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Related Concept Videos

Assessment of the Mouth

Assessment of the Mouth

A thorough mouth assessment, including inspection and palpation of the lips, gums, tongue, tonsils, uvula, and pharynx, is crucial in detecting potential health issues. Diseases ranging from oral cancer to systemic conditions like diabetes could be identified early through careful oral examination. This article provides a detailed guide on conducting a comprehensive mouth assessment.
Mouth Inspection
The inspection begins with visually examining the mouth for symmetry, color, and size.

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Related Experiment Video

Updated: May 13, 2026

Mimicking and Measuring Occlusal Erosive Tooth Wear with the "Rub&Roll" and Non-contact Profilometry

Mimicking and Measuring Occlusal Erosive Tooth Wear with the "Rub&Roll" and Non-contact Profilometry

Published on: February 2, 2018

Novel software for quantitative evaluation and graphical representation of masticatory efficiency.

D J Halazonetis¹, M Schimmel, G S Antonarakis

¹Department of Orthodontics, School of Dentistry, University of Athens, Greece. dhal@dhal.com

Journal of Oral Rehabilitation

|March 5, 2013

Summary

ViewGum software offers a simple, valid method for assessing chewing efficiency using a two-colour gum test. It analyzes colour blending to quantify masticatory performance, aiding clinical evaluation.

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Last Updated: May 13, 2026

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Area of Science:

Biomedical Engineering
Dental Science
Image Analysis

Background:

Chewing gum colour blending is a clinical tool for assessing chewing efficiency.
Existing software for this test is complex and lacks automated results visualization.
There's a need for improved methods to evaluate masticatory difficulties.

Purpose of the Study:

To validate ViewGum, a new image analysis software for evaluating chewing boli.
To establish a baseline graph for masticatory efficiency in healthy individuals.
To assess the software's utility in clinical settings.

Main Methods:

Utilized a two-colour chewing gum mixing ability test.
Applied novel image analysis software (ViewGum) to evaluate boli.
Analyzed hue variation and standard deviation of hue (SDHue) across chewing cycles.
Performed regression analysis on log-transformed SDHue values.

Main Results:

Image analysis showed a significant decrease in hue variation with increased chewing cycles.
Standard deviation of hue (SDHue) was significantly different across all chewing cycles.
A strong correlation (r² = 0.94, P < 0.01) was found between SDHue and chewing cycles.

Conclusions:

ViewGum software simplifies the two-colour chewing gum test for clinical use.
The software provides speed, ease of use, and immediate clinical insights.
ViewGum is a valid tool for evaluating masticatory efficiency.