A biomechanical approach to study lunge in fence athletes

Abstract

Fencing requires neuromuscular coordination, strength, and power, and it has a high impact on the musculoskeletal system [1–5]. The lunge is the most important strike action. It is produced with explosive power and surprises the opponent to score points. The lunge starts from the armed arm, which must be moved as quickly as possible toward the opponent, combined with lower body movements to provide a boosting action [4]. The present study aims at assessing kinematics and electromyographic differences between tasks and categories. The participants were 28 male and female, élite and recreational fencers, practicing foil and épée. The age ranged from 8 to 35 years old. Anthropometric and biographical information were taken. Kinematics data were acquired using a wearable inertial system BTS G-SENSOR2, positioned on the L5 vertebra. Four wearable EMG probes BTS FREEEMG 1000 were used to detect EMG signal of Deltoideus Anterior (DLTA) and Rectus femoris (RF) both on the armed side; Erector Longissimus muscle (LONG) and Gastrocnemius medialis (GAM), on the opposite one. These devices were synchronized by the acquisition software BTS EMG-Analyzer. Muscles' MVC and two trials of lunge (AF), step forward lunge (AA) and step backward lunge (DA) were taken. Data were processed with MATLAB and Tracker. VWilcoxon’s effect size for continuous variables and prevalence differences for categorical ones. Age and anthropometric measures were statistically different between the two categories (P < 0.05). No statistically significant differences are observed between the sexes, excluding thigh circumference (P < 0.05). The normalized distances and x-axis ROM between tasks and the y-axis ROM in the second trial (AA), the mean normalized muscle activation of DLTA, RF, and GAM between categories were statistically different (P <0.05). No significant statistical differences in muscle activation patterns were observed between different categories. Each correlation coefficient was interpreted based on a previously described classification using similar variables: 0-0.4 (weak), 0.4-0.7 (moderate), and 0.7-1.0 (strong). Table 1 summarizes the results observed from the correlation, the direction of the arrow stands for the direction of correlation (positive or negative), while the number of arrows is the intensity of correlation (weak, moderate, or strong). It is important to emphasize the negative correlation between lunge time and activation intensity of the LONG muscle, as well as the positive correlation between lunge distance and activation intensity of the GAM muscle. Differences have been observed in some kinematic and electromyographic parameters among categories and tasks. No substantial difference in muscle patterns is observed between different categories. Furthermore, correlations have emerged between muscular activity and spatiotemporal variables of movement: a greater rapidity of movement is associated with greater activity of the LONG, because it is balance responsible. A longer lunge distance is related to a greater activity of the GAM (boosting muscle).