Parameter Identification From Normal and Pathological Middle Ears Using a Tailored Parameter Identification Algorithm

Author:

Sackmann Benjamin1,Eberhard Peter2,Lauxmann Michael3

Affiliation:

1. Reutlingen Research Institute, Reutlingen University, Reutlingen 72762, Germany

2. Institute of Engineering and Computational Mechanics, University of Stuttgart, Stuttgart 70569, Germany

3. School of Engineering, Reutlingen University, Reutlingen 72762, Germany

Abstract

Abstract Current clinical practice is often unable to identify the causes of conductive hearing loss in the middle ear with sufficient certainty without exploratory surgery. Besides the large uncertainties due to interindividual variances, only partially understood cause–effect principles are a major reason for the hesitant use of objective methods such as wideband tympanometry in diagnosis, despite their high sensitivity to pathological changes. For a better understanding of objective metrics of the middle ear, this study presents a model that can be used to reproduce characteristic changes in metrics of the middle ear by altering local physical model parameters linked to the anatomical causes of a pathology. A finite-element model is, therefore, fitted with an adaptive parameter identification algorithm to results of a temporal bone study with stepwise and systematically prepared pathologies. The fitted model is able to reproduce well the measured quantities reflectance, impedance, umbo and stapes transfer function for normal ears and ears with otosclerosis, malleus fixation, and disarticulation. In addition to a good representation of the characteristic influences of the pathologies in the measured quantities, a clear assignment of identified model parameters and pathologies consistent with previous studies is achieved. The identification results highlight the importance of the local stiffness and damping values in the middle ear for correct mapping of pathological characteristics and address the challenges of limited measurement data and wide parameter ranges from the literature. The great sensitivity of the model with respect to pathologies indicates a high potential for application in model-based diagnosis.

Publisher

ASME International

Subject

Physiology (medical),Biomedical Engineering

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