Rehabilitation Center "Het Roessingh", University of Twente, Enschede, The Netherlands.
J Electromyogr Kinesiol. 1992;2(1):15-25. doi: 10.1016/1050-6411(92)90004-3.
Three components determine the power spectrum of the surface EMG signal: the auto- and cross-power spectra of the firing processes and the power spectra of the motor unit action potential (MUAP). To clarify the relative contribution of these components to the median frequency (MF) of the power spectrum, a stochastic simulation model was used in which most input parameters [e.g., MUAP peak-peak time (PPT), mean interpulse interval time, and synchronization parameters] were described in terms of distribution functions. Simulation clearly predicts that MF is especially sensitive to variations in MUAP shape, the MUAP PPT, and synchronization. The influence of the firing process parameters was predicted to be marginal. To obtain values for the MUAP parameters, a needle-triggered averaging technique was used to gather surface MUAPs from the m. biceps brachii. With use of these MUAPs as input for the model, it was found that intrasubject variability of MF is caused by variations in both MUAP PPT and MUAP shape, whereas intersubject variability in MF is caused primarily by variations in PPT.
发射过程的自功率谱和互功率谱,以及运动单位动作电位(MUAP)的功率谱。为了阐明这些成分对功率谱的中值频率(MF)的相对贡献,使用了一个随机模拟模型,其中大多数输入参数[例如,MUAP 峰峰值时间(PPT)、平均脉冲间隔时间和同步参数]都用分布函数来描述。模拟清楚地预测 MF 特别敏感于 MUAP 形状、MUAP PPT 和同步的变化。预测发射过程参数的影响微不足道。为了获得 MUAP 参数的值,使用针触发平均技术从肱二头肌 m. 收集表面 MUAP。使用这些 MUAP 作为模型的输入,发现 MF 的个体内变异性是由 MUAP PPT 和 MUAP 形状的变化引起的,而 MF 的个体间变异性主要是由 PPT 的变化引起的。