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Experimental data acquisition and Finite Element Analysis of kinetic aspects of functional occlusion in order to optimize dental reconstrucions

Experimental data acquisition and Finite Element Analysis of kinetic aspects of functional occlusion in order to optimize dental reconstrucions
功能性咬合动力学方面的实验数据采集和有限元分析,以优化牙齿重建
批准号:
280729065
负责人:
Professor Dr. Marc Schmitter
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2016
资助国家:
德国
项目状态:
已结题
起止时间:
2015-12-31 至 2019-12-31

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中文摘要
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英文摘要
Correct occlusion is an essential aspect of the fabrication of dental restorations. Because dental technicians produce prosthetic restorations outside the oral cavity, accurate transfer of movement of the mandible to dental laboratory conditions is mandatory. Dental restorations without interferences and with sufficient chewing ability can then be produced. In recent years prosthetic reconstructions have been increasingly produced by CAD/CAM. This enables special attention to be devoted to the individual functional condition of the patient. This enormous advantage can, however, be exploited only when both kinematic (= motion and deformation) and kinetic (= forces and stresses) data are recorded. Unfortunately, until now, kinematic data, exclusively, have been recorded and, therefore, used for construction of dental restorations. The motion of the teeth, the deformation of the mandible, the deformation of the periodontal gap and the articular disc, including all the tissues involved-during motion and during chewing could not previously be recorded. In addition, individual information about these dynamics during chewing and clenching and/or grinding (bruxism) of the teeth has not been available; such information might be essential, because extraordinarily high eccentric forces are developed during these activities, resulting in a high risk of failure of all ceramic or veneered dental restorations. In this context interference-free occlusion of the restoration, taking into account the aforementioned kinetic aspects, is mandatory. In this study this missing kinetic data would be acquired for 22 healthy subjects, by acquisition of biting/chewing forces, electric muscle activity, jaw movement, and MRI images. These data would enable improvement of an existing finite-element model (FEM) of the stomatognathic system, including the temporomandibular joints, all chewing muscles, the mandible, the teeth, the temporomandibular disc, and the periodontal system. This modification of the FEM, and its expansion for use with extreme geometry would enable simulation of the kinetic aspects of chewing and bruxism of the teeth. Finally, the simulations should result in the CAD/CAM-based reconstruction and production of interference-free occlusion, enabling optimization of occlusal aspects of these restorations, and, consequently, reduced technical complications, for example chipping and delamination of the ceramic restoration. Another objective of the use of these FEM is simulation of the loading of dental implants and such implant-supported suprastructures during chewing/bruxism. Because dental implants are connected rigidly to the bone, occlusal forces cannot be damped as they are for natural teeth; this results in greater stress on the suprastructures and the surrounding bone. On the basis of the results expected from such optimized FE simulations, these aspects can be taken into consideration during CAD/CAM-based manufacture of the suprastructures.
期刊论文(2)
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科研奖励(0)
会议论文
Effects of introducing gap constraints in the masticatory system: A finite element study
在咀嚼系统中引入间隙约束的影响:有限元研究
DOI: 10.1201/9780429265297-2
发表时间: 2018
期刊: Biodental Engineering V
影响因子: --
作者: [S. E. Martinez Choy, J. Lenz, K. Schweizerhof, H. J. Schindler]
通讯作者: H. J. Schindler
DOI: 10.1111/joor.12501
发表时间: 2017-05-01
期刊: JOURNAL OF ORAL REHABILITATION
影响因子: 2.9
作者: [Choy, S. E. Martinez, Lenz, J., Schindler, H. J.]
通讯作者: Schindler, H. J.
Influence of the craniomandibular system on human posture control during dynamic balance tasks
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
复杂数据下半参数转换模型及其在老年慢性病发展中的应用研究
  • 批准号:
    72101261
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    孙韬
  • 依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位: