Department of Kinesiology, Brock University, St. Catharines, Ontario, Canada.
Department of Systems Design Engineering, University of Waterloo, Ontario, Canada.
J Electromyogr Kinesiol. 2020 Feb;50:102383. doi: 10.1016/j.jelekin.2019.102383. Epub 2019 Dec 28.
Rather than discarding motor unit potential trains (MUPTs) because they do not meet 100% validity criteria, we describe and evaluate a novel editing routine that preserves valid discharge times, based on decreasing shape variability (variance ratio, VR) within a MUPT. The error filtered estimation (EFE) algorithm is then applied to the remaining 'high confidence' discharge times to estimate inter-discharge interval (IDI) statistics. Decomposed surface EMG data from the flexor carpi radialis recorded from 20 participants during 60% MVC wrist flexion was used. There were two levels of denoising criteria (relaxed and strict) criteria for removing MUPs to decrease the VR and increase the signal-to-noise ratio (SNR) of a MUPT. In total, VR decreased 24.88% and SNR increased 6.0% (p's < 0.05). The MUP template peak-to-peak (P-P) amplitude and P-P duration were dependent on the level of denoising (p's < 0.05). The standard error of the estimate (SEE) of the mean IDI before and after editing using the relaxed criteria (3.2% versus 3.69%), was very similar (p > 0.05). The same was true for the SEE between denoising criteria, which increased only to 5.14% for the strict criteria (p > 0.05). Editing the MUPTs resulted in a significant decrease in MUP shape variability and in the measures extracted from the MUP templates, with trivial differences between the SEE of the mean IDI between the edited and unedited MUPTs.
我们描述并评估了一种新的编辑程序，该程序基于肌动单元电位（MUPTs）内放电时间的变异性降低（变异比，VR），保留有效的放电时间，而不是因为不符合 100%有效性标准而丢弃 MUPTs。然后，将错误过滤估计（EFE）算法应用于剩余的“高置信度”放电时间，以估计放电间隔（IDI）统计信息。从 20 名参与者在 60%最大握力腕屈时记录的桡侧腕屈肌表面肌电图数据中分解。有两种去噪标准（放松和严格）用于去除 MUPs，以降低 VR 并提高 MUPT 的信噪比（SNR）。总的来说，VR 降低了 24.88%，SNR 提高了 6.0%（p 值均<0.05）。MUP 模板峰峰值（P-P）幅度和 P-P 持续时间取决于去噪水平（p 值均<0.05）。使用放松标准编辑前后平均 IDI 的估计标准误差（SEE）（3.2%与 3.69%）非常相似（p 值均>0.05）。去噪标准之间的 SEE 也是如此，严格标准仅增加到 5.14%（p 值均>0.05）。编辑 MUPTs 导致 MUP 形状变异性和从 MUP 模板中提取的测量值显著降低，编辑和未编辑 MUPTs 之间平均 IDI 的 SEE 差异微不足道。
