EMG analysis tuned for determining the timing and level of activation in different motor units.
EMG analysis tuned for determining the timing and level of activation in different motor units.
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DOI：
10.1016/j.jelekin.2011.04.003
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发表时间：
2011-08
影响因子：
2.5
通讯作者：
Wakeling, James M.
中科院分区：
文献类型：
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作者：
Lee, Sabrina S. M.;Miara, Maria de Boef;Arnold, Allison S.;Biewener, Andrew A.;Wakeling, James M.
不同运动单元的招募模式和激活动力学极大地影响了肌肉力量发展的时间模式和大小，然而这些特征在肌肉模型中通常不被考虑。本研究的目的是通过肌电图（EMG）记录和直接从动物肌肉中记录的抽搐力谱来表征慢速和快速运动单元的招募和激活动力学。记录了7只山羊腓肠肌肌电图和肌力数据。这些实验引发的肌电信号频率含量有显著差异（p<0.001）。利用小波分析和主成分分析对其频率含量进行了表征，得到了中心频率分别为149.94Hz和323.13Hz的优化小波。优化后的小波用于计算肌电信号强度，并根据重构的抽搐力分布图推导出慢速和快速运动单元的传递函数，从而从肌电信号中估计肌肉的激活状态。得到的激活-失活时间常数在激活状态和力剖面之间的r值为0.98到0.99。这项工作为开发改进的肌肉模型建立了一个框架，该模型考虑了混合肌肉中慢纤维和快纤维的内在特性，并且可以更准确地预测肌电图的肌肉力量输出。
Recruitment patterns and activation dynamics of different motor units greatly influence the temporal pattern and magnitude of muscle force development, yet these features are not often considered in muscle models. The purpose of this study was to characterize the recruitment and activation dynamics of slow and fast motor units from electromyographic (EMG) recordings and twitch force profiles recorded directly from animal muscles. EMG and force data from the gastrocnemius muscles of seven goats were recorded during in vivo tendon-tap reflex and in situ nerve stimulation experiments. These experiments elicited EMG signals with significant differences in frequency content (p<0.001). The frequency content was characterized using wavelet and principal components analysis, and optimized wavelets with centre frequencies, 149.94Hz and 323.13Hz, were obtained. The optimized wavelets were used to calculate the EMG intensities and, with the reconstructed twitch force profiles, to derive transfer functions for slow and fast motor units that estimate the activation state of the muscle from the EMG signal. The resulting activation-deactivation time constants gave r values of 0.98 to 0.99 between the activation state and the force profiles. This work establishes a framework for developing improved muscle models that consider the intrinsic properties of slow and fast fibres within a mixed muscle, and that can more accurately predict muscle force output from EMG.
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影响因子：
5.5
作者：
GRIMBY, L;HANNERZ, J;HEDMAN, B
通讯作者：
HEDMAN, B
影响因子：
2.5
作者：
HENNEMAN, E;OLSON, CB
通讯作者：
OLSON, CB
影响因子：
2.8
作者：
Hodson-Tole, E. F.;Wakeling, J. M.
通讯作者：
Wakeling, J. M.
影响因子：
2.5
作者：
von Tscharner, V
通讯作者：
von Tscharner, V
EMG信号分析技术：检测，处理，分类和应用（校正）。
影响因子：
6.4
作者：
通讯作者：
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