Evidence map›Paper›PMID 42356929›Full record

SynthesisSensors (Basel, Switzerland)2026

Accuracy and Validity of 3D Markerless Motion Capture Compared to Marker-Based Systems for Lower-Limb Biomechanical Assessment: A Systematic Review.

Aditya Chougule, Matthew Dowsett, David Ekundayomi, Ava Machesney, Tomos Mather, Benjamin Gompels, Stephen McDonnell

Abstract readSystematic Review
In one paragraph

Synthesis in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Aditya ChouguleTrauma and Orthopaedics Department, University of Cambridge, Cambridge CB21TN, UK.
Matthew DowsettTrauma and Orthopaedics Department, University of Cambridge, Cambridge CB21TN, UK.ORCID 0009-0007-8108-7230
David EkundayomiTrauma and Orthopaedics Department, University of Cambridge, Cambridge CB21TN, UK.ORCID 0009-0005-1807-6454
Ava MachesneyTrauma and Orthopaedics Department, University of Cambridge, Cambridge CB21TN, UK.ORCID 0009-0007-5892-0116
Tomos MatherTrauma and Orthopaedics Department, University of Cambridge, Cambridge CB21TN, UK.
Benjamin GompelsTrauma and Orthopaedics Department, University of Cambridge, Cambridge CB21TN, UK.
Stephen McDonnellTrauma and Orthopaedics Department, University of Cambridge, Cambridge CB21TN, UK.ORCID 0000-0002-3181-4192

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Marker-based motion capture systems are considered the gold standard for biomechanical analysis of movements associated with anterior cruciate ligament (ACL) injury risk; however, their cost and technical requirements limit their use for large-scale athlete screening. Markerless motion capture has emerged as a potential alternative, using pose estimation algorithms or depth cameras to quantify movement without reflective markers. This systematic review evaluated the accuracy and validity of markerless motion capture systems for measuring lower-limb kinematics during jump-landing tasks commonly used in ACL injury screening. MEDLINE, Embase, and Web of Science were searched from 1990 to March 2025 for studies comparing markerless and marker-based systems in healthy participants. Extracted outcomes included Bland-Altman plots, root mean square error, mean absolute error, Pearson's correlation coefficient, coefficient of multiple correlation, and intraclass correlation coefficient. Across studies, markerless systems demonstrated moderate to high validity for several lower-limb kinematic measures, particularly in the sagittal plane, although validity varied across joints, movement phases, and task complexity. These findings suggest markerless motion capture shows potential for biomechanical assessment in ACL injury screening, but further validation is required before widespread implementation.

Indexed as

Imaging, Three-DimensionalLower ExtremityMotion CaptureAlgorithmsAnterior Cruciate LigamentAnterior Cruciate Ligament InjuriesBiomechanical PhenomenaHumansMovementACL injurybiomechanicsinjury screeninglower-limb kinematicsmarkerless motion capture

Identifiers

PMID42356929
PMCPMC13306381

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.