Reutlingen University, Alteburgstr. 150, 72762, Reutlingen, Germany; Institute of Engineering and Computational Mechanics, University of Stuttgart, Pfaffenwaldring 9, 70569, Stuttgart, Germany.
Department of Otolaryngology, University of Tübingen, Elfriede-Aulhorn-Str. 5, 72076, Tübingen, Germany.
Hear Res. 2019 Jul;378:126-138. doi: 10.1016/j.heares.2019.02.011. Epub 2019 Feb 28.
Today's audiometric methods for the diagnosis of middle ear disease are often based on a comparison of measurements with standard curves, that represent the statistical range of normal hearing responses. Because of large inter-individual variances in the middle ear, especially in wideband tympanometry (WBT), specificity and quantitative evaluation are greatly restricted. A new model-based approach could transform today's predominantly qualitative hearing diagnostics into a quantitative and tailored, patient-specific diagnosis, by evaluating WBT measurements with the aid of a middle-ear model. For this particular investigation, a finite element model of a human ear was used. It consisted of an acoustic ear canal and a tympanic cavity model, a middle-ear with detailed nonlinear models of the tympanic membrane and annular ligament, and a simplified inner-ear model. This model has made it possible for us to simulate pathologies like the stiffening of ligaments or joints, because we can simply change the corresponding mechanical parameters of the model. On the other hand, it is also possible to identify pathologies from measurements, by analyzing the parameters obtained by a system identification procedure. This reduces the number of required model parameters through sensitivity studies and parameter clustering. Uncertainties due to the lack of knowledge, subjectivity in numerical implementation and model simplification are taken into account by the application of fuzzy arithmetic. The most confident parameter set can be determined by applying an inverse fuzzy method on the measurement data. The principle and the benefits of this model-based approach are illustrated by the example of a two-mass oscillator, and also by the simulation of the energy absorbance of an ear with malleus fixation, where the parameter changes that are introduced can be determined quantitatively through the system identification.
现今，中耳疾病的听力诊断方法常基于对测量值与标准曲线的对比，标准曲线代表正常听力反应的统计范围。由于中耳个体间差异较大，特别是在宽频带鼓室图测试（WBT）中，特异性和定量评估受到极大限制。一种新的基于模型的方法可以将目前主要基于定性的听力诊断转变为定量的、针对个体的诊断，通过中耳模型评估 WBT 测量值。为此，我们使用了人耳的有限元模型。该模型由声导纳耳道和鼓膜腔模型、包含详细鼓膜和环韧带非线性模型的中耳，以及简化内耳模型组成。该模型使我们能够模拟像韧带或关节僵硬等病变，因为我们可以简单地改变模型的相应机械参数。另一方面，也可以通过分析系统识别过程中获得的参数，从测量中识别出病变。通过敏感性研究和参数聚类，减少了所需模型参数的数量。通过模糊运算，可以考虑由于缺乏知识、数值实现和模型简化的主观性而导致的不确定性。通过在测量数据上应用反模糊方法，可以确定最可信的参数集。该基于模型的方法的原理和优势通过两质量振子的例子来说明，还通过模拟锤骨固定的耳朵的能量吸收率来说明，通过系统识别可以定量确定引入的参数变化。
