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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.
Non-contact anterior cruciate ligament injuries typically occur during cutting maneuvers and are associated with high peak knee abduction moments (KAM) within early stance. To screen athletes for injury risk or quantify the efficacy of prevention programs, it may be necessary to design tasks that mimic game situations. Thus, this study compared KAMs and ranking consistency of female handball players in three sport-specific fake-and-cut tasks of increasing complexity. The biomechanics of female handball players (n = 51, mean ± SD: 66.9 ± 7.8 kg, 1.74 ± 0.06 m, 19.2 ± 3.4 years) were recorded with a 3D motion capture system and force plates during three standardized fake-and-cut tasks. Task 1 was designed as a simple pre-planned cut, task 2 included catching a ball before a pre-planned cut in front of a static defender, and task 3 was designed as an unanticipated cut with three dynamic defenders involved. Inverse dynamics were used to calculate peak KAM within the first 100 ms of stance. KAM was decomposed into the frontal plane knee joint moment arm and resultant ground reaction force. RANOVAs (α ≤ 0.05) were used to reveal differences in the KAM magnitudes, moment arm, and resultant ground reaction force for the three tasks. Spearman's rank correlations were calculated to test the ranking consistency of the athletes' KAMs. There was a significant task main effect on KAM (p = 0.02; ηp2 = 0.13). The KAM in the two complex tasks was significantly higher (task 2: 1.73 Nm/kg; task 3: 1.64 Nm/kg) than the KAM in the simplest task (task 1: 1.52 Nm/kg). The ranking of the peak KAM was consistent regardless of the task complexity. Comparing tasks 1 and 2, an increase in KAM resulted from an increased frontal plane moment arm. Comparing tasks 1 and 3, higher KAM in task 3 resulted from an interplay between both moment arm and the resultant ground reaction force. In contrast to previous studies, unanticipated cutting maneuvers did not produce the highest KAMs. These findings indicate that the players have developed an automated sport-specific cutting technique that is utilized in both pre-planned and unanticipated fake-and-cut tasks.
Hintergrund: Die markerlose Bewegungserfassung (sog. Motion Capturing) ist eine neu entwickelte Technik, die die Nachteile der bisherigen verwendeten markerbasierten Bewegungserfassung eliminieren und weitere Vorteile bieten soll. Da Kniegelenkmomente in der Frontalebene, insbesondere das Knie-Abduktions-Moment, als einer der größten Risikofaktoren für eine Verletzung des vorderen Kreuzbandes bei Richtungswechseln angesehen werden, ist ein Vergleich der zwei Systeme in diesem Bereich sinnvoll.
Zielsetzung: Evaluation der Vergleichbarkeit des markerlosen Motion Capturing (Theia3D) mit dem markerbasierten Motion Capturing (Qualisys Track Manager) in Bezug auf die Kniegelenkmomente in der Frontalebene bei 90 ° Richtungswechsel
Stichprobe: 20 gesunde Probanden (9 Frauen, 11 Männer; Größe 174,7 ± 8,4 cm; Gewicht 71,1 ± 10 Kg; Alter 24,1 ± 4,3 Jahre)
Methodik: Gleichzeitige Aufnahme von jeweils drei Messungen eines 90° Richtungswechsels pro Proband:In mit acht Miqus Videokameras und 21 Miqus M3 Infrarotkameras. Die Bodenreaktionskraft wurde mittels einer Kraftmessplatte erhoben.
Ergebnisse: Ein signifikanter systematischer Unterschied (p = 0.02) ergab sich für das KAM gesamt. Verglichen zu dem markerbasierten System zeigt das markerlose System ein höheres KAM gesamt (ML: 0.22 ± 0.11 Nm/Kg, MB: 0.07 ± 0.33 Nm/Kg) aber einen niedrigeren peak KAM gesamt (ML: 0.56 ± 0.2 Nm/Kg, MB: 0.68 ± 0.49 Nm/Kg) und peak KAM 100ms (ML: 0.47 ± 0.19 Nm/Kg, MB: 0.62 ± 0.50 Nm/Kg). Des Weiteren wurden große Differenzen innerhalb der Probanden beobachtet.
Schlussfolgerung: Die Ergebnisse veranschaulichen, dass ein direkter Vergleich zwischen den zwei Systemen nicht sinnvoll ist. Dennoch zeigen sie, dass das markerlose System zu plausiblen Ergebnissen führen und mit einer zukünftigen Weiterentwicklung des Systems die Anwendung vielversprechend sein kann.