Background Stiff landing is associated with increased anterior cruciate ligament (ACL) injury risk, especially in young female athletes. As an alternative to a force platform, a tri-axial accelerometer is a useful tool to reflect the magnitude of the ground reaction force exerted during games.
Objective To clarify the movements that require high trunk accelerations and their frequency during badminton games.
Design Observational study.
Setting Youth athletes, local tournament levels.
Participants Forty-five female badminton players [17 junior high school (JHS) and 28 high school (HS) athletes].
Assessment of Risk Factors Movements that generated >4G resultant acceleration were assessed as a risk for ACL injury.
Main Outcome Measurements Frequency and characteristics of the movements that generated >4G acceleration during singles games of badminton.
Results A total of 6,306 movements generated >4G acceleration during an 896-min game duration (7.04 cases/min; 95% confidence interval (CI), 6.87–7.21 cases/min). HS players (7.27 cases/min; 95% CI, 7.05–7.48 cases/min) had a higher incidence of great trunk acceleration compared with JHS players (6.58 cases/min; 95% CI, 6.29–6.87 cases/min). The top three most frequent movements were landing after an overhead stroke (JHS, 1.13 cases/min; HS, 1.58 cases/min), lunging during an under-/side-hand stroke (JHS, 0.98 cases/min; HS, 1.27 cases/min), and cutting from a split stepping (JHS, 0.96 cases/min; HS, 1.29 cases/min).
Conclusions HS athletes had an opportunity to incur exposure to high-loading movements during badminton games, which supports an epidemiological survey’s results that the incidence rate of ACL injury in HS athletes is six times higher than that in JHS athletes. In addition, previously reported mechanisms of ACL injury in badminton (i.e. single-leg landing after an overhead stroke and plant-and-cut manoeuvre after a lunge stepping) were revealed as the high-frequency movements that generated >4G acceleration. This study suggests that video analysis with micro-sensor technology can individually detect the high-loading movements during game-play situations, which contribute to identifying the high-risk athletes from the on-court/field perspective.
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