Author(s): MARINEAU, E., PRUNAULT, C., DUCAS, J., DESCARREAUX, M., ABBOUD, J., Institution: UNIVERSITY OF QUEBEC IN TROIS-RIVIERES, Country: CANADA, Abstract-ID: 265

INTRODUCTION:
Motor variability (MV) reflects how the neuromuscular system adapts to maintain task performance under changing constraints. In sport, experts typically show lower MV during controlled, non-fatiguing tasks, reflecting stable and efficient motor control. However, endurance sports inherently involve muscle fatigue, a strong physiological perturbation known to alter the neuromuscular system. Whether expertise confers greater or lesser MV under fatigue remains unclear. This study examined how cycling expertise shapes MV adaptations during cycling under muscle fatigue. We hypothesized that expert cyclists would display greater MV under fatigue, reflecting a more flexible use of degrees of freedom.
METHODS:
Thirty-two high-skilled cyclists (HS) and 30 low-skilled participants (LS) completed a single-session cycling protocol on a stationary bike, consisting of two 5-min submaximal bouts separated by two 30-s maximal efforts to induce muscle fatigue. MV was assessed before maximal efforts (T1), after maximal efforts (T2), and at the end of the protocol (T3). Surface EMG was recorded from the vastus lateralis, biceps femoris, tibialis anterior, and gastrocnemius, and 3D kinematics were collected to compute trunk and lower-limb angles and cadence. MV was quantified using coefficients of variation (CV). Linear mixed models tested effects of expertise, time, and their interaction.
RESULTS:
Perceived exertion (modified Borg scale) increased from T1 (2.53 ± 0.81) to maximal efforts (8.75 ± 1.40) and remained elevated at T2 (4.47 ± 1.47) and T3 (3.27 ± 1.19) (p < 0.001). EMG median frequency decreased across all muscles (p < 0.05), confirming muscle fatigue. Muscle fatigue altered MV across multiple variables, including cadence CV, vastus lateralis EMG amplitude CV, and trunk frontal angle CV (all p<0.05). Cadence CV increased at T2 and returned to baseline at T3, whereas trunk and knee frontal angle CV remained elevated. Experts showed lower MV in trunk frontal CV (p < 0.001), low-back sagittal CV (p = 0.026), and upper-back sagittal angles CV (p = 0.011), as well as reduced EMG onset CV of the biceps femoris (p = 0.006). Significant group × fatigue interactions were observed for cadence CV and frontal knee angle CV (p < 0.05): HS showed transient increases at T2 followed by recovery, whereas LS exhibited sustained increases.
CONCLUSION:
Muscle fatigue induces transient and sustained changes in MV during cycling. Contrary to our hypothesis, expertise constrains MV not only at baseline but also under fatigue, suggesting that HS rely on stable motor strategies even when physiological capacity declines. In this constrained cyclist–bike system, cadence and frontal knee angle emerge as the primary adjustable strategies through which experts regulate fatigue-related adaptations. Future studies should examine these mechanisms in less constrained sports (e.g., running or throwing), where greater degrees of freedom may allow more flexible motor control adaptations.