首页> 外文期刊>Journal of electromyography and kinesiology: Official journal of the International Society of Electrophysiological Kinesiology >Detection of surface electromyography recording time interval without muscle fatigue effect for biceps brachii muscle during maximum voluntary contraction
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Detection of surface electromyography recording time interval without muscle fatigue effect for biceps brachii muscle during maximum voluntary contraction

机译:检测最大肌无力时肱二头肌肌肉无肌疲劳效应的表面肌电图记录时间间隔

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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 10. s of force and sEMG signals of BBM were recorded simultaneously during MVC. The subjects reached the maximum force level within 2. s 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 0. s time index corresponds to maximum force point). Then, the first 8. s of sEMG and force signals were divided into 0.5. s 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 0. s time intervals (i.e. -0.25 to 0.25. s). 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 0. s time interval. Thus, it might be assumed that the muscle fatigue starts after the 0. s 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 2. s gradual increase time) for 12 subjects were 2353, 1258. ms and 536-4186. ms, 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.
机译:通过使用12位受试者的肱二头肌肱肌(BBM)的力和表面肌电图(sEMG)信号来检查疲劳对最大自愿收缩(MVC)参数的影响。这项研究的目的是找到不受肌肉疲劳影响的MVC录音的sEMG时间间隔。在MVC期间同时记录了至少10 s的BBM力和sEMG信号。通过稍微增加力量,受试者在2 s内达到最大力量水平,然后最大程度地收缩BBM。相对于最大力的时间指标标记每个sEMG和力信号的时间指标(即,在时间归一化之后,每个sEMG或力信号的0. s时间指标对应于最大力点)。然后,将sEMG的前8. s和力信号分为0.5。 s间隔。计算每个间隔的平均力,中值频率(MF)和综合EMG(iEMG)值。振幅归一化是通过将力信号除以其时间间隔为0. s(即-0.25到0.25。s)的平均值来进行的。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信号(MF,iEMG)进行统计分析(弗里德曼检验与邓恩事后检验)。尽管ANOVA结果并未提供有关肌肉疲劳发作的统计上显着信息,但线性回归(平均力与时间)显示从0 s时间间隔开始的斜率减小(Pearson-r = 0.9462,p <0.0001)。 。因此,可以假设在0 s时间间隔后开始出现肌肉疲劳,因为肌肉无法达到其峰值力量水平。这意味着不受肌肉疲劳影响的MVC计算的最可靠间隔是从EMG活动开始到力峰值时间。 12位受试者的平均值,SD和此间隔的范围(不包括2. s逐渐增加的时间)分别为2353、1258。ms和536-4186。毫秒。超过此间隔会在针对BBM的MVC-sEMG研究的最大幅度计算中引入估计误差。结果表明,需要同时记录力和sEMG信号才能更准确地计算MVC-sEMG的最大幅度。

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