Background Joint moments computed using inverse dynamic techniques are important estimators of net joint loads. Joints moments computed from marker position and ground reaction force data filtered using different cut-off frequencies may capture changes in moment magnitudes at a single joint that exceed normal physiological response. Peak external knee abduction moment (KAM) generated during landing (ie, the drop vertical jump, DVJ) predicts anterior cruciate ligament injury risk using marker and force data filtered at different cut-off frequencies. The purpose of the current investigation was to determine the effects of using the same low cut-off frequencies versus different cut-off frequencies on joint moment magnitudes to evaluate if artificial smoothing attenuates actual resultant joint loads related to injury risk. Methods Twenty-two female, high school volleyball players performed three maximum DVJs in a laboratory setting. The average peak KAM was computed for each knee using marker and force data filtered with the same low cut-off frequencies and different cut-off frequencies. Results Peak KAMs were significantly larger using different cut-off frequencies. The order of athletes ranked based on the magnitude of their peak KAMs did not significantly change across all filtering cut-off frequencies. Conclusions The magnitude of peak KAM may differ when the same low or different higher cut-off frequencies are used to filter marker and ground reaction forces (GRF) data collected using standard motion capture equipment. It is not clear to what extent the decrease in peak KAM reported when the same low cut-off frequencies were used was solely due to attenuation of the GRF signal.

Increased BF% and BMI relate to lower composite FMS™ and individual FMS™ test scores, indicating potentially poor movement patterns in larger National Collegiate Athletic Association football athletes. Future research should focus on examining lower extremity-specific FMS™ tasks individually from composite FMS™ scores.

Context Due to the limitations of single-center studies in achieving appropriate sampling with relatively rare disorders, multicenter collaborations have been proposed to achieve desired sampling levels. However, documented reliability of biomechanical data is necessary for multicenter injury-prevention studies and is currently unavailable. Objective To measure the reliability of 3-dimensional (3D) biomechanical waveforms from kinetic and kinematic variables during a single-leg landing (SLL) performed at 3 separate testing facilities. Design Multicenter reliability study. Setting 3 laboratories. Patients 25 female junior varsity and varsity high school volleyball players who visited each facility over a 1-mo period. Intervention Subjects were instrumented with 43 reflective markers to record 3D motion as they performed SLLs. During the SLL the athlete balanced on 1 leg, dropped down off of a 31-cm-high box, and landed on the same leg. Kinematic and kinetic data from both legs were processed from 2 trials across the 3 laboratories. Main Outcome Measures Coefficients of multiple correlations (CMC) were used to statistically compare each joint angle and moment waveform for the first 500 ms of landing. Results Average CMC for lower-extremity sagittal-plane motion was excellent between laboratories (hip .98, knee .95, ankle .99). Average CMC for lower-extremity frontal-plane motion was also excellent between laboratories (hip .98, knee .80, ankle .93). Kinetic waveforms were repeatable in each plane of rotation (3-center mean CMC ≥.71), while knee sagittal-plane moments were the most consistent measure across sites (3-center mean CMC ≥.94). Conclusions CMC waveform comparisons were similar relative to the joint measured to previously published reports of between-sessions reliability of sagittal- and frontal-plane biomechanics performed at a single institution. Continued research is needed to further standardize technology and methods to help ensure that highly reliable results can be achieved with multicenter biomechanical screening models.

Our biodynamics laboratory group has conducted large cohort biomechanical-epidemiological studies targeted at identifying the complex interactions among biomechanical, biological, hormonal, and psychosocial factors that lead to increased risk of anterior cruciate ligament (ACL) injuries. The findings from our studies have revealed highly sensitive and specific predictors for ACL injury. Despite the high incidence of ACL injuries among young athletes, larger cohorts are needed to reveal the underlying mechanistic causes of increased risk for ACL injury. In the current study, we have outlined key factors that contribute to the overall success of multicenter, biomechanical-epidemiological investigations designed to test a larger number of athletes who otherwise could not be recruited, screened, or tested at a single institution. Twenty-five female volleyball players were recruited from a single high school team and tested at three biodynamics laboratories. All athletes underwent three-dimensional motion capture analysis of a drop vertical jump task. Kinematic and kinetic variables were compared within and among laboratories. Reliability of peak kinematic variables was consistently rated good-to-excellent. Reliability of peak kinetic variables was consistently rated goodto-excellent within sites, but greater variability was observed between sites. Variables measured in the sagittal plane were typically more reliable than variables measured in the coronal and transverse planes. This study documents the reliability of biomechanical variables that are key to identification of ACL injury mechanisms and of athletes at high risk. These findings indicate the feasibility of executing multicenter, biomechanical investigations that can yield more robust, reliable, and generalizable findings across larger cohorts of athletes.

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