Jiang Ning, Parker Philip A, Englehart Kevin B
Department of Electrical and Computer Engineering, University of New Brunswick, Fredericton, Canada.
IEEE Trans Biomed Eng. 2006 Aug;53(8):1605-14. doi: 10.1109/TBME.2006.876631.
Concurrently active motor units (MUs) of a given muscle can exhibit a certain degree of synchronous firings, and a certain degree of common variation in their firing rates. The former property is referred to as motor unit synchrony in the literature, which is termed motor unit innervation process (MUIP) correlation in this study. The latter is referred to as motor unit common drive and can be quantified by the common drive coefficient, which is the correlation coefficient between the smoothed firing rates of the two MUs. Both properties have important roles and implications in the generation and resulting characteristics of the myoelectric signal and for the development of signal processing algorithms in myoelectric signal (MES) applications. In order to study these implications and characteristics, in this paper estimation procedures are developed to quantify the degree of MUIP correlation and common drive as functions of physiological parameters. Also, the interaction between MUIP correlation and motor unit common drive is studied in a physiologically realistic simulation model. Neurons modeled by Hodgkin-Huxley systems form the framework of the simulation model in which excitation and synaptic characteristics can be modified. MUIP correlation and common drive degree and interaction are studied through a number of simulations. To support the simulation results, experimental in vivo motor unit trains were collected at low levels of contraction from 11 subjects, and decomposed into the constituent unit trains giving 50 concurrently active motor unit pairs. The simulation demonstrated that the innervation process correlation coefficient is controlled primarily by the postsynaptic conductance, gsyn, and was less than 0.05 mS/cm2 for realistic values of gsyn. The common drive was found to be controlled by the exciting neuron input with no statistically significant interaction between it and the MUIP correlation. The experimental data gave results in close agreement with those of the simulation.
特定肌肉中同时活跃的运动单位(MU)可表现出一定程度的同步放电,以及其放电频率的一定程度的共同变化。前一种特性在文献中被称为运动单位同步性,在本研究中被称为运动单位神经支配过程(MUIP)相关性。后一种特性被称为运动单位共同驱动,可通过共同驱动系数进行量化,该系数是两个运动单位平滑放电频率之间的相关系数。这两种特性在肌电信号的产生及其特征方面以及肌电信号(MES)应用中的信号处理算法开发中都具有重要作用和意义。为了研究这些意义和特征,本文开发了估计程序,以量化作为生理参数函数的MUIP相关性和共同驱动程度。此外,在一个生理现实的模拟模型中研究了MUIP相关性与运动单位共同驱动之间的相互作用。由霍奇金-赫胥黎系统建模的神经元构成了模拟模型的框架,在该模型中可以修改兴奋和突触特性。通过大量模拟研究了MUIP相关性、共同驱动程度及其相互作用。为了支持模拟结果,从11名受试者的低收缩水平收集了体内运动单位序列,并将其分解为组成单位序列,得到50对同时活跃的运动单位。模拟表明,神经支配过程相关系数主要由突触后电导gsyn控制,对于gsyn的实际值,该系数小于0.05 mS/cm2。发现共同驱动由兴奋性神经元输入控制,它与MUIP相关性之间没有统计学上显著的相互作用。实验数据给出的结果与模拟结果非常一致。