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不同频率等长振动运动诱发肌肉疲劳的分析

Analysis of muscle fatigue induced by isometric vibration exercise at varying frequencies.

作者信息

Mischi M, Rabotti C, Cardinale M

机构信息

Department of Electrical Engineering, Eindhoven University of Technology, the Netherlands.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:6463-6. doi: 10.1109/EMBC.2012.6347474.

Abstract

An increase in neuromuscular activity, measured by electromyography (EMG), is usually observed during vibration exercise. The underlying mechanisms are however unclear, limiting the possibilities to introduce and exploit vibration training in rehabilitation programs. In this study, a new training device is used to perform vibration exercise at varying frequency and force, therefore enabling the analysis of the relationship between vibration frequency and muscle fatigue. Fatigue is estimated by maximum voluntary contraction measurement, as well as by EMG mean-frequency and conduction-velocity analysis. Seven volunteers performed five isometric contractions of the biceps brachii with a load consisting of a baseline of 80% of their maximum voluntary contraction (MVC), with no vibration and with a superimposed 20, 30, 40, and 50 Hz vibrational force of 40 N. Myoelectric and mechanical fatigue were estimated by EMG analysis and by assessment of the MVC decay, respectively. A dedicated motion artifact canceler, making use of accelerometry, is proposed to enable accurate EMG analysis. Use of this canceler leads to better interpolation of myoelectric fatigue trends and to better correlation between mechanical and myoelectric fatigue. In general, our results suggest vibration at 30 Hz to be the most fatiguing exercise. These results contribute to the analysis of vibration exercise and motivate further research aiming at improved training protocols.

摘要

通过肌电图(EMG)测量发现,在振动训练期间通常会观察到神经肌肉活动增加。然而,其潜在机制尚不清楚,这限制了在康复计划中引入和利用振动训练的可能性。在本研究中,使用一种新型训练设备以不同频率和力量进行振动训练,从而能够分析振动频率与肌肉疲劳之间的关系。通过最大自主收缩测量以及EMG平均频率和传导速度分析来评估疲劳。七名志愿者对肱二头肌进行五次等长收缩,负荷为其最大自主收缩(MVC)的80%作为基线,分别在无振动以及叠加40 N的20、30、40和50 Hz振动力的情况下进行。分别通过EMG分析和MVC衰减评估来估计肌电和机械疲劳。提出了一种利用加速度测量的专用运动伪影消除器,以实现准确的EMG分析。使用该消除器可更好地插值肌电疲劳趋势,并使机械疲劳与肌电疲劳之间具有更好的相关性。总体而言,我们的结果表明30 Hz的振动是最易导致疲劳的训练。这些结果有助于对振动训练进行分析,并推动旨在改进训练方案的进一步研究。

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