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Parameter identification of a human stapedial annular ligament model in the context of a model-based hearing diagnosis of the human middle ear

  • This study describes a non-contact measuring and parameter identification procedure designed to evaluate inhomogeneous stiffness and damping characteristics of the annular ligament in the physiological amplitude and frequency range without the application of large static external forces that can cause unnatural displacements of the stapes. To verify the procedure, measurements were first conducted on a steel beam. Then, measurements on an individual human cadaveric temporal bone sample were performed. The estimated results support the inhomogeneous stiffness and damping distribution of the annular ligament and are in a good agreement with the multiphoton microscopy results which show that the posterior-inferior corner of the stapes footplate is the stiffest region of the annular ligament. This method can potentially help to establish a correlation between stiffness and damping characteristics of the annular ligament and inertia properties of the stapes and, thus, help to reduce the number of independent parameters in the model-based hearing diagnosis.

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Metadaten
Author of HS ReutlingenBurovikhin, Dmitrii; Sackmann, Benjamin; Lauxmann, Michael
URN:urn:nbn:de:bsz:rt2-opus4-24949
URL:https://www.curac.org/images/advportfoliopro/images/CURAC2019/Tagungsband_Impressum_Curac.pdf
ISBN:978-3-00-063717-9
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
Language:English
Publication year:2019
Tag:annular ligament model; middle ear; model-based hearing diagnosis; parameter identification procedure
Page Number:6
First Page:95
Last Page:100
PPN:Im Katalog der Hochschule Reutlingen ansehen
DDC classes:610 Medizin, Gesundheit
004 Informatik
Open access?:Ja
Licence (German):License Logo  Open Access