The purpose of this study was to determine if the implementation of a strict validation procedure, designed to limit the inclusion of inaccuracies from the decomposition of surface electromyographic (sEMG) signals, affects population-based motor unit (MU) analyses. Four sEMG signals were obtained from the vastus lateralis of 59 participants during isometric contractions at different relative intensities [30%, 70%, and 100% of maximal voluntary contraction (MVC)], and its individual motor unit potential trains (MUPTs) were extracted. The MUPTs were then excluded (ISIval) based on the coefficient of variation and histogram of the interspike intervals (ISI), the absence of additional clusters that reveals missed or additional firings, and more. MU population-based regression models (i.e., modeling the entire motor unit pool) were performed between motor unit potential size (MUP_SIZE), mean firing rate (MFR), and recruitment threshold (RT%) separately for DSDC_Only (includes all MUPTs without the additional validation performed) and ISIval data at each contraction intensity. The only significant difference in regression coefficients between DSDC_Only and ISIval was for the intercepts of the MUP_SIZE/MFR at 100% MVC. The validation had no other significant effect on any of the other regression coefficients for each of the contraction intensities. Our findings suggest that even though the decomposition of surface signals leads to some inaccuracies, these errors have limited effects on the regression models used to estimate the behavior of the whole pool. Therefore, we propose that motor unit population-based regression models may be robust enough to overcome decomposition-induced errors at the individual MU level.

这项研究的目的是确定旨在限制表面肌电图（sEMG）信号分解所包含的不准确性的严格验证程序的实施是否会影响基于人群的运动单位（MU）分析。在不同相对强度[最大自主收缩（MVC）的30％，70％和100％]进行等距收缩时，从59名参与者的股外侧肌获得了四个sEMG信号，并提取了其各个运动单位电位序列（MUPT） 。然后，根据变异系数和尖峰间隔（ISI）的直方图，不存在额外的星团来揭示错过或额外的射击等因素，排除MUPT（ISIval）。基于MU人口的回归模型（即_仅DSDC（包括未执行额外验证的所有MUPT）和每个收缩强度的ISIval数据，分别针对SIDC（_SIZE），平均射击率（MFR）和补充阈值（RT％）。DSDC _Only和ISIval之间回归系数的唯一显着差异是MUP _SIZE的截距/ MFR为100％MVC。对于每种收缩强度，验证对其他任何回归系数均没有其他显着影响。我们的发现表明，即使表面信号的分解会导致某些不准确之处，但这些错误对用于估计整个池行为的回归模型的影响有限。因此，我们建议基于运动单位人口的回归模型可能足够健壮，以克服各个MU水平上的分解引起的误差。