[Biomechanical screening for injury prevention : The importance of 3D-motion analysis in high performance sports]

Preseason multiple biomechanics testing and dimension reduction for injury risk surveillance in elite female soccer athletes: short-communication

Injury risk is regularly assessed during the preseason in susceptible populations like female soccer players. However, multiple outcomes (high-dimensional dataset) derived from multiple testing may make pattern recognition difficult. Thus, dimension reduction and clustering may be useful for improving injury surveillance when results of multiple assessments tools are available. Thus, we determined the influence of dimension reduction for pattern recognition followed by clustering on multiple biomechanical injury markers in elite female soccer players during preseason. We introduce the use of dimension reduction through linear principal component analysis (PCA), non-linear kernel principal component analysis (k-PCA), t-distributed stochastic neighbor embedding (t-sne), and uniform manifold approximation and projection (umap) for injury markers via grid search. Muscle strength, muscle function, jump technique and power, balance, muscle stiffness, exercise tolerance, and running performance were assessed in an elite female soccer team (n=21) prior to the competitive season. As a result, umap facilitated the injury pattern recognition compared to PCA, k-PCA, and t-sne. One of three patterns was related to a team subgroup with acceptable muscle conditions. In contrast, the other two patterns showed higher injury risk profiles. For our dataset, umap improved injury surveillance through multiple testing characteristics. Dimension reduction and clustering techniques present as useful strategies to analyze subgroups of female soccer players who have different risk profiles for injury.

Association Between Markerless Motion Capture Screenings and Musculoskeletal Injury Risk for Military Trainees: A Large Cohort and Reliability Study

Background:

Markerless motion capture (MMC) systems used to screen for musculoskeletal injury (MSKI) risk have become popular in military and collegiate athletic settings. However, little is known regarding the test-retest reliability or, more importantly, the ability of these systems to accurately identify individuals at risk for MSKI.

Purpose:

To determine the association between scores from a proprietary MMC movement screen test and the likelihood of suffering a subsequent MSKI and establish the test-retest reliability of the MMC system used.

Study Design:

Cohort study; Level of evidence, 3.

Methods:

Trainees for the Air Force Special Warfare program underwent MMC screenings immediately before entering the 8-week training course. MSKI data were extracted from a database for the surveillance period for each trainee. Logistic regression analyses were performed to identify associations between baseline MMC scores and the likelihood of suffering any MSKI or, specifically, a lower extremity MSKI. The test-retest portion of the study collected MMC scores from 10 separate participants performing 4 trials of the standard test procedures. Reliability was assessed using intraclass correlation coefficients by a single rater.

Results:

Overall, 1570 trainees, of whom 800 (51%) suffered an MSKI, were included in the analysis. MMC scores poorly predicted the likelihood of any or a lower extremity MSKI (odds ratio, 1.01-1.02). Further, receiver operating characteristic curve analyses demonstrated poor sensitivity and specificity for prediction of MSKI with MMC scores (area under the curve = 0.53). Finally, intraclass correlation coefficients from the test-retest analysis of MMC scores ranged from 0.157 to 0.602.

Conclusion:

This MMC system displayed poor to moderate test-retest reliability and did not demonstrate the ability to discriminate between individuals who were and were not likely to suffer an MSKI.