Hernandez Luis R, Camic Clayton L
Department of Kinesiology and Physical Education, Northern Illinois University, DeKalb, IL 60115, USA.
Sports (Basel). 2019 Apr 2;7(4):78. doi: 10.3390/sports7040078.
The purpose of this study was to investigate the effect of fatigue status and contraction type on complexity of the surface electromyographic (sEMG) signal. Twelve females (mean age ± SD = 21.1 ± 1.4 years) performed three fatigue-inducing protocols that involved maximal concentric, eccentric, or isometric knee-extensor contractions over three non-consecutive sessions. Pre- and post-fatigue assessments were also completed each session and consisted of three maximal efforts for each type of contraction. Complexity of sEMG signals from the vastus lateralis was assessed using Sample Entropy (SampEn) and Detrended Fluctuation Analysis (DFA) as expressed using the scaling exponent α. The results showed that fatigue decreased ( < 0.05) sEMG complexity as indicated by decreased SampEn (non-fatigued: 1.57 ± 0.22 > fatigued: 1.46 ± 0.25) and increased DFA α (non-fatigued: 1.27 ± 0.26 < fatigued: 1.32 ± 0.23). In addition, sEMG complexity was different among contraction types as indicated by SampEn (concentric: 1.58 ± 0.22 > eccentric: 1.47 ± 0.27 and isometric: 1.50 ± 0.21) and DFA α (concentric: 1.27 ± 0.18 < isometric: 1.32 ± 0.18). Thus, these findings suggested sEMG complexity is affected by fatigue status and contraction type, with the degree of fatigue-mediated loss of complexity dependent on the type of contraction used to elicit fatigue.
本研究的目的是调查疲劳状态和收缩类型对表面肌电图（sEMG）信号复杂性的影响。12名女性（平均年龄±标准差=21.1±1.4岁）进行了三种诱导疲劳的方案，这些方案包括在三个非连续的时间段内进行最大程度的向心、离心或等长膝关节伸展收缩。每个时间段还完成了疲劳前后的评估，包括每种收缩类型的三次最大努力。使用样本熵（SampEn）和去趋势波动分析（DFA）（用标度指数α表示）评估股外侧肌sEMG信号的复杂性。结果表明，疲劳降低了（<0.05）sEMG复杂性，表现为SampEn降低（非疲劳：1.57±0.22>疲劳：1.46±0.25）和DFAα增加（非疲劳：1.27±0.26<疲劳：1.32±0.23）。此外，SampEn表明收缩类型之间的sEMG复杂性不同（向心：1.58±0.22>离心：1.47±0.27和等长：1.50±0.21），DFAα也不同（向心：1.27±0.18<等长：1.32±0.18）。因此，这些发现表明sEMG复杂性受疲劳状态和收缩类型的影响，疲劳介导的复杂性丧失程度取决于用于引发疲劳的收缩类型。
