JOURNAL ARTICLE
Reliability of measuring mandibular movement and condylar position using an optical jaw registration system.
Published In: International Journal of Computerized Dentistry, 2026, v. 29, n. 1. P. 41 1 of 3
Database: Dentistry & Oral Sciences Source 2 of 3
Authored By: Nebe, Marvin; Fenske, Fabian; Grau, Elisabeth; Schierz, Oliver; Brinkmann, Lisa; Reißmann, Daniel R. 3 of 3
Abstract
The article focuses on evaluating the reliability of an optical digital jaw registration system, the Tizian JMA Optic (zebris Medical, Germany), for measuring mandibular movements and condylar position in healthy adult patients. In a prospective clinical study with 20 participants aged 19 to 77, mandibular movements (mouth opening, protrusion, laterotrusion) and condylar positions were recorded by two calibrated examiners across two appointments about one week apart. Results showed excellent intra- and inter-appointment reliability, with intraclass correlation coefficients (ICCs) of 0.95 for mouth opening, 0.94 for protrusion, 0.87–0.89 for laterotrusion, and 0.98 for condylar position, without significant examiner-related differences. The study concludes that this digital system provides reliable measurements suitable for clinical functional diagnostics and digital prosthetic workflows, while noting that further research is needed to assess its benefits in patient populations with temporomandibular disorders or other vulnerabilities.
Additional Information
- Source:International Journal of Computerized Dentistry. 2026/01, Vol. 29, Issue 1, p41
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2026
- ISSN:1463-4201
- DOI:10.3290/j.ijcd.b6173234
- Accession Number:193108756
- Copyright Statement:Copyright of International Journal of Computerized Dentistry is the property of Quintessence Publishing Company Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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