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从生物控制论角度识别咀嚼器官肌肉力量。

Identification of mastication organ muscle forces in the biocybernetic perspective.

作者信息

Kijak Edward, Margielewicz Jerzy, Gąska Damian, Lietz-Kijak Danuta, Więckiewicz Włodzimierz

机构信息

Department of Prosthetic Dentistry, Faculty of Medicine and Dentistry, Pomeranian Medical University, Rybacka 1, 70-204 Szczecin, Poland.

Silesian University of Technology, Krasińskiego 8, 40-019 Katowice, Poland.

出版信息

Biomed Res Int. 2015;2015:436595. doi: 10.1155/2015/436595. Epub 2015 Mar 26.

Abstract

UNLABELLED

PURPOSE OF THE PAPER: This paper is an attempt to mathematically describe the mastication organ muscle functioning, taking into consideration the impact of the central nervous system.

MATERIAL

To conduct model tests, three types of craniums were prepared: short, normal, and long. The necessary numeric data, required to prepare the final calculation models of different craniofacial types, were used to identify muscle and occlusion forces generated by muscles in the area of incisors and molars. The mandible in model tests was treated as a nondeformable stiff form.

METHODS

The formal basis for the formulated research problem was reached using the laws and principles of mechanics and control theory. The proposed method treats muscles as "black boxes," whose properties automatically adapt to the nature of the occlusion load. The identified values of occlusion forces referred to measurements made in clinical conditions.

RESULTS

The conducted verification demonstrated a very good consistency of model and clinical tests' results. The proposed method is an alternative approach to the so far applied methods of muscle force identification. Identification of muscle forces without taking into account the impact of the nervous system does not fully reflect the conditions of mastication organ muscle functioning.

摘要

未标注

本文目的:本文旨在考虑中枢神经系统的影响,从数学角度描述咀嚼器官肌肉的功能。

材料

为进行模型测试,制备了三种类型的颅骨:短型、正常型和长型。用于准备不同颅面类型最终计算模型的必要数值数据,被用于确定在门牙和磨牙区域肌肉产生的肌肉力和咬合力量。模型测试中的下颌骨被视为不可变形的刚性形式。

方法

利用力学和控制理论的定律及原理,为所提出的研究问题奠定了形式基础。所提出的方法将肌肉视为“黑箱”,其属性会自动适应咬合负荷的性质。所确定的咬合力量值参考了临床条件下的测量结果。

结果

所进行的验证表明模型测试结果与临床测试结果非常吻合。所提出的方法是迄今应用的肌肉力识别方法的一种替代方法。不考虑神经系统影响来识别肌肉力并不能完全反映咀嚼器官肌肉的功能状况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e653/4391721/a3f36349248e/BMRI2015-436595.001.jpg

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