The objective of this study is to explore the diagnostic decision and sensitivity of the surface electromyogram (EMG) clustering index (CI) with respect to post-stroke motor unit (MU) alterations through a simulation approach by the existing motor neuron pool model and surface EMG model. In the simulation analysis, three patterns of diagnostic decisions were presented in 24 groups representing eight types in three degrees of MU alterations. Specifically, the CI decision exhibited an abnormally increased pattern for five types, an abnormally decreased pattern for two types, and an invariant pattern for one type. Furthermore, the CI diagnostic decision was found to be highly sensitive to three types because a 50% degree of alteration in these types resulted in a distinct deviation of 2.5 in the CI Z-score. The mixed CI patterns were confirmed in experimental data collected from the paretic muscles of 14 subjects with stroke, as compared to the healthy muscles of 10 control subjects. Given the simulation results as a guideline, the CI diagnostic decision could be interpreted from general neural or muscular changes into specific MU changes (in eight types). This can further promote clinical applications of the convenient surface EMG tool in examining and monitoring paretic muscle changes toward customized stroke rehabilitation.

中文翻译：

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基于模型的肌电聚集指数相对于运动单位特性的敏感性分析：研究中风后FDI肌肉。

这项研究的目的是通过现有的运动神经元池模型和表面的一种模拟方法来探索表面肌电图（EMG）聚类指数（CI）对中风后运动单位（MU）改变的诊断决策和敏感性EMG模型。在仿真分析中，在24个组中呈现了三种诊断决策模式，分别代表了三种类型MU变化的八种类型。具体地说，CI决策显示出五种类型的异常增加模式，两种类型的异常减少模式以及一种类型的不变模式。此外，发现CI诊断决策对三种类型高度敏感，因为这些类型中50％的变化程度导致CI Z得分明显偏离2.5。与从10名对照受试者的健康肌肉相比，从14名中风受试者的腹壁肌肉收集的实验数据中证实了混合CI模式。以模拟结果为指导，可以将CI诊断决策从一般的神经或肌肉变化解释为特定的MU变化（八种类型）。这可以进一步促进便捷的表面肌电图工具在临床检查和监测椎间盘肌肉向定制化卒中康复方面的变化方面的临床应用。