Shahid Shahjahan, Walker Jacqueline, Lyons Gerard M, Byrne Ciaran A, Nene Anand Vishwanath
g.tec Guger Technologies OEG, Herberstein str. 60, 8020, Graz, Austria.
IEEE Trans Biomed Eng. 2005 Jul;52(7):1195-209. doi: 10.1109/tbme.2005.847525.
The electromyographic (EMG) signal provides information about the performance of muscles and nerves. At any instant, the shape of the muscle signal, motor unit action potential (MUAP), is constant unless there is movement of the position of the electrode or biochemical changes in the muscle due to changes in contraction level. The rate of neuron pulses, whose exact times of occurrence are random in nature, is related to the time duration and force of a muscle contraction. The EMG signal can be modeled as the output signal of a filtered impulse process where the neuron firing pulses are assumed to be the input of a system whose transfer function is the motor unit action potential. Representing the neuron pulses as a point process with random times of occurrence, the higher order statistics based system reconstruction algorithm can be applied to the EMG signal to characterize the motor unit action potential. In this paper, we report results from applying a cepstrum of bispectrum based system reconstruction algorithm to real wired-EMG (wEMG) and surface-EMG (sEMG) signals to estimate the appearance of MUAPs in the Rectus Femoris and Vastus Lateralis muscles while the muscles are at rest and in six other contraction positions. It is observed that the appearance of MUAPs estimated from any EMG (wEMG or sEMG) signal clearly shows evidence of motor unit recruitment and crosstalk, if any, due to activity in neighboring muscles. It is also found that the shape of MUAPs remains the same on loading.
肌电图（EMG）信号提供了有关肌肉和神经活动的信息。在任何时刻，肌肉信号即运动单位动作电位（MUAP）的形状都是恒定的，除非电极位置发生移动，或者由于收缩水平的变化导致肌肉发生生化变化。神经元脉冲的发放速率与肌肉收缩的持续时间和力量有关，其确切的发生时间本质上是随机的。EMG信号可以被建模为一个滤波后的脉冲过程的输出信号，其中假设神经元发放脉冲是一个系统的输入，该系统的传递函数就是运动单位动作电位。将神经元脉冲表示为具有随机发生时间的点过程，可以将基于高阶统计量的系统重建算法应用于EMG信号，以表征运动单位动作电位。在本文中，我们报告了将基于双谱倒谱的系统重建算法应用于真实的有线肌电图（wEMG）和表面肌电图（sEMG）信号的结果，以估计股直肌和股外侧肌在静息状态以及其他六个收缩位置时MUAP的形态。据观察，从任何EMG（wEMG或sEMG）信号估计得到的MUAP形态都清楚地显示出运动单位募集和串扰（如果有的话，这是由于相邻肌肉的活动引起的）的证据。还发现，加载时MUAP的形状保持不变。
