Solent University, Department of Sport and Health, Southampton, UK.
Manchester Metropolitan University, Musculoskeletal Sciences and Sports Medicine Research Centre, Manchester Institute of Sport, Manchester, UK.
J Electromyogr Kinesiol. 2023 Oct;72:102810. doi: 10.1016/j.jelekin.2023.102810. Epub 2023 Aug 2.
Surface EMG (sEMG) has been used to compare loading conditions during exercise. Studies often explore mean/median frequencies. This potentially misses more nuanced electrophysiological differences between exercise tasks. Therefore, wavelet-based analysis was used to evaluate electrophysiological characteristics in the sEMG signal of the quadriceps under both higher- and lower-torque (70 % and 30 % of MVC, respectively) isometric knee extension performed to momentary failure. Ten recreationally active adult males with previous resistance training experience were recruited. Using a within-session, repeated-measures, randomised crossover design, participants performed isometric knee extension whilst sEMG was collected from the vastus medialis (VM), rectus femoris (RF) and vastus lateralis (VL). Mean signal frequency showed similar characteristics in each condition at momentary failure. However, individual wavelets revealed different frequency component changes between the conditions. All frequency components increased during the low-torque condition. But low-frequency components increased, and high-frequency components decreased, in intensity throughout the high-torque condition. This resulted in convergence of the low-torque and high-torque trial wavelet characteristics towards the end of the low-torque trial. Our results demonstrate a convergence of myoelectric signal properties between low- and high-torque efforts with fatigue via divergent signal adaptations. Further work should disentangle factors influencing frequency characteristics during exercise tasks.
表面肌电图(sEMG)已被用于比较运动过程中的负荷条件。研究通常探讨平均/中位数频率。这可能会错过运动任务之间更细微的电生理差异。因此,使用基于小波的分析来评估在分别以 70%和 30%最大肌力(MVC)进行的短暂力竭的等长膝关节伸展过程中股四头肌的 sEMG 信号中的电生理特征。招募了 10 名具有既往抗阻训练经验的休闲成年男性。使用单次会话、重复测量、随机交叉设计,参与者在进行等长膝关节伸展时收集股直肌(RF)、股外侧肌(VL)和股内侧肌(VM)的 sEMG。在瞬间失败时,每个条件下的平均信号频率均表现出相似的特征。然而,个体小波揭示了条件之间不同的频率分量变化。在低扭矩条件下,所有频率分量均增加。但是,在高扭矩条件下,低频分量增加,高频分量减少,强度降低。这导致低扭矩和高扭矩试验的小波特征在低扭矩试验结束时趋于收敛。我们的结果表明,随着疲劳的出现,通过信号的发散适应,低扭矩和高扭矩努力之间的肌电信号特性会收敛。进一步的工作应该梳理在运动任务中影响频率特征的因素。