Hacettepe University, School of Medicine, Biophysics Department, Sihhiye, Ankara, Turkey.
J Electromyogr Kinesiol. 2010 Aug;20(4):773-6. doi: 10.1016/j.jelekin.2010.02.006. Epub 2010 Mar 7.
The effects of fatigue on maximum voluntary contraction (MVC) parameters were examined by using force and surface electromyography (sEMG) signals of the biceps brachii muscles (BBM) of 12 subjects. The purpose of the study was to find the sEMG time interval of the MVC recordings which is not affected by the muscle fatigue. At least 10s of force and sEMG signals of BBM were recorded simultaneously during MVC. The subjects reached the maximum force level within 2s by slightly increasing the force, and then contracted the BBM maximally. The time index of each sEMG and force signal were labeled with respect to the time index of the maximum force (i.e. after the time normalization, each sEMG or force signal's 0s time index corresponds to maximum force point). Then, the first 8s of sEMG and force signals were divided into 0.5s intervals. Mean force, median frequency (MF) and integrated EMG (iEMG) values were calculated for each interval. Amplitude normalization was performed by dividing the force signals to their mean values of 0s time intervals (i.e. -0.25 to 0.25s). A similar amplitude normalization procedure was repeated for the iEMG and MF signals. Statistical analysis (Friedman test with Dunn's post hoc test) was performed on the time and amplitude normalized signals (MF, iEMG). Although the ANOVA results did not give statistically significant information about the onset of the muscle fatigue, linear regression (mean force vs. time) showed a decreasing slope (Pearson-r=0.9462, p<0.0001) starting from the 0s time interval. Thus, it might be assumed that the muscle fatigue starts after the 0s time interval as the muscles cannot attain their peak force levels. This implies that the most reliable interval for MVC calculation which is not affected by the muscle fatigue is from the onset of the EMG activity to the peak force time. Mean, SD, and range of this interval (excluding 2s gradual increase time) for 12 subjects were 2353, 1258ms and 536-4186ms, respectively. Exceeding this interval introduces estimation errors in the maximum amplitude calculations of MVC-sEMG studies for BBM. It was shown that, simultaneous recording of force and sEMG signals was required to calculate the maximum amplitude of the MVC-sEMG more accurately.
本研究旨在通过肱二头肌(BBM)的力和表面肌电(sEMG)信号,探讨疲劳对最大自主收缩(MVC)参数的影响。12 名受试者同时记录至少 10s 的力和 BBM 的 sEMG 信号。受试者通过稍微增加力在 2s 内达到最大力水平,然后最大程度地收缩 BBM。每个 sEMG 和力信号的时间索引都相对于最大力的时间索引进行标记(即,时间归一化后,每个 sEMG 或力信号的 0s 时间索引对应于最大力点)。然后,将 sEMG 和力信号的前 8s 分为 0.5s 间隔。为每个间隔计算平均力、中值频率(MF)和积分肌电图(iEMG)值。通过将力信号除以 0s 时间间隔的平均值(即-0.25 至 0.25s)对力信号进行幅度归一化。对 iEMG 和 MF 信号重复类似的幅度归一化过程。对时间和幅度归一化后的信号(MF、iEMG)进行统计分析(Friedman 检验加 Dunn 事后检验)。尽管方差分析结果没有提供关于肌肉疲劳开始的统计学信息,但线性回归(平均力与时间)显示出从 0s 时间间隔开始的下降斜率(Pearson-r=0.9462,p<0.0001)。因此,可以假设肌肉疲劳从 0s 时间间隔开始,因为肌肉无法达到其峰值力水平。这意味着,对于不受肌肉疲劳影响的 MVC 计算,最可靠的间隔是从肌电图活动开始到最大力时间。12 名受试者的这个间隔的平均值、标准差和范围(不包括 2s 逐渐增加时间)分别为 2353、1258ms 和 536-4186ms。超过这个间隔会导致 MVC-sEMG 研究中最大振幅计算的估计误差。结果表明,需要同时记录力和 sEMG 信号,以更准确地计算 MVC-sEMG 的最大振幅。