ArticleFrontiers in bioengineering and biotechnology2024
Evaluation of drop vertical jump kinematics and kinetics using 3D markerless motion capture in a large cohort.
Article in Frontiers in bioengineering and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy and Validity of 3D Markerless Motion Capture Compared to Marker-Based Systems for Lower-Limb Biomechanical Assessment: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Concurrent validation of OpenCap for identifying ACL re-injury risk factors during a drop jump test in a healthy cohort.Scientific reports · 2026Article
- OpenCap vs. LESS: Sport-Specific Profiling of Dynamic Knee Valgus.Journal of clinical medicine · 2025Article
- Comparison of lower limb kinematic and kinetic estimation during athlete jumping between markerless and marker-based motion capture systems.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Introduction: 3D Markerless motion capture technologies have advanced significantly over the last few decades to overcome limitations of marker-based systems, which require significant cost, time, and specialization. As markerless motion capture technologies develop and mature, there is increasing demand from the biomechanics community to provide kinematic and kinetic data with similar levels of reliability and accuracy as current reference standard marker-based 3D motion capture methods. The purpose of this study was to evaluate how a novel markerless system trained with both hand-labeled and synthetic data compares to lower extremity kinematic and kinetic measurements from a reference marker-based system during the drop vertical jump (DVJ) task. Methods: Synchronized video data from multiple camera views and marker-based data were simultaneously collected from 127 participants performing three repetitions of the DVJ. Lower limb joint angles and joint moments were calculated and compared between the markerless and marker-based systems. Root mean squared error values and Pearson correlation coefficients were used to quantify agreement between the systems. Results: Root mean squared error values of lower limb joint angles and joint moments were ≤ 9.61 degrees and ≤ 0.23 N×m/kg, respectively. Pearson correlation values between markered and markerless systems were 0.67-0.98 hip, 0.45-0.99 knee and 0.06-0.99 ankle for joint kinematics. Likewise, Pearson correlation values were 0.73-0.90 hip, 0.61-0.95 knee and 0.74-0.95 ankle for joint kinetics. Discussion: These results highlight the promising potential of markerless motion capture, particularly for measures of hip, knee and ankle rotations. Further research is needed to evaluate the viability of markerless ankle measures in the frontal plane to determine if differences in joint solvers are inducing unanticipated error.
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