首页> 外文期刊>Journal of electromyography and kinesiology: Official journal of the International Society of Electrophysiological Kinesiology >Local muscle endurance is associated with fatigue-based changes in electromyographic spectral properties, but not with conduction velocity
【24h】

Local muscle endurance is associated with fatigue-based changes in electromyographic spectral properties, but not with conduction velocity

机译:局部肌肉耐力与基于疲劳的肌电频谱特性变化有关,但与传导速度无关

获取原文
获取原文并翻译 | 示例
           

摘要

The purpose of this study was to examine the associations amongst muscle fiber action potential conduction velocity (CV), spectral characteristics of the surface electromyographic (EMG) signal, and endurance time during a sustained submaximal isometric muscle action. Eleven men (mean +/- SD age = 23 +/- 4 yrs) performed a sustained, submaximal isometric muscle action of the dominant forearm flexors at 60% of the maximum voluntary contraction (MVC) until the designated force level could no longer be maintained. Sixteen separate bipolar surface EMG signals were detected from the biceps brachii with a linear electrode array during this contraction. Two channels from this array were used to measure CV, and one of these two channels was used for further EMG signal processing. The channels that provided the highest signal quality were used for the CV measurements and further data analysis. A wavelet analysis was then used to analyze the bipolar EMG signal, and the resulting wavelet spectrum was decomposed with a nonparametric spectral decomposition procedure. The results showed that the time to exhaustion during the sustained contraction was not correlated with the rate of decrease in CV, but it was highly correlated with both the decrease in high-frequency spectral power (r = 0.947) and the increase in low-frequency spectral power (r = 0.960). These findings are particularly interesting, considering that the decrease in traditional EMG spectral variables (e. g., mean frequency or median frequency) with fatigue is generally attributed to reductions in CV. While this may indeed be true, the present results suggested that other factors (i. e., other than CV) that can affect the shape of the EMG frequency spectrum during fatigue are more important in determining the endurance capabilities of the muscle than is CV. (C) 2015 Elsevier Ltd. All rights reserved.
机译:这项研究的目的是检查在持续的次最大等距肌肉动作过程中,肌纤维动作电位传导速度(CV),表面肌电图(EMG)信号的频谱特征和耐力时间之间的关联。 11名男性(平均+/- SD年龄= 23 +/- 4岁)以最大自愿收缩(MVC)的60%对前臂屈肌进行持续的,次最大的等距肌肉动作,直到无法再达到指定的力量水平为止保持。在此收缩过程中,使用线性电极阵列从肱二头肌中检测到十六个独立的双极表面肌电信号。来自该阵列的两个通道用于测量CV,这两个通道之一用于进一步的EMG信号处理。提供最高信号质量的通道用于CV测量和进一步的数据分析。然后使用小波分析来分析双极EMG信号,并通过非参数频谱分解程序分解所得的小波频谱。结果表明,持续收缩过程中的疲劳时间与CV的降低速率无关,但与高频频谱功率的降低(r = 0.947)和低频信号的增加密切相关。频谱功率(r = 0.960)。考虑到传统的肌电图频谱变量(例如平均频率或中频)随疲劳度的降低通常归因于CV的降低,因此这些发现特别有趣。尽管这确实可能是正确的,但本结果表明,在疲劳期间可影响EMG频谱形状的其他因素(即CV以外的因素)比CV更重要的是确定肌肉的耐力。 (C)2015 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号