Evidence map›Paper›PMID 41282424›Full record

ArticleHealthcare technology letters

Augmented Reality With Dynamic Anatomy Modelling for Knee Arthroscopy.

Deokgi Jeung, Hyun-Joo Lee, Hee-June Kim, Hyunseok Choi, Jaesung Hong

Abstract read
In one paragraph

Article in Healthcare technology letters. 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

5 authors.

Deokgi JeungDepartment of Robotics and Mechatronics Engineering DGIST Daegu South Korea.ORCID https://orcid.org/0000-0002-7223-1540
Hyun-Joo LeeDepartment of Orthopaedic Surgery, School of Medicine Kyungpook National University, Kyungpook National University Hospital Daegu South Korea.
Hee-June KimDepartment of Orthopaedic Surgery, School of Medicine Kyungpook National University, Kyungpook National University Hospital Daegu South Korea.
Hyunseok ChoiDIGITRACK Inc. Daegu South Korea.
Jaesung HongDepartment of Robotics and Mechatronics Engineering DGIST Daegu South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research on augmented reality (AR) for knee arthroscopy has not adequately focused on knee flexion during surgery. To overcome major AR errors caused by knee movement, this study presents an association model between the finite-element models of the knee surface and bones to enable dynamic anatomy modelling. The association model allows the displacement of the knee surface elements and the reaction force of the bone elements to interact with each other. During knee flexion, the real-time shape of the knee is captured with a colour and depth camera, and the association model deforms accordingly from the extension to the flexion state. The proposed model was evaluated using computed tomography data from the knees of six participants. The results showed that the association model successfully compensates for the movement of the femur and tibia within an error margin of only 3.85 mm around the drilling area. The proposed model could therefore enable effective AR-based surgical navigation during knee surgeries.

Indexed as

association modelaugmented realityfinite elementknee arthroscopysurgical navigation

Identifiers

PMID41282424
PMCPMC12636265

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.