Croce Ronald, Craft Amber, Miller John, Chamberlin Kent, Filipovic David
Motor Control and Biomechanics Laboratory, Department of Kinesiology, University of New Hampshire, Durham, New Hampshire, 03824, USA.
Department of Electrical and Computer Engineering, University of New Hampshire, Durham, New Hampshire, USA.
Muscle Nerve. 2016 Mar;53(3):452-63. doi: 10.1002/mus.24764. Epub 2015 Dec 29.
Surface electromyography (SEMG) and mechanomyography (SMMG) responses of the quadriceps during muscular contractions to exhaustion were computed and analyzed by analysis of variance and polynomial regression analyses.
Participants performed maximum flexion-extension movements at 180°/s until volitional exhaustion, rested for 2 minutes, and then completed a second bout of movements until exhaustion. Torque and SEMG/SMMG median frequencies and amplitudes were examined at 9 points across repetitions completed.
(1) Torque decreased precipitously; (2) SEMG amplitude displayed an initial increase, then a steady decrease, and SMMG amplitude showed a continuous decrease; and (3) SEMG and SMMG median frequencies displayed a continual decrease over repetitions completed. Fractional polynomial and quadratic models explained the fatigue process with the highest precision.
Changes in electrical and mechanical properties of the quadriceps during fatigue reflect alterations in neuromuscular activation strategies and/or muscle wisdom. SEMG frequency modeled muscle fatigue more effectively than amplitude, whereas SMMG frequency and amplitude were equally effective.
通过方差分析和多项式回归分析,计算并分析了股四头肌在肌肉收缩至疲劳过程中的表面肌电图(SEMG)和机械肌电图(SMMG)反应。
参与者以180°/秒的速度进行最大屈伸运动,直至自觉疲劳,休息2分钟,然后完成第二轮运动直至疲劳。在完成的重复运动过程中的9个时间点检查扭矩以及SEMG/SMMG的中位频率和幅度。
(1)扭矩急剧下降;(2)SEMG幅度最初增加,然后稳定下降,而SMMG幅度持续下降;(3)在完成的重复运动过程中,SEMG和SMMG的中位频率持续下降。分数多项式和二次模型对疲劳过程的解释精度最高。
股四头肌在疲劳过程中电和机械特性的变化反映了神经肌肉激活策略和/或肌肉机能的改变。SEMG频率比幅度更有效地模拟肌肉疲劳,而SMMG频率和幅度同样有效。