Numerical model characterization of the sound transmission mechanism in the tympanic membrane from a high-speed digital holographic experiment in transient regime
Source abstract
Abstract
A methodology for the development of a finite element numerical model of the tympanic membrane (TM) based on experiments carried out in the time domain on a cadaveric human temporal bone is presented. Using a high-speed digital holographic (HDH) system, acoustically-induced transient displacements of the TM surface are obtained. The procedure is capable to generate and validate the finite element model of the TM by numerical and experimental data correlation. Reverse engineering approach is used to identify key material parameters that define the mechanical response of the TM. Finally, modal numerical simulations of the specimen are performed. Results show the feasibility of the methodology to obtain an accurate model of a specific specimen and to help interpret its behaviour with additional numerical simulations. STATEMENT OF SIGNIFICANCE: Improving knowledge of the dynamic behavior of the tympanic membrane is key to understanding the sound transmission system in human hearing and advance in the treatment of its pathologies. Recently we acquired a new tool to carry out experiments in transient regime by means of digital laser holography, capable of providing a large amount of information in a controlled transient test. In this work, these data are used to develop a methodology that generates a numerical model of the tympanic membrane based on numerical-experimental correlations. It is important to be able to develop models that fit specific patients. In this work, additional modal simulations are also presented that, in addition to validating the results, provide more information on the specimen.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Acoustic Wave Phenomena Research · Speech and Audio Processing · Hearing Loss and Rehabilitation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (50)
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