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A biomechanical model of the human tongue for understanding speech production and other lingual behaviors.

机译:人类舌头的生物力学模型,用于理解语音产生和其他语言行为。

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摘要

A biomechanical model of the human tongue was constructed, based upon a detailed anatomical study of an actual cadaver. Data from the Visible Human Project were segmented to create a volumetric representation of the tongue and its constituent muscles. The volumetric representation was converted to a smooth NURBS-bounded solid model--for compatibility with meshing algorithms--by lofting between splines, the vertices of which were defined by the coordinates of a smoothed triangular mesh representation. Using a hyperelastic constitutive model that allowed for the addition of active stress, the model deforms in response to user-specified muscle activation patterns. A series of meshes was created to perform a mesh validation study; in the validation tests performed, a 245,223-element mesh was found to be sufficient to model tongue behavior.;Systematic samples of the behavior of the model were collected. Principal component analyses were performed on the samples to discover low-dimensional representations of tongue postures. Statistical models (linear regression models and neural networks) were fit to predict tongue posture from muscle activation, and vice versa. In all tests, it was found that a relatively small sample of tongue postures can be used to successfully generalize to larger data sets.;Finally, a variety of specific tests were performed, based on claims and predictions found in previous literature. Of these, the claims of the muscular hydrostat theory of tongue movement were best supported. Simulations were also run that simulated lingual hemiplegia. It was found that substantially different muscular activation patterns were required to achieve equivalent postures in a hemiplegic tongue, relative to a normal tongue.
机译:基于对实际尸体的详细解剖研究,构建了人舌的生物力学模型。将来自“可见人类项目”的数据进行细分,以创建舌头及其组成肌肉的体积表示。通过在样条曲线之间放样,将体积表示形式转换为平滑的NURBS边界实体模型(与网格算法兼容),样条曲线之间的顶点由平滑的三角形网格表示形式的坐标定义。使用允许增加活动应力的超弹性本构模型,该模型可响应用户指定的肌肉激活模式而变形。创建了一系列网格以执行网格验证研究。在进行的验证测试中,发现一个245,223个元素的网格足以模拟舌头行为。;收集了模型行为的系统样本。对样本进行主成分分析,以发现舌头姿势的低维表征。统计模型(线性回归模型和神经网络)适合于通过肌肉激活来预测舌头姿势,反之亦然。在所有测试中,发现可以使用相对较小的舌头姿势样本成功地推广到较大的数据集。最后,根据先前文献中的说法和预测,进行了各种特定的测试。其中,最好的支持是肌肉静水压的舌头运动理论。还进行了模拟舌偏瘫的模拟。已经发现,相对于正常舌头,在偏瘫舌头中要达到相同的姿势需要实质上不同的肌肉激活模式。

著录项

  • 作者

    Baker, Todd Adam.;

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Language Linguistics.;Biology Physiology.;Engineering Biomedical.;Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2008
  • 页码 294 p.
  • 总页数 294
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 语言学 ; 生物医学工程 ; 机械、仪表工业 ;
  • 关键词

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