Baratta R V, Solomonow M, Zhou B H, Zhu M
Louisiana State University Medical Center, Department of Orthopaedic Surgery, New Orleans 70112, USA.
J Electromyogr Kinesiol. 1998 Oct;8(5):279-85. doi: 10.1016/s1050-6411(97)00031-x.
Three methods that can significantly reduce the variability of the EMG power density spectrum (PDS) variable by eliminating artifactual components are described. Two methods, one that allows the subtraction of power line noise in the time domain and one which allows the subtraction of system noise in the frequency domain from the EMG, were shown to be effective in helping to accurately estimate the median frequency (MF) of the PDS, and especially during low level contractions (0-25% maximal voluntary contraction, MVC) when the signal-to-noise ratio is unfavorable. The techniques eliminate the artifactual effects of system and power line noises from the EMG recordings throughout the force range (0-100% MVC) while preserving the native EMG power at all frequencies. It was also shown that if a technique to train subjects to produce their true MVC is employed, the absolute force/torque produced could be as much as 30% higher than in untrained MVC. The effect of true MVC production was also shown to be significant when interpretation of PDS variables are correlated to the processes which produce contraction.
本文描述了三种通过消除伪迹成分来显著降低肌电图功率密度谱（PDS）变量变异性的方法。其中两种方法，一种允许在时域中减去电力线噪声，另一种允许在频域中从肌电图中减去系统噪声，已被证明在帮助准确估计PDS的中位数频率（MF）方面是有效的，特别是在低水平收缩（0-25%最大自主收缩，MVC）时，此时信噪比不利。这些技术在整个力范围（0-100%MVC）内消除了肌电图记录中系统和电力线噪声的伪迹效应，同时保留了所有频率下的原始肌电图功率。研究还表明，如果采用一种训练受试者产生其真正MVC的技术，所产生的绝对力/扭矩可能比未经训练的MVC高出30%。当将PDS变量的解释与产生收缩的过程相关联时，真正MVC产生的影响也被证明是显著的。
