Volltext-Downloads (blau) und Frontdoor-Views (grau)

Model-based hearing diagnosis of middle ear condition using inverse fuzzy arithmetic and artificial neuronal network

  • Due to the large interindividual variances and the poor optical accessibility of the ear, the specificity of hearing diagnostics today is severely restricted to a certain clinical picture and quantitative assessment. Often only a yes or no decision is possible, which depends strongly on the subjective assessment of the ENT physician. A novel approach, in which objectively obtainable, non invasive audiometric measurements are evaluated using a numerical middle ear model, makes it possible to make the hidden middle ear properties visible and quantifiable. The central topic of this paper is a novel parameter identification algorithm that combines inverse fuzzy arithmetic with an artificial neural network in order to achieve a coherent diagnostic overall picture in the comparison of model and measurement. Its usage is shown at a pathological pattern called malleus fixation where the upper ligament of the malleus is pathologically stiffened.

Download full text files

Export metadata

Additional Services

Share in Twitter Search Google Scholar


Author of HS ReutlingenSackmann, Benjamin; Priwitzer, Barbara; Lauxmann, Michael
Erschienen in:CURAC 2019 - Tagungsband : 18. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie e. V. : 19. - 21. September 2019, Reutlingen
Publisher:Deutsche Gesellschaft für Computer- und Roboterassistierte Chirurgie e.V.
Place of publication:Stuttgart
Editor:Oliver BurgertORCiD
Document Type:Conference proceeding
Publication year:2019
Tag:artificial neural network; fuzzy arithmetic; middle-ear model; model-based ENT diagnostic; wideband tympanometry
Page Number:6
First Page:89
Last Page:94
PPN:Im Katalog der Hochschule Reutlingen ansehen
DDC classes:610 Medizin, Gesundheit
004 Informatik
Open access?:Ja
Licence (German):License Logo  Open Access