Open Access

Young female handball players represent a high-risk population for anterior cruciate ligament (ACL) injuries. While the external knee abduction moment (KAM) is known to be a risk factor, it is unclear how cutting technique affects KAMs in sport-specific cutting maneuvers. Further, the effect of added game specificity (e.g., catching a ball or faking defenders) on KAMs and cutting technique remains unknown. Therefore, this study aimed: (i) to test if athletes grouped into different clusters of peak KAMs produced during three sport-specific fake-and-cut tasks of different complexities differ in cutting technique, and (ii) to test whether technique variables change with task complexity. Fifty-one female handball players (67.0 ± 7.7 kg, 1.70 ± 0.06 m, 19.2 ± 3.4 years) were recruited. Athletes performed at least five successful handball-specific sidestep cuts of three different complexities ranging from simple pre-planned fake-and-cut maneuvers to catching a ball and performing an unanticipated fake-and-cut maneuver with dynamic defenders. A k-means cluster algorithm with squared Euclidean distance metric was applied to the KAMs of all three tasks. The optimal cluster number of koptimal = 2 was calculated using the average silhouette width. Statistical differences in technique variables between the two clusters and the tasks were analyzed using repeated-measures ANOVAs (task complexity) with nested groupings (clusters). KAMs differed by 64.5%, on average, between clusters. When pooling all tasks, athletes with high KAMs showed 3.4° more knee valgus, 16.9% higher downward and 8.4% higher resultant velocity at initial ground contact, and 20.5% higher vertical ground reaction forces at peak KAM. Unlike most other variables, knee valgus angle was not affected by task complexity, likely due to it being part of inherent movement strategies and partly determined by anatomy. Since the high KAM cluster showed higher vertical center of mass excursions and knee valgus angles in all tasks, it is likely that this is part of an automated motor program developed over the players' careers. Based on these results, reducing knee valgus and downward velocity bears the potential to mitigate knee joint loading and therefore ACL injury risk.

Treadmills are essential to the study of human and animal locomotion as well as for applied diagnostics in both sports and medicine. The quantification of relevant biomechanical and physiological variables requires a precise regulation of treadmill belt velocity (TBV). Here, we present a novel method for time-efficient tracking of TBV using standard 3D motion capture technology. Further, we analyzed TBV fluctuations of four different treadmills as seven participants walked and ran at target speeds ranging from 1.0 to 4.5 m/s. Using the novel method, we show that TBV regulation differs between treadmill types, and that certain features of TBV regulation are affected by the subjects’ body mass and their locomotion speed. With higher body mass, the TBV reductions in the braking phase of stance became higher, even though this relationship differed between locomotion speeds and treadmill type (significant body mass × speed × treadmill type interaction). Average belt speeds varied between about 98 and 103% of the target speed. For three of the four treadmills, TBV reduction during the stance phase of running was more intense (> 5% target speed) and occurred earlier (before 50% of stance phase) unlike the typical overground center of mass velocity patterns reported in the literature. Overall, the results of this study emphasize the importance of monitoring TBV during locomotor research and applied diagnostics. We provide a novel method that is freely accessible on Matlab’s file exchange server (“getBeltVelocity.m”) allowing TBV tracking to become standard practice in locomotion research.

This study aimed to compare a simplified calculation of the knee abduction moment with the traditional inverse dynamics calculation when athletes perform fake-cut maneuvers with different complexities. In the simplified calculation, we multiply the force vector with its lever arm to the knee, projected onto the local coordinate system of the proximal thigh, hence neglecting the inertial contributions from distal segments. We found very strong ranking consistency using Spearman’s rank correlation coefficient when using the simplified method compared to the traditional calculation. Independent of the tasks, the simplified method resulted in higher moments than the inverse dynamics. This was caused by ignoring the moment caused by segment linear acceleration generating a counteracting moment by about 7%. An alternative to the complex calculations of inverse dynamics can be used to investigate the contributions of the GRF magnitude and its lever arm to the knee.

The majority of anterior cruciate ligament (ACL) injuries in team sports are non-contact injuries, with cutting maneuvers identified as high-risk tasks. Young female handball players have been shown to be at greater risk for ACL injuries than males. One risk factor for ACL injuries is the magnitude of the knee abduction moment (KAM). Cutting technique variables on foot placement, overall approach and knee kinematics have been shown to influence the KAM. Since injury risk is believed to increase with increasing task complexity, the purpose of the study was to test the effect of task complexity on technique variables that influence the KAM in female handball players during fake-and-cut tasks.