Introduction: Injuries of the anterior cruciate ligament (ACL) commonly occur during complex game situations when the athlete encounters multiple factors such as ball, opponent, field position, and game strategy (Grooms et al., 2018). Many of the current traditional injury screening programs are performed within a predictable, fixed or ‘closed’ environment which do not represent real game situations that require high neurocognitive demands (Dingenen & Gokeler, 2017; Grooms et al., 2018). A complementary approach to lab-based settings is necessary to incorporate the demands of the complex athletic environments. By using wearable sensor technology, we aim to develop an on-field injury screening test in elite youth male soccer players. Investigating the individual differences in motor coordination patterns of the players during sport-specific tasks might enhance our understanding of how ACL injuries occur. Hypotheses: We hypothesized that the motor coordination patterns of the players would be affected when they perform under different conditions manipulated with constraints (task and environmental). Methods: A football-specific test setup was created to analyse the kinematic and performance measures of a group of 17 male youth elite football players aged 15 years (height = 164 ± 9 cm, mass = 50.9± 7.4 kg). The players were grouped into two and measured on two consecutive days. All the players were instructed to complete the test setup (4 conditions, 5 trials) as fast as possible. Condition 1 includes no constraint, condition 2 includes a task constraint (football dummies), condition 3 includes an environmental constraint (stroboscopic glasses) (SENAPTEC, Beaverton, Oregon) and condition 4 includes both task and environmental constraints. 3-D kinematics of the hip, knee, ankle joints were captured using Xsens wearable full-body sensor suits (Xsens, MVN Link version, Enschede, The Netherlands). MATLAB (MATLAB R2019a, The MathWorks Inc., Massachusetts) was used to process and analyse the kinematic data. Data from condition 1 was determined as reference behavior/condition to be compared to other conditions. Kinematic data are presented in attitude vectors (ATV). Results: In total, 81% of the players demonstrated a significant difference (P < 0.05) in angles of hip, knee and ankle joints when performing under different conditions. The percentage of players with increased comparison-based joint movements as follows; condition 1 to condition 2 comparison; 41% hip flexion, 59% hip extension, 53% hip abduction, 47% hip adduction, 62% knee flexion, 38% knee extension, 59% knee abduction, 41% knee adduction, 47% ankle dorsiflexion, 53% ankle plantarflexion, condition 1 to condition 3 comparison; 35% hip flexion, 65% hip extension, 47% hip abduction, 53% hip adduction, 50% knee flexion, 50% knee extension, 41% knee abduction, 59% knee adduction, 59% ankle dorsiflexion, 41% ankle plantarflexion and condition 1 to condition 4 comparison; 31% hip flexion, 69% hip extension, 38% hip abduction, 62% hip adduction, 60% knee flexion, 40% knee extension, 44% knee abduction, 56% knee adduction, 69% ankle dorsiflexion, 31% ankle plantarflexion. Conclusion: The result of this pilot study demonstrated that manipulating task with different constraints caused significant changes in players’ motor coordination patterns which supported the hypothesis of our study. Our findings suggest to develop ACL injury screening tests in a sport-specific setting.
Exercise Prescription for a Patient 3 Months After Hip Fracture