[Study on quantitative analysis of bracket-induced nonlinear response of labio-cheek soft tissue during the orthodontic process].

In the orthodontics process, intervention and sliding of an orthodontic bracket during the orthodontic process can arise large response of the labio-cheek soft tissue. Soft tissue damage and ulcers frequently happen at the early stage of orthodontic treatment. In the field of orthodontic medicine, qualitative analysis is always carried out through statistics of clinical cases, while quantitative explanation of bio-mechanical mechanism is lacking. For this purpose, finite element analysis of a three-dimensional labio-cheek-bracket-tooth model is conducted to quantify the bracket-induced mechanical response of the labio-cheek soft tissue, which involves complex coupling of contact nonlinearity, material nonlinearity and geometric nonlinearity. Firstly, based on the biological composition characteristics of labio-cheek, a second-order Ogden model is optimally selected to describe the adipose-like material of the labio-cheek soft tissue. Secondly, according to the characteristics of oral activity, a two-stage simulation model of bracket intervention and orthogonal sliding is established, and the key contact parameters are optimally set. Finally, the two-level analysis method of overall model and submodel is used to achieve efficient solution of high-precision strains in submodels based on the displacement boundary obtained from the overall model calculation. Calculation results with four typical tooth morphologies during orthodontic treatment show that: ① the maximum strain of soft tissue is distributed along the sharp edges of the bracket, consistent with the clinically observed profile of soft tissue deformation; ② the maximum strain of soft tissue is reduced as the teeth align, consistent with the clinical manifestation of common damage and ulcers at the beginning of orthodontic treatment and reduced patient discomfort at the end of treatment. The method in this paper can provide reference for relevant quantitative analysis studies in the field of orthodontic medical treatment at home and abroad, and further benefit to the product development analysis of new orthodontic devices.

An Improved Vision Method for Robust Monitoring of Multi-Point Dynamic Displacements with Smartphones in an Interference Environment.

Current research on dynamic displacement measurement based on computer vision mostly requires professional high-speed cameras and an ideal shooting environment to ensure the performance and accuracy of the analysis. However, the high cost of the camera and strict requirements of sharp image contrast and stable environment during the shooting process limit the broad application of the technology. This paper proposes an improved vision method to implement multi-point dynamic displacement measurements with smartphones in an interference environment. A motion-enhanced spatio-temporal context (MSTC) algorithm is developed and applied together with the optical flow (OF) algorithm to realize a simultaneous tracking and dynamic displacement extraction of multiple points on a vibrating structure in the interference environment. Finally, a sine-sweep vibration experiment on a cantilever sphere model is presented to validate the feasibility of the proposed method in a wide-band frequency range. In the test, a smartphone was used to shoot the vibration process of the sine-sweep-excited sphere, and illumination change, fog interference, and camera jitter were artificially simulated to represent the interference environment. The results of the proposed method are compared to conventional displacement sensor data and current vision method results. It is demonstrated that, in an interference environment, (1) the OF method is prone to mismatch the feature points and leads to data deviated or lost; (2) the conventional STC method is sensitive to target selection and can effectively track those targets having a large proportion of pixels in the context with motion tendency similar to the target center; (3) the proposed MSTC method, however, can ease the sensitivity to target selection through in-depth processing of the information in the context and finally enhance the robustness of the target tracking. In addition, the MSTC method takes less than one second to track each target between adjacent frame images, implying a potential for online measurement.