Details

Autor(en) / Beteiligte

• Hama, Yohei
• Sasaki, Yoshiyuki
• Soeda, Hitomi
• Yamaguchi, Kohei
• Okada, Mitsuzumi
• Komagamine, Yuriko
• Sakanoshita, Norimasa
• Hirota, Yusuke
• Emura, Koji
• Minakuchi, Shunsuke

Titel

Accuracy of newly developed color determination application for masticatory performance: Evaluating color-changeable chewing gum

Ist Teil von

• Journal of Prosthodontic Research, 2024, pp.JPR_D_23_00140

Ort / Verlag

Japan: Japan Prosthodontic Society

Erscheinungsjahr

2024

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Purpose: Color-changeable chewing gums are used to evaluate masticatory performance, as measured by a colorimeter or visually based on a color scale. Although anyone can use a color scale, the evaluation accuracy depends on the evaluator. We develop an application that can determine the degree of color change in chewing gum using smartphone images, making color evaluation accurate and easy to measure.Methods: For the application, 60 chewed gum samples were prepared. Two shots were captured using two smartphone models. To create the application algorithm, a formula was developed to approximately map the color value from the smartphone images to the true value using a colorimeter. A basic validation was performed on 60 new samples covering a range of colors, followed by a field validation on 100 healthy dentate participants aged 20–39 years.Results: The intraclass correlation coefficient for two repeated shots had a high value ≥ 0.97 in the basic and field validations, confirming reliability. No significant differences were observed in the paired t-test and Wilcoxon signed-rank test, and a significant and strong correlation (correlation coefficient ≥ 0.92) was observed between the evaluation values using the colorimeter and the basic and field validations. Bland–Altman plots further confirmed the validity of the application.Conclusions: A software application was developed to enable easy, quick, and accurate determination of the masticatory performance of a chewing gum from images taken using a smartphone with highly reliable and validated results.