Evidence map›Paper›PMID 42490640›Full record

ArticlePloS one2026

Validation of markerless human pose estimation methods for clinical assessment of elbow range of motion.

David Rode, Romina Willi, Eva Schulz, Tim Schneller, Philipp Moroder, Laurent Audigé, Mario Bizzini, Nicola A Maffiuletti, Peter Wolf, Robert Riener

Abstract readValidation Study
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

10 authors.

David RodeSensory-Motor Systems Lab, ETH Zurich, Zurich, Switzerland.ORCID https://orcid.org/0000-0001-9619-8821
Romina WilliHuman Performance Lab, Schulthess Klinik, Zurich, Switzerland.ORCID https://orcid.org/0000-0003-3453-4476
Eva SchulzKardinal Schwarzenberg Klinikum, Schwarzach im Pongau, Austria.ORCID https://orcid.org/0009-0009-4885-6477
Tim SchnellerHuman Performance Lab, Schulthess Klinik, Zurich, Switzerland.ORCID https://orcid.org/0009-0007-6949-9849
Philipp MoroderHuman Performance Lab, Schulthess Klinik, Zurich, Switzerland.
Laurent AudigéResearch and Development, Schulthess Klinik, Zurich, Switzerland.
Mario BizziniHuman Performance Lab, Schulthess Klinik, Zurich, Switzerland.
Nicola A MaffiulettiHuman Performance Lab, Schulthess Klinik, Zurich, Switzerland.
Peter WolfSensory-Motor Systems Lab, ETH Zurich, Zurich, Switzerland.
Robert RienerSensory-Motor Systems Lab, ETH Zurich, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinicians rely on the assessment of joint range of motion to determine the necessity of clinical interventions and to track rehabilitation progress. They often perform visual assessments of these joint angles due to limited time for longer but more accurate methods. Markerless monocular human pose estimation methods could help reduce the workload of physicians in clinical practice, allow patients to conduct regular assessments remotely, and be used to provide reliable assessments in the absence of expert raters, but they have not been validated extensively on clinical populations. We measured the elbow flexion and extension ranges of motion of 46 patients with shoulder and elbow pathologies. These values were assessed by RTMW and HSMR, two different monocular pose estimation methods, and an experienced physician who performed visual assessments. A state-of-the-art passive-marker optical motion capture system was used as the reference system. For elbow flexion, HSMR outperformed visual assessment. HSMR had a higher concordance correlation coefficient of 0.92 and a lower minimal detectable change of 6.74° as determined by a concordance analysis and a linear mixed-effects model. Conversely, for elbow extension, visual assessment outperformed both markerless methods. RTMW was the best-performing markerless method with a concordance correlation coefficient of 0.83 and a minimal detectable change of 7.93°. Thus, HSMR represented a viable alternative to visual assessment for measuring elbow flexion range of motion in a clinical population, but neither RTMW nor HSMR offered an improvement over visual assessment for measuring elbow extension range of motion.

Indexed as

Elbow JointRange of Motion, ArticularAdultAgedFemaleHumansMaleMiddle AgedMotion CaptureYoung Adult

Identifiers

PMID42490640
PMCPMC13395372

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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.