对单个运动单元(SMU)活动的分析提供了基础,可以从中识别有关控制肌肉力的神经策略的信息。由于α运动神经元产生的动作电位与神经支配的肌纤维接收的动作电位之间存在一对一的关联。如此强大的评估通常是用侵入性电极进行的(即,肌内肌电图(EMG)),然而,信号处理技术的最新进展使高密度表面肌电图(HDsEMG)记录中的单个运动单元(SMU)活动得以识别。这个矩阵,由肌电图实验设计共识(CEDE)项目开发,为使用侵入性(针和细线EMG)和非侵入性(HDsEMG)SMU识别方法记录和分析SMU活动提供建议,总结它们在不同测试条件下使用时的优缺点。出院率和外周的分析和报告建议(即,还提供了肌纤维传导速度)SMU特性。Delphi程序达成共识的结果载于附录中。这个矩阵旨在帮助研究人员收集,报告,并在研究和临床应用的背景下解释SMU数据。
The analysis of single motor unit (SMU) activity provides the foundation from which information about the neural strategies underlying the control of muscle force can be identified, due to the one-to-one association between the action potentials generated by an alpha motor neuron and those received by the innervated muscle fibers. Such a powerful assessment has been conventionally performed with invasive electrodes (i.e., intramuscular electromyography (EMG)), however, recent advances in signal processing techniques have enabled the identification of single motor unit (SMU) activity in high-density surface electromyography (HDsEMG) recordings. This matrix, developed by the
Consensus for Experimental Design in Electromyography (CEDE) project, provides recommendations for the recording and analysis of SMU activity with both invasive (needle and fine-wire EMG) and non-invasive (HDsEMG) SMU identification methods, summarizing their advantages and disadvantages when used during different testing conditions. Recommendations for the analysis and reporting of discharge rate and peripheral (i.e., muscle fiber conduction velocity) SMU properties are also provided. The results of the Delphi process to reach
consensus are contained in an appendix. This matrix is intended to help researchers to collect, report, and interpret SMU data in the context of both research and clinical applications.