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Journal Article

Citation

Frazer L, Templin T, Eliason TD, Butler C, Hando B, Nicolella D. Front. Bioeng. Biotechnol. 2023; 11: e1293923.

Copyright

(Copyright © 2023, Frontiers Media)

DOI

10.3389/fbioe.2023.1293923

PMID

38125303

PMCID

PMC10731296

Abstract

INTRODUCTION: Non-combat musculoskeletal injuries (MSKIs) during military training significantly impede the US military's functionality, with an annual cost exceeding $3.7 billion. This study aimed to investigate the effectiveness of a markerless motion capture system and full-body biomechanical movement pattern assessments to predict MSKI risk among military trainees.

METHODS: A total of 156 male United States Air Force (USAF) airmen were screened using a validated markerless biomechanics system. Trainees performed multiple functional movements, and the resultant data underwent Principal Component Analysis and Uniform Manifold And Projection to reduce the dimensionality of the time-dependent data. Two approaches, semi-supervised and supervised, were then used to identify at-risk trainees.

RESULTS: The semi-supervised analysis highlighted two major clusters with trainees in the high-risk cluster having a nearly five times greater risk of MSKI compared to those in the low-risk cluster. In the supervised approach, an AUC of 0.74 was produced when predicting MSKI in a leave-one-out analysis.

DISCUSSION: The application of markerless motion capture systems to measure an individual's kinematic profile shows potential in identifying MSKI risk. This approach offers a novel way to proactively address one of the largest non-combat burdens on the US military. Further refinement and wider-scale implementation of these techniques could bring about substantial reductions in MSKI occurrence and the associated economic costs.


Language: en

Keywords

military; biomechanics; functional movement analysis; injury risk assessment; kinematics; markerless motion capture

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