Evidence map›Paper›PMID 40632973›Full record

ArticleJournal of the American Academy of Orthopaedic Surgeons. Global research & reviews2025

Accuracy of the Automated Range of Motion Observer and Reporter Software for Fully Automated Joint Measurement From Patient Videos.

Sundeep Chakladar, Christopher J Dy, David M Brogan

Abstract read
In one paragraph

Article in Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

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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

3 authors.

Sundeep ChakladarFrom the Department of Orthopaedic Surgery (Chakladar), Washington University School of Medicine in St. Louis, St. Louis, MO, and the Division of Hand and Microsurgery (Dr. Dy, Dr. Brogan), Department of Orthopaedic Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO.
Christopher J Dy

Funding

Establishing The Validity, Responsiveness, And Appropriateness Of Patient-Reported Outcome Measures For Adult Traumatic Brachial Plexus InjuryR01AR079139 · NIAMS · WASHINGTON UNIVERSITY · PI DY, CHRISTOPHER JOHN · 2021 to 2023
$656k
Identification and Imaging of Skeletal Muscle Response to Graded Nerve CrushK08AR080260 · NIAMS · WASHINGTON UNIVERSITY · PI BROGAN, DAVID MICAH · 2022 to 2025
$624k
NIAMS NIH HHS K08 AR080260NIAMS NIH HHS K08AR080260-01NIAMS NIH HHS R01 AR079139NIAMS NIH HHS R01 AR079139-01
6 · The paper itself

Abstract

introductionAccurate assessment of joint range of motion (ROM) is essential for diagnosing and managing upper extremity injuries. Universal goniometers are the most used tools for measuring ROM, but they require skilled observers and are limited by interobserver variability. An automated system for measuring joint range of motion from patient videos could facilitate standardized reporting of outcomes after reconstructive surgery.

methodsAn Automated Range of Motion Observer and Reporter (ARMOR) software was developed as an autonomous, video-based ROM measurement tool leveraging OpenCV pose estimation. ARMOR was used to assess upper extremity range of motion and was validated against photography-based (photogoniometry) and manual goniometry in a cohort of brachial plexus surgery patients.

resultsThe correlation coefficients comparing ARMOR to manual goniometry were above 0.90 for all motion tasks, except for elbow flexion. For shoulder flexion, the mean difference between ARMOR and manual goniometry was more than 14° smaller than the difference for photogoniometry. Mean differences for shoulder abduction were similar between ARMOR and photogoniometry.

conclusionARMOR's accuracy in assessing shoulder ROM, independence from human observer bias, and telemedicine compatibility makes it a promising solution for consistent and accessible ROM assessment. The autonomous nature of the software enhances the data collection workflow for clinical researchers while eliminating interrater variability.

Indexed as

Arthrometry, ArticularRange of Motion, ArticularShoulder JointSoftwareVideo RecordingAdultFemaleHumansMaleObserver Variation

Identifiers

PMID40632973
PMCPMC12440433

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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.