Evidence map›Paper›PMID 41157543›Full record

ArticleSensors (Basel, Switzerland)2025

Intelligent Dental Handpiece: Real-Time Motion Analysis for Skill Development.

Mohamed Sallam, Yousef Salah, Yousef Osman, Ali Hegazy, Esraa Khatab, Omar Shalash

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

6 authors.

Mohamed SallamCollege of Artificial Intelligence, Arab Academy for Science, Technology and Maritime Transport, Alamin 51718, Egypt.ORCID 0009-0004-3280-5396
Yousef SalahCollege of Artificial Intelligence, Arab Academy for Science, Technology and Maritime Transport, Alamin 51718, Egypt.ORCID 0009-0002-2598-0060
Yousef OsmanCollege of Artificial Intelligence, Arab Academy for Science, Technology and Maritime Transport, Alamin 51718, Egypt.
Ali HegazyCollege of Artificial Intelligence, Arab Academy for Science, Technology and Maritime Transport, Alamin 51718, Egypt.
Esraa KhatabSchool of Mathematical and Computer Sciences, Heriot-Watt University, Dubai P.O. Box 501745, United Arab Emirates.ORCID 0000-0002-8006-7699
Omar ShalashArtificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman P.O. Box 346, United Arab Emirates.ORCID 0000-0002-7613-2064

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modern dental education increasingly calls for smarter tools that combine precision with meaningful feedback. In response, this study presents the Intelligent Dental Handpiece (IDH), a next-generation training tool designed to support dental students and professionals by providing real-time insights into their techniques. The IDH integrates motion sensors and a lightweight machine learning system to monitor and classify hand movements during practice sessions. The system classifies three motion states: Alert (10°-15° deviation), Lever Range (0°-10°), and Stop Range (>15°), based on IMU-derived features. A dataset collected from 61 practitioners was used to train and evaluate three machine learning models: Logistic Regression, Random Forest, Support Vector Machine (Linear RBF, Polynomial kernels), and a Neural Network. Performance across models ranged from 98.52% to 100% accuracy, with Random Forest and Logistic Regression achieving perfect classification and AUC scores of 1.00. Motion features such as Deviation, Take Time, and Device type were most influential in predicting skill levels. The IDH offers a practical and scalable solution for improving dexterity, safety, and confidence in dental training environments.

Indexed as

Education, DentalHandHumansLogistic ModelsMachine LearningMotionNeural Networks, ComputerSupport Vector Machinedental skill assessmentintelligent dental handpiecemotion classificationreal-time feedback

Identifiers

PMID41157543
PMCPMC12567667

What OpenQuestion holds

Textmetadata
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.