Abstract
BACKGROUND: Teleorthodontics may offer benefits to both patients and providers in terms of accessibility, efficiency, and quality of care. Therefore, there is an increasing need for accurate, noninvasive monitoring technologies. The present study evaluated the accuracy of a mobile device for four-dimensional imaging in capturing dynamic facial movements and its potential application in orthodontic patients with severe dentofacial deformities. METHODS: In this prospective clinical study, facial movements of 30 adult orthodontic patients (dentofacial deformity: n = 20, controls: n = 10) were captured to evaluate the accuracy of a 4D mobile camera system. Imaging was conducted via Intel RealSense D415 in three settings: (1) with high-accuracy preset, (2) with medium-density presets, and (3) with additional tracking software. The stationary system Canfield Vectra H5 served as the gold standard. Each patient was asked to perform three movements: maximum smiling, lip pursing, and cheek puffing. Accuracy was assessed by the root mean square (RMS). RESULTS: In total, 270 4D sequences were analyzed. Overall, the RMS between the 4D sequences and the gold standard were smaller than 1 mm (p < .001). The (a) high-accuracy setting results in a significantly lower RMS than does the (b) medium-density setting (p < .001). Setting (c) resulted in higher RMS values for lip pursing and cheek puffing than setting (a) or (b). Among the movements, smiling presented the greatest RMS, whereas lip pursing and cheek puffing presented similarly small differences. Class-wise comparisons did not reveal evidence of differences. CONCLUSION: The present study demonstrated that the portable 4D camera system achieved sub-millimeter accuracy in patients with dentofacial deformities. Accuracy was influenced by the recording preset, whereas additional software did not improve performance. Within the limits of this pilot study, the device showed adequate recording quality to support feasibility in teleorthodontic applications for capturing facial dynamics. Future research should evaluate its usability, cost-effectiveness, and potential integration with artificial intelligence to extend clinical applications.