CONCLUSION: These findings highlight muscle-specific contributions that differentiate kick quality between top-level and average athletes. FPCA offers a novel framework to assess movement quality, providing insights for technique improvement and supporting the development of automated performance evaluation systems in combat sports.
METHODS: EMG signals from 16 lower-limb muscles were collected via a Noraxon system synchronized with Vicon 3D motion capture. Group differences in integrated EMG (iEMG) were assessed using ANOVA, and muscles showing significant differences were further analyzed with FPCA (smoothing parameter e-7; eigenvalues >1; cumulative variance >85%).
RESULTS: Elite athletes demonstrated significantly higher iEMG values in specific muscles of both the supporting and kicking legs (p < 0.05). FPCA revealed higher scores for selected muscle components in the supporting and kicking legs among elite athletes (p < 0.05, ES = 0.64, R 2 = 92.6%; p < 0.05, ES = 0.66, R 2 = 88.8%; p < 0.01, ES = 0.53, R 2 = 94.8%). Notably, PC5 of the biceps femoris in the kicking leg was prominent during the kicking phase, while PC 4 of the gluteus maximus and biceps femoris in the supporting leg was critical during the recovery and end phases.
CONCLUSION: These findings highlight muscle-specific contributions that differentiate kick quality between top-level and average athletes. FPCA offers a novel framework to assess movement quality, providing insights for technique improvement and supporting the development of automated performance evaluation systems in combat sports.