Neuromuscular control and biomechanical adaptations in strength training: Implications for improved athletic performance
Abstract
Neuromuscular control plays a critical role in athletic performance, influencing movement efficiency, coordination, and injury prevention. While strength training enhances neuromuscular efficiency, traditional electromyographic (EMG) analysis methods often fail to capture transient activations and complex neuromuscular adaptations. This study aims to evaluate neuromuscular adaptations in strength training using wavelet-based EMG analysis, nonlinear dynamics, and muscle synergy analysis via non-negative matrix factorization (NMF). The primary objective is to determine whether these advanced techniques provide a more comprehensive assessment of motor unit synchronization, stability, and movement coordination. A six-week strength training program was conducted with 47 competitive athletes (30 males, 17 females). EMG signals were analyzed to assess wavelet power variations, recurrence rate, fractal dimension, and synergy activation levels. Pearson correlation analysis identified relationships between neuromuscular parameters. Strength training significantly improved neuromuscular efficiency, reducing wavelet power (1.35 to 0.98), decreasing recurrence rate (0.74 to 0.50), and increasing coordination efficiency (71.4% to 92.4%). An unexpected plateau effect was observed after three weeks, suggesting a transition from early-phase neuromuscular adaptation to a stabilization phase. These findings highlight the importance of progressive overload variations in sustaining neuromuscular adaptation. The integration of wavelet-based EMG, nonlinear dynamics, and synergy analysis enhances training assessments, offering a data-driven framework for optimizing performance and injury prevention strategies.
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