Ravier Philippe, Buttelli Olivier, Jennane Rachid, Couratier Pierre
Laboratoire d'Electronique Signaux Images, Université d'Orléans, France.
J Electromyogr Kinesiol. 2005 Apr;15(2):210-21. doi: 10.1016/j.jelekin.2004.08.008. Epub 2004 Nov 18.
During a sustained contraction, electromyographic signals (EMGs) undergo a spectral compression. This fatigue behaviour induces a shift of the mean and the median frequencies to lower frequencies. On the other hand, several studies conclude that the mean/median frequency can increase, decrease or remain constant with an increasing force level. Such inconsistency is embarrassing since the fatigue state may be influenced by the force level. In this paper, we propose a frequency indicator which is sensitive to the force level independently of the fatigue state evaluated at 70% of the maximal voluntary contraction. Ten healthy volunteers participated in the study and both surface EMGs (from the short head of the biceps brachii) and force signals were measured. This study compared force and fatigue effects on the EMGs during short (3-s) isometric contractions at different strength intensities and during a sustained isometric contraction until exhaustion. The EMGs partly show 1/falpha spectral behaviours since their power spectral densities may experimentally fit with two linear segments in a log-log representation. The measured "right" slope produces variations of force as 20 times the variations of fatigue. 1/falpha Behaviour may be related to stochastic fractals. This fractal indicator is a new frequency indicator that is thus complementary to other known classical frequency indicators when studying force during unknown fatigue states.
在持续收缩过程中,肌电图信号(EMG)会经历频谱压缩。这种疲劳行为会导致平均频率和中位数频率向更低频率偏移。另一方面,多项研究得出结论,随着力水平的增加,平均/中位数频率可能会增加、降低或保持不变。这种不一致令人尴尬,因为疲劳状态可能会受到力水平的影响。在本文中,我们提出了一种频率指标,它对力水平敏感,且与在最大自主收缩的70%时评估的疲劳状态无关。十名健康志愿者参与了该研究,测量了表面肌电图(来自肱二头肌短头)和力信号。本研究比较了在不同强度的短时间(3秒)等长收缩以及持续等长收缩直至疲劳时,力和疲劳对肌电图的影响。肌电图部分呈现1/fα频谱行为,因为它们的功率谱密度在对数-对数表示中可能通过两个线性段进行实验拟合。测得的“正确”斜率产生的力变化是疲劳变化的20倍。1/fα行为可能与随机分形有关。这个分形指标是一种新的频率指标,因此在研究未知疲劳状态下的力时,它是对其他已知经典频率指标的补充。