PURPOSE This study aimed to assess the validity of the first (EMGth1) and second (EMGth2) breakpoints in the EMG signal during skating. SCOPE Ten well-trained long track speed skaters performed a maximal incremental skating test on a slide board. EMG signals from six lower limb muscles were recorded during the last 15 s of each stage and converted to Root Mean Square for determination EMGth1 and EMGth2 using mathematical (2 and 3 linear regressions) and visual methods. CONCLUSIONS EMGth1 had a low detection rate (<50%) while EMGth2 could be identified visually in > 80% of cases, in 85% of cases using 2-lines and 63% using 3-lines regression. Quads (VL + VM) and Gluts (GM + GMd) had the highest EMGth2 detection rate for all methods (>70%). EMGth2 from Quads and Gluts detected by the 2-lines and 3-lines regression were not different than the second ventilatory threshold (VT2) (p > 0.05), while the visual method overestimated VT2 (p < 0.01). EMGth2 detected from Quads by the 2-lines regression method presented better correlation with VT2 stage (r = 0.91), lowest bias, and limit of agreement. We conclude that EMG is a valid non-invasive method to detect VT2 during skating when using a mathematical method to determine EMGth2.

中文翻译：

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不同的肌电图分析方法可识别速滑运动员的有氧和无氧阈值的有效性。

目的本研究旨在评估滑冰过程中EMG信号中第一个（EMGth1）和第二个（EMGth2）断点的有效性。范围十名训练有素的长距离速滑运动员在滑板上进行了最大的增量滑冰测试。在每个阶段的最后15 s期间记录来自下肢六块肌肉的EMG信号，并使用数学（2和3线性回归）和视觉方法将其转换为均方根，以确定EMGth1和EMGth2。结论EMGth1的检出率较低（<50％），而在80％以上的病例中，EMGth2可以通过肉眼识别，在8％的病例中使用2行和63％的病例使用3行回归。在所有方法中，Quads（VL + VM）和Gluts（GM + GMd）的EMGth2检测率最高（> 70％）。通过2线和3线回归检测到的Quads和Gluts的EMGth2与第二通气阈值（VT2）并无差异（p> 0.05），而视觉方法高估了VT2（p <0.01）。通过两线回归方法从Quads中检测到的EMGth2与VT2阶段（r = 0.91），最低偏差和一致性极限之间具有更好的相关性。我们得出结论，当使用数学方法确定EMGth2时，EMG是在滑冰过程中检测VT2的有效非侵入性方法。