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探讨热身和拉伸后腘绳肌肌电图的多重分形变化。

Exploring Acute Changes in Hamstring EMG after Warm-up and Stretching Using a Multifractal Analysis.

出版信息

Med Sci Sports Exerc. 2023 Jun 1;55(6):1023-1033. doi: 10.1249/MSS.0000000000003128. Epub 2023 Jan 14.

DOI:10.1249/MSS.0000000000003128
PMID:36719665
Abstract

INTRODUCTION

This study aimed to apply multifractal detrended fluctuation analysis (MFDFA) to surface EMG to detect neuromuscular changes after realistic warm-up procedures that was followed by various stretching exercises.

METHODS

Sixteen volunteers conducted two experimental sessions. Testing included two maximal voluntary contractions before, after a standardized warm-up, and after a stretching exercise (static or neurodynamic nerve gliding technique). EMG was registered on biceps femoris and semitendinosus muscles. EMG was analyzed using different parameters obtained from the singularity Hurst exponent function and multifractal power spectrum (both obtained from the multifractal detrended fluctuation analysis).

RESULTS

The Hurst exponent, α maximum, and peak value of the multifractal spectrum significantly decreased after warm-up as compared with baseline for both biceps femoris ( P = 0.003, P = 0.006, and P = 0.003, respectively) and semitendinosus ( P = 0.006, P = 0.013 and P = 0.01, respectively) muscles. No further alteration was obtained after static or neurodynamic nerve gliding stretching as compared with post-warm-up ( P = 1.0). No significant difference was obtained for Hurst exponent range, width, and asymmetry of the multifractal spectrum ( P > 0.05).

CONCLUSIONS

From the present results, EMG depicted multifractal features sensitive to detect neuromuscular changes after a warm-up procedure. An increase in multiscale complexity is revealed after warm-up without any further alteration after stretching. The multifractal spectrum depicted dominant small fluctuations that shifted toward slightly larger fluctuations that could be attributed to motor unit recruitment.

摘要

简介

本研究旨在应用多重分形去趋势波动分析(MFDFA)对表面肌电图(sEMG)进行分析,以检测经过现实热身程序和各种伸展运动后的神经肌肉变化。

方法

16 名志愿者进行了两次实验。测试包括在标准化热身前、热身后和伸展运动(静态或神经动态神经滑动技术)后进行两次最大自主收缩。在二头肌和半腱肌上记录肌电图。使用奇异 Hurst 指数函数和多重分形功率谱(均来自多重分形去趋势波动分析)获得的不同参数分析肌电图。

结果

与基线相比,热身后二头肌(P=0.003、P=0.006 和 P=0.003)和半腱肌(P=0.006、P=0.013 和 P=0.01)的 Hurst 指数、α最大值和多重分形谱峰值显著降低。与热身后相比,静态或神经动态神经滑动拉伸后无进一步变化(P=1.0)。多重分形谱的 Hurst 指数范围、宽度和不对称性无显著差异(P>0.05)。

结论

从目前的结果来看,肌电图描绘了对热身程序后神经肌肉变化敏感的多重分形特征。热身后,多尺度复杂性增加,伸展后无进一步变化。多重分形谱描绘了主导小波动,这些波动略微向稍大波动转移,这可能归因于运动单位募集。

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