Kleine Bert U, van Dijk Johannes P, Zwarts Machiel J, Stegeman Dick F
Department of Clinical Neurophysiology, Institute of Neurology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.
J Electromyogr Kinesiol. 2008 Aug;18(4):652-61. doi: 10.1016/j.jelekin.2007.01.010. Epub 2007 Mar 23.
High-density surface EMG can be used to obtain a spatially selective representation of several motor unit action potentials. Recently, a decomposition of the signal into the underlying motor neuron firing patterns has been described. The reliability of the algorithm has not yet been tested. Eleven healthy subjects participated. High-density surface EMG was recorded from the vastus lateralis muscle during an isometric knee extension. Two independent operators analyzed the signals. After operator-supervised cluster analysis of spikes, motor unit action potential templates were constructed and an automatic template matching was performed. The decomposition was adjusted by hand. Agreement between operators was calculated for the number of coincident firings. Bland-Altman plots of peak-to-peak amplitude were constructed and limits of agreement were calculated. For completely decomposed motor unit action potential trains the between-operator agreement of firing events was very high. The peak-to-peak amplitude of monopolar motor unit action potentials was 115microV (SD 74microV). The agreement was within 3microV and independent of amplitude. With partial decomposition agreement within 26microV was achieved. For bipolarly derived motor unit action potentials the peak-to-peak amplitude was 54microV (SD 49microV), the agreement was within 3microV. Only for recordings obtained from a force level below 5% of the maximum voluntary contraction full decomposition was possible. It was concluded that when full decomposition is achieved, two independent operators are likely to arrive at nearly identical firing patterns.
高密度表面肌电图可用于获取多个运动单位动作电位的空间选择性表示。最近,已描述了将信号分解为潜在运动神经元放电模式的方法。该算法的可靠性尚未经过测试。11名健康受试者参与了研究。在等长膝关节伸展过程中,从股外侧肌记录高密度表面肌电图。两名独立的操作人员分析了这些信号。在操作人员监督下对尖峰进行聚类分析后,构建运动单位动作电位模板并进行自动模板匹配。手动调整分解过程。计算操作人员之间在同时放电次数上的一致性。构建峰峰值幅度的布兰德-奥特曼图并计算一致性界限。对于完全分解的运动单位动作电位序列,操作人员之间在放电事件上的一致性非常高。单极运动单位动作电位的峰峰值幅度为115微伏(标准差74微伏)。一致性在3微伏以内且与幅度无关。对于部分分解,一致性在26微伏以内。对于双极导出的运动单位动作电位,峰峰值幅度为54微伏(标准差49微伏),一致性在3微伏以内。仅在从最大自主收缩的5%以下的力水平获得的记录中才可能实现完全分解。得出的结论是,当实现完全分解时,两名独立的操作人员很可能得出几乎相同的放电模式。