Harba M I, Teng L Y
Universiti Sains Malaysia, Perak, Malaysia.
Front Med Biol Eng. 1999;9(1):31-47.
Cross-correlating two surface EMG signals detected at two different locations along the path of flow of action potential enables the measurement of the muscle fiber average conduction velocity in those active motor units monitored by the electrodes. The position of the peak of the cross-correlation function is the time delay between the two signals and hence the velocity may be deduced. The estimated velocity using this technique has been observed previously to depend on the location of the electrodes on the muscle surface. Different locations produced different estimates. In this paper we present a measurement system, analyze its inherent inaccuracies and use it for the purpose of investigating the reliability of measurement of conduction velocity from surface EMG. This system utilizes EMG signals detected at a number of locations on the biceps brachii, when under light tension, to look for any pattern of variations of velocity as a function of location and time. It consists of a multi-electrode unit and a set of eight parallel on-line correlators. The electrode unit and the parallel correlators ensure that these measurements are carried out under the same physical and physiological conditions of the muscle. Further, the same detected signals are used in different measurement configurations to try to understand the reasons behind the observed variations in the estimated velocity. The results obtained seem to suggest that there will always be an unpredictable random component superimposed on the estimated velocity, giving rise to differences between estimates at different locations and differences in estimates with time at the same location. Many factors contribute to this random component, such as the non-homogeneous medium between the muscle fibers and the electrodes, the non-parallel geometry and non-uniform conduction velocity of the fibers, and the physical and physiological conditions of the muscle. While it is not possible to remove this random component completely from the measurement, the user must be aware of its presence and how to reduce its effects.
将沿着动作电位传播路径在两个不同位置检测到的两个表面肌电图信号进行互相关，能够测量由电极监测的那些活跃运动单元中的肌纤维平均传导速度。互相关函数峰值的位置是两个信号之间的时间延迟，因此可以推导出速度。此前观察到，使用该技术估计的速度取决于电极在肌肉表面的位置。不同位置会产生不同的估计值。在本文中，我们介绍了一种测量系统，分析了其固有的不准确性，并将其用于研究从表面肌电图测量传导速度的可靠性。该系统利用肱二头肌在轻度张力下在多个位置检测到的肌电图信号，来寻找速度随位置和时间变化的任何模式。它由一个多电极单元和一组八个并行的在线相关器组成。电极单元和并行相关器确保这些测量是在肌肉相同物理和生理条件下进行的。此外，相同的检测信号用于不同的测量配置，以试图理解估计速度中观察到的变化背后的原因。获得的结果似乎表明，在估计速度上总会叠加一个不可预测的随机成分，导致不同位置的估计值之间存在差异，以及同一位置的估计值随时间存在差异。许多因素导致了这个随机成分，例如肌纤维和电极之间的非均匀介质、纤维的非平行几何形状和非均匀传导速度，以及肌肉的物理和生理条件。虽然不可能从测量中完全消除这个随机成分，但用户必须意识到它的存在以及如何降低其影响。
