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Measuring Maxillary Posterior Tooth Movement: A Model Assessment using Palatal and Dental Superimposition
Published on: February 23, 2024
Development of a novel statistical model for mandibular kinematics
Kazuo Hayashi1, Itaru Mizoguchi, Seung-Pyo Lee
1Division of Orthodontics and Dentofacial Orthopedics, Department of Oral Growth and Development, School of Dentistry, Health Sciences University of Hokkaido, Kanazawa 1757, Ishikari-Tobetsu, Hokkaido 061-0293, Japan. kazu@hoku-iryo-u.ac.jp
This study introduces a novel statistical method for analyzing chewing function in patients with anterior crossbite. The new approach accurately predicts population average chewing cycles, reducing subjective estimation in analysis.
Area of Science:
- Biomedical Engineering
- Statistics
- Orthodontics
Background:
- Masticatory function analysis requires robust statistical methods.
- Orthognathic surgery impacts jaw movement and chewing efficiency.
- Previous methods for analyzing chewing cycles may involve subjective estimations.
Purpose of the Study:
- To establish a new statistical method for analyzing masticatory function.
- To develop a predictive statistical model for population average chewing cycles.
- To compare chewing movements in patients with anterior crossbite post-orthognathic surgery with controls.
Main Methods:
- Utilized an opto-electronic motion-analysis system to measure chewing movement.
- Employed a combination of spline functions with random coefficients and self-modeling regression (SEMOR) extended to three dimensions.
- Focused on the mandibular incisor point as the target for jaw movement analysis.
Main Results:
- Developed a statistical model capable of predicting population average curves for chewing cycles.
- Identified significant differences in chewing patterns between the patient and control groups in specific areas.
- The spline function and SEMOR combination effectively minimized subjective interpretation.
Conclusions:
- The proposed statistical method, combining spline functions and SEMOR, offers an objective approach to analyzing masticatory function.
- This method provides a reliable way to predict representative chewing cycles, particularly in patient populations undergoing orthognathic surgery.
- The findings highlight the utility of advanced statistical modeling in understanding complex biomechanical functions like chewing.
