Evidence map›Paper›PMID 32295597›Full record

ArticleBiomedical engineering online2020

Identification of arthropathy and myopathy of the temporomandibular syndrome by biomechanical facial features.

Bruno Coelho Calil, Danilo Vieira da Cunha, Marcus Fraga Vieira, Adriano de Oliveira Andrade, Daniel Antônio Furtado, Douglas Peres Bellomo Junior, Adriano Alves Pereira

Registry-linked trialOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical engineering online, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07486609 (Diagnostic Accuracy of Jaw Motion Analyzer Versus Research Diagnostic Criteria and Magnetic Resonance Imaging for Temporomandibular Disorders), which is not on this map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
2.8field-weighted citation impact, top 11% 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.

NCT07486609 naenrolling by invitationnot on this mapstarted 2025, after this paper: background citation

Diagnostic Accuracy of Jaw Motion Analyzer Versus Research Diagnostic Criteria and Magnetic Resonance Imaging for Temporomandibular Disorders: A Pilot Study

TypeinterventionalSponsorCairo UniversityRan2025 to 2027Enrolled29ConditionsTemporomandibular Disorders (TMDs)ArmsThe Jaw Motion Analyzer (JMA, Zebris, Germany) as the index test, Research Diagnostic Criteria for Temporomandibular Disoders, Magnetic Resonance Imaging
3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Review
  5. Article
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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 at 2 institutions in 1 country.

Bruno Coelho CalilLaboratory of Biomedical Engineering, Faculty of Electrical Engineering, Federal University of Uberlandia, Av. Joao Naves de Avila, 2121, Uberlandia, 38408-100, Brazil. bruno.calil@una.br.ORCID http://orcid.org/0000-0001-6051-9814
Danilo Vieira da CunhaLaboratory of Biomedical Engineering, Faculty of Electrical Engineering, Federal University of Uberlandia, Av. Joao Naves de Avila, 2121, Uberlandia, 38408-100, Brazil.
Marcus Fraga VieiraBioengineering and Biomechanics Laboratory, Federal University of Goias, Av. Esperanca, s/n, Campus Samambaia, Goiania, GO, 74690-900, Brazil.
Adriano de Oliveira AndradeLaboratory of Biomedical Engineering, Faculty of Electrical Engineering, Federal University of Uberlandia, Av. Joao Naves de Avila, 2121, Uberlandia, 38408-100, Brazil.
Daniel Antônio FurtadoLaboratory of Biomedical Engineering, Faculty of Electrical Engineering, Federal University of Uberlandia, Av. Joao Naves de Avila, 2121, Uberlandia, 38408-100, Brazil.
Douglas Peres Bellomo JuniorLaboratory of Biomedical Engineering, Faculty of Electrical Engineering, Federal University of Uberlandia, Av. Joao Naves de Avila, 2121, Uberlandia, 38408-100, Brazil.
Adriano Alves PereiraLaboratory of Biomedical Engineering, Faculty of Electrical Engineering, Federal University of Uberlandia, Av. Joao Naves de Avila, 2121, Uberlandia, 38408-100, Brazil.
Universidade Federal de Uberlândia · BRUniversidade Federal de Goiás · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTemporomandibular disorders (TMDs) are pathological conditions affecting the temporomandibular joint and/or masticatory muscles. The current diagnosis of TMDs is complex and multi-factorial, including questionnaires, medical testing and the use of diagnostic methods, such as computed tomography and magnetic resonance imaging. The evaluation, like the mandibular range of motion, needs the experience of the professional in the field and as such, there is a probability of human error when diagnosing TMD. The aim of this study is therefore to develop a method with infrared cameras, using the maximum range of motion of the jaw and four types of classifiers to help professionals to classify the pathologies of the temporomandibular joint (TMJ) and related muscles in a quantitative way, thus helping to diagnose and follow up on TMD.

methodsForty individuals were evaluated and diagnosed using the diagnostic criteria for temporomandibular disorders (DC/TMD) scale, and divided into three groups: 20 healthy individuals (control group CG), 10 individuals with myopathies (MG), 10 individuals with arthropathies (AG). A quantitative assessment was carried out by motion capture. The TMJ movement was captured with camera tracking markers mounted on the face and jaw of each individual. Data was exported and analyzed using a custom-made software. The data was used to identify and place each participant into one of three classes using the K-nearest neighbor (KNN), Random Forest, Naïve Bayes and Support Vector Machine algorithms.

resultsSignificant precision and accuracy (over 90%) was reached by KNN when classifying the three groups. The other methods tested presented lower values of sensitivity and specificity.

conclusionThe quantitative TMD classification method proposed herein has significant precision and accuracy over the DC/TMD standards. However, this should not be used as a standalone tool but as an auxiliary method for diagnostic TMDs.

Indexed as

FaceMechanical PhenomenaAdolescentAdultBayes TheoremBiomechanical PhenomenaFemaleHumansInfrared RaysMaleMiddle AgedSupport Vector MachineTemporomandibular Joint DisordersYoung AdultKNNQuantitative assessmentTemporomandibular disorderTMDTMJ

Identifiers

PMID32295597
PMCPMC7161015
OpenAlexW3016341271

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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.