Effect of acute fatigue on movement variability during squat execution 

Vinyet Solé, Carla Pérez-Chirinos, Victor Toro Román, Bruno Fernández-Valdes, Sara Ledesma, Oriol Teruel, Felipe J. Alviso. 

Research Group in Technology Applied to High Performance and Health (TAARS), Tecnocampus, Department of Health Sciences, Pompeu Fabra University, Mataró (Barcelona, Spain).  

Introduction 

Movement variability is a key indicator for understanding the stability and adaptability of the neuromuscular system. Under fatigue conditions, this variability may be altered, reflecting changes in coordinative capacities. The aim of this study is to analyse how acute fatigue, induced by the Wingate test, affects movement variability during squat execution, by assessing coordinative capacity variables (coefficient of variation and standard deviation) and conditional capacity variables (mean and peak values). Additionally, the ability of two complementary technologies to detect these changes in applied sports contexts is evaluated. 

Keywords 

coordinative fatigue, movement variability, coefficient of variation, accelerometry, force platform, coordinative capacities, conditional capacities, sports technology 

Methods 

Eighteen physically active young adults participated in the study (13 men and 5 women; mean age 25.63 ± 4.07 years). The protocol consisted of four blocks of 30-second squats (PRE, POST 1, POST 2, and POST 3), interspersed with Wingate tests. Vertical force data were recorded using a force platform (Neuroexcellence, 160 Hz) and three-dimensional acceleration data using a mobile device with the Phyphox app (IMU, 100 Hz). Coefficient of variation (CV), standard deviation (SD), mean value, and peak value were calculated for both systems. Inter-limb asymmetries and correlations between technologies were also analysed. 

Results 

Coordinative capacity variables decreased significantly with fatigue. Acceleration CV dropped from 0.645 ± 0.070 (PRE) to 0.552 ± 0.102 (POST 3; p < .001), and SD from 6.99 ± 0.91 to 5.90 ± 1.22 (p < .001). In force data, CV decreased from 0.707 ± 0.134 to 0.594 ± 0.143 (p < .001), and SD from 526.2 ± 147.2 to 441.4 ± 140.0 N (p < .001). Peak force values decreased from 1788.7 ± 383.6 to 1638.1 ± 365.7 N (p ≤ .003), while mean force values remained stable (p = .151). Correlations between the force platform and accelerometry were very high for CV (PRE: r = 0.754; POST 3: r = 0.849) and SD (PRE: r = 0.847; POST 3: r = 0.813; p < .001), and moderate for peak value (r ≈ 0.77). No significant differences were found in inter-limb asymmetries at any of the assessed time points. 

Conclusions 

Acute fatigue reduces movement variability, which may indicate a more stable but potentially less adaptable execution pattern. The strong correlation between the force platform and mobile accelerometry for coordinative capacity variables supports the use of portable technologies as reliable tools for functional fatigue monitoring in real sports settings.