Surface electromyographic frequency characteristics of the quadriceps differ between continuous high- and low-torque isometric knee extension to momentary failure

• Published in: Journal of electromyography and kinesiology 2023-10, Vol.72, p.102810-102810, Article 102810
• Main Authors: Murphy, Jonathan, Hodson-Tole, Emma, Vigotsky, Andrew D., Potvin, Jim R., Fisher, James P., Steele, James
• Format: Article
• Language: English
• Subjects: Motor unit; Resistance training; sEMG; Wavelets
• ISSN: 1050-6411; 1873-5711
• DOI: 10.1016/j.jelekin.2023.102810

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.