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Biomechanical Risk Factors of Injury-Related Single-Leg Movements in Male Elite Youth Soccer Players
(2022)
Altered movement patterns during single-leg movements in soccer increase the risk of lower-extremity non-contact injuries. The identification of biomechanical parameters associated with lower-extremity injuries can enrich knowledge of injury risks and facilitate injury prevention. Fifty-six elite youth soccer players performed a single-leg drop landing task and an unanticipated side-step cutting task. Three-dimensional ankle, knee and hip kinematic and kinetic data were obtained, and non-contact lower-extremity injuries were documented throughout the season. Risk profiling was assessed using a multivariate approach utilising a decision tree model (classification and regression tree method). The decision tree model indicated peak knee frontal plane angle, peak vertical ground reaction force, ankle frontal plane moment and knee transverse plane angle at initial contact (in this hierarchical order) for the single-leg landing task as important biomechanical parameters to discriminate between injured and non-injured players. Hip sagittal plane angle at initial contact, peak ankle transverse plane angle and hip sagittal plane moment (in this hierarchical order) were indicated as risk factors for the unanticipated cutting task. Ankle, knee and hip kinematics, as well as ankle and hip kinetics, during single-leg high-risk movements can provide a good indication of injury risk in elite youth soccer players.
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.
The compliant nature of distal limb muscle-tendon units is traditionally considered suboptimal in explosive movements when positive joint work is required. However, during accelerative running, ankle joint net mechanical work is positive. Therefore, this study aims to investigate how plantar flexor muscle-tendon behavior is modulated during fast accelerations. Eleven female sprinters performed maximum sprint accelerations from starting blocks, while gastrocnemius muscle fascicle lengths were estimated using ultrasonography. We combined motion analysis and ground reaction force measurements to assess lower limb joint kinematics and kinetics, and to estimate gastrocnemius muscle-tendon unit length during the first two acceleration steps. Outcome variables were resampled to the stance phase and averaged across three to five trials. Relevant scalars were extracted and analyzed using one-sample and two-sample t-tests, and vector trajectories were compared using statistical parametric mapping. We found that an uncoupling of muscle fascicle behavior from muscle-tendon unit behavior is effectively used to produce net positive mechanical work at the joint during maximum sprint acceleration. Muscle fascicles shortened throughout the first and second steps, while shortening occurred earlier during the first step, where negative joint work was lower compared with the second step. Elastic strain energy may be stored during dorsiflexion after touchdown since fascicles did not lengthen at the same time to dissipate energy. Thus, net positive work generation is accommodated by the reuse of elastic strain energy along with positive gastrocnemius fascicle work. Our results show a mechanism of how muscles with high in-series compliance can contribute to net positive joint work.
Objective: To identify and evaluate the evidence of the most relevant running-related risk factors (RRRFs) for running-related overuse injuries (ROIs) and to suggest future research directions.
Design: Systematic review considering prospective and retrospective studies. (PROSPERO_ID: 236832)
Data sources: Pubmed. Connected Papers. The search was performed in February 2021.
Eligibility criteria: English language. Studies on participants whose primary sport is running addressing the risk for the seven most common ROIs and at least one kinematic, kinetic (including pressure measurements), or electromyographic RRRF. An RRRF needed to be identified in at least one prospective or two retrospective studies.
Results: Sixty-two articles fulfilled our eligibility criteria. Levels of evidence for specific ROIs ranged from conflicting to moderate evidence. Running populations and methods applied varied considerably between studies. While some RRRFs appeared for several ROIs, most RRRFs were specific for a particular ROI. The biomechanical measurements performed in many studies would have allowed for consideration of many more RRRFs than have been reported, highlighting a potential for more effective data usage in the future.
Conclusion: This study offers a comprehensive overview of RRRFs for the most common ROIs, which might serve as a starting point to develop ROI-specific risk profiles of individual runners. Future work should use macroscopic (big data) approaches involving long-term data collections in the real world and microscopic approaches involving precise stress calculations using recent developments in biomechanical modelling. However, consensus on data collection standards (including the quantification of workload and stress tolerance variables and the reporting of injuries) is warranted.
Activities for rehabilitation and prevention are often lengthy and associated with pain and frustration. Their playful enrichment (hereafter: gamification) can counteract this, resulting in so-called “exergames”. However, in contrast to games designed solely for entertainment, the increased motivation and immersion in gamified training can lead to a reduced perception of pain and thus to health deterioration. Therefore, it is necessary to monitor activities continuously. However, only an AI-based system able to generate autonomous interventions could vacate the therapists’ costly time and allow better training at home. An automated adjustment of the movement training’s difficulty as well as individualized goal setting and control are essential to achieve such autonomy. This article’s contribution is two-fold: (1) We portray the potentials of gamification in the health area. (2) We present a framework for smart rehabilitation and prevention training allowing autonomous, dynamic, and gamified interactions.
In diesem Artikel werden die neuesten Entwicklungen in der Forschungsgruppe um Herrn Prof. Dr. Wendt vorgestellt. Es wird der Einsatz des neuen 3-D-Druckers der Firma Neotech, sowie die neuesten Entwicklungen im Leuchtturmprojekt Flitzmo beschrieben. Zudem konnte dieses Jahr mit dem Projekt zum Einsatz von Robotik im Bereich Assisted Living begonnen werden.
In pandemic times, the possibilities for conventional sports activities are severely limited; many sports facilities are closed or can only be used with restrictions. To counteract this lack of health activities and social exchange, people are increasingly adopting new digital sports solutions—a behavior change that had already started with the trend towards fitness apps and activity trackers. Existing research suggests that digital solutions increase the motivation to move and stay active. This work further investigates the potentials of digital sports incorporating the dimensions gender and preference for team sports versus individual sports. The study focuses on potential users, who were mostly younger professionals and academics. The results show that the SARS-CoV-19 pandemic had a significant negative impact on sports activity, particularly on persons preferring team sports. To compensate, most participants use more digital sports than before, and there is a positive correlation between the time spent physically active during the pandemic and the increase in motivation through digital sports. Nevertheless, there is still considerable skepticism regarding the potential of digital sports solutions to increase the motivation to do sports, increase performance, or raise a sense of team spirit when done in groups.
This study aims to investigate the individual response concerning BRFs for AT when the mid-sole hardness underneath the rearfoot was systematically altered. We first identified FGs based on the footwear condition that minimised the risk for AT across BRFs. We then tested the FGs for differences in anthropometrics, footwear comfort, and running characteristics.