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Parameter identification from normal and pathological middle ears using a tailored parameter identification algorithm

  • 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.

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Metadaten
Author of HS ReutlingenLauxmann, Michael; Sackmann, Benjamin
DOI:https://doi.org/10.1115/1.4052371
ISSN:0148-0731
Erschienen in:Journal of biomechanical engineering
Publisher:ASME
Place of publication:New York
Document Type:Journal article
Language:English
Publication year:2022
Tag:middle-ear model; middle-ear pathologies; model-based hearing diagnosis; tailored parameter identification algorithm
Volume:144
Issue:3
Page Number:13
Article Number:BIO-21-1101
DDC classes:500 Naturwissenschaften
Open access?:Nein