Evidence map›Paper›PMID 37905197›Full record

ArticleHand therapy2022

A system for automated acquisition of digital flexion using a 3-D camera and custom gantry.

David M Brogan, Aws Anaz, Marjorie Skubic, Christopher J Dy, Jay Bridgeman

Open access · greenAbstract read
In one paragraph

Article in Hand therapy, 2022. 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, top 86% of its field
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, 1 citations in OpenAlex.

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

5 authors at 2 institutions in 1 country.

David M BroganDepartment of Orthopedic Surgery, Washington University in St. Louis, St Louis, MO, USA.ORCID https://orcid.org/0000-0001-6259-4885
Aws AnazDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.ORCID https://orcid.org/0000-0002-9648-7049
Marjorie SkubicDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.
Christopher J DyDepartment of Orthopedic Surgery, Washington University in St. Louis, St Louis, MO, USA.
Jay BridgemanDepartment of Orthopedic Surgery, University of Missouri, Columbia, MO, USA.
University of Missouri · USWashington University in St. Louis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Automated measurement of digital range of motion (ROM) may improve the accuracy of reporting and increase clinical efficiency. We hypothesize that a 3-D camera on a custom gantry will produce ROM measurements similar to those obtained with a manual goniometer. Methods: A 3-D camera mounted on a custom gantry, was mechanized to rotate 200° around a platform. The video was processed to segment each digit and calculate joint angles in people with no history of any hand conditions or surgery to validate the system. A second-generation prototype was then assessed in people with different hand conditions. Metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joint flexion were measured repeatedly with a goniometer and the automated system. The average difference between manual and automatic measurements was calculated along with intraclass correlation coefficients (ICC). Results: In the initial validation, 1,488 manual and 1,488 automated joint measurements were obtained and the measurement algorithm was refined. In people with hand conditions, 688 manual and 688 automated joint measurements were compared. Average acquisition time was 7 s per hand, with an additional 2-3 s required for data processing. ICC between manual and automated data in the clinical study ranged from 0.65 to 0.85 for the MCP joints, and 0.22 to 0.66 for PIP joints. Discussion: The automated system resulted in rapid data acquisition, with reliability varying by type of joint and location. It has the potential to improve efficiency in the collection of physical exam findings. Further developments of the system are needed to measure thumb and distal phalangeal motions.

Indexed as

3-D cameraautomated range of motionmeasurement

Identifiers

PMID37905197
PMCPMC10588428
OpenAlexW4283318896

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.