Time Course of Neuromuscular Fatigue During Different Resistance Exercise Loadings in Power Athletes, Strength Athletes, and Nonathletes

Author:

Kotikangas Johanna12,Walker Simon12,Peltonen Heikki123,Häkkinen Keijo12

Affiliation:

1. Biology of Physical Activity, Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland;

2. NeuroMuscular Research Center, Jyväskylä, Finland; and

3. Sport Business, School of Business, Jamk University of Applied Science, Jyväskylä, Finland

Abstract

Abstract Kotikangas, J, Walker, S, Peltonen, H, and Häkkinen, K. Time course of neuromuscular fatigue during different resistance exercise loadings in power athletes, strength athletes, and nonathletes. J Strength Cond Res 38(7): 1231–1242, 2024—Training background may affect the progression of fatigue and neuromuscular strategies to compensate for fatigue during resistance exercises. Thus, our aim was to examine how training background affects the time course of neuromuscular fatigue in response to different resistance exercises. Power athletes (PA, n = 8), strength athletes (SA, n = 8), and nonathletes (NA, n = 7) performed hypertrophic loading (HL, 5 × 10 × 10RM), maximal strength loadings (MSL, 7 × 3 × 3RM) and power loadings (PL, 7 × 6 × 50% of 1 repetition maximum) in back squat. Average power (AP), average velocity (VEL), surface electromyography (sEMG) amplitude (sEMGRMS), and sEMG mean power frequency (sEMGMPF) were measured within all loading sets. During PL, greater decreases in AP occurred from the beginning of SET1 to SET7 and in VEL to both SET4 and SET7 in NA compared with SA (p < 0.01, g > 1.84). During HL, there were various significant group × repetition interactions in AP within and between sets (p < 0.05, ηp 2 > 0.307), but post hoc tests did not indicate significant differences between the groups (p > 0.05, g = 0.01–0.93). During MSL and HL, significant within-set and between-set decreases occurred in AP (p < 0.001, ηp 2 > 0.701) and VEL (p < 0.001, ηp 2 > 0.748) concurrently with increases in sEMGRMS (p < 0.01, ηp 2 > 0.323) and decreases in sEMGMPF (p < 0.01, ηp 2 > 0.242) in all groups. In conclusion, SA showed fatigue resistance by maintaining higher AP and VEL throughout PL. During HL, PA tended to have the greatest initial fatigue response in AP, but between-group comparisons were nonsignificant despite large effect sizes (g > 0.8). The differences in the progression of neuromuscular fatigue may be related to differing neural activation strategies between the groups, but further research confirmation is required.

Funder

Emil Aaltosen Säätiö

Suomen Urheilututkimussäätiö

Publisher

Ovid Technologies (Wolters Kluwer Health)

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