Unraveling chaotic motor patterns of elite and sub-elite wrestlers in snap-down technique using multidimensional recurrence quantification analysis of muscle activity
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引用次数: 0
Abstract
Success in competitive sports depends on athletes' ability to consistently perform complex motor patterns, requiring both stability and adaptability. Rapid adjustments are crucial in freestyle wrestling because of unpredictable opponent actions. Previous research has noted elite wrestlers' adaptability, but traditional linear analyses miss the chaotic, nonlinear dynamics of these movements. This study used multidimensional recurrence ruantification analysis (MDRQA) to explore repeatability, stability, and adaptability in recurrent patterns of neuromuscular coordination among elite and sub-elite wrestlers. Electromyography (EMG) signals from the triceps, biceps, anterior deltoid, and latissimus dorsi in the dominant upper limb were recorded during seven successful snap-down techniques. Determinism (%DET) and laminarity (%LAM) assessed repeatability and stability, whereas the entropy of diagonal (EntL) and vertical (EntV) recurrence patterns measured the complexity and adaptability. Elite wrestlers showed significantly higher %DET and %LAM values, indicating greater motor pattern consistency. Higher EntL and EntV values demonstrate increased complexity and adaptability in neuromuscular control, suggesting the use of chaotic dynamics for optimal performance. This study highlights the importance of nonlinear approaches, such as MDRQA, in understanding athletes' motor control. These insights can inform training programs to enhance athletes' consistency, adaptability, and complexity, ultimately improving their performance in unpredictable environments.
期刊介绍:
Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.