Evidence map›Paper›PMID 40277638›Full record

ArticleBiomimetics (Basel, Switzerland)2025

Performance Evaluation of Rapid Entire Body Assessment Using AI-Assisted Ergonomic Analysis in Dentistry.

Benhar Arvind Manohar, Jebakani Devaraj, Chellapandian Maheswaran, Selvan Pugalenthi

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2025. 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
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.

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

4 authors.

Benhar Arvind ManoharDepartment of Mechanical Engineering, Government College of Engineering, Tirunelveli 627007, India.ORCID 0009-0009-9523-3520
Jebakani DevarajDepartment of Mechanical Engineering, Government College of Engineering, Tirunelveli 627007, India.
Chellapandian MaheswaranDepartment of Civil Engineering, Mepco Schlenk Engineering College, Sivakasi 626005, India.ORCID 0000-0003-4284-8678
Selvan PugalenthiDepartment of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi 626005, India.ORCID 0000-0003-1247-0774

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study seeks to automate the Rapid Entire Body Assessment (REBA) in dentistry with Artificial Intelligence (AI) technologies, notably MediaPipe, to improve accuracy and obviate the necessity for expert judgment. This research utilizes time-synchronized videos and averages across frames to mitigate mistakes resulting from visual occlusion and over- or underestimation, respectively. The REBA scores of the observed dentists were evaluated and compared with the conventional single image-based method. Among the evaluated dentists, 83% of dentists are at high risk, and the other 17% of dentists are at very high risk, requiring solutions to lower their REBA scores and prevent musculoskeletal disorders (MSDs). The individual REBA point profiles differed, necessitating a collective study through response surface methodology (RSM) utilizing Design Expert software. The RSM model exhibited substantial results, as indicated by R

Indexed as

artificial intelligencedentistMediaPipemusculoskeletal disordersrapid entire body assessmentRSM

Identifiers

PMID40277638
PMCPMC12024601

What OpenQuestion holds

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LicenceCC BY
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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.