In English

Development of 3D Finite Element Model of Human head

Li Jung Kim
Göteborg : Chalmers tekniska högskola, 2017. 85 s.
[Examensarbete på avancerad nivå]

Bone-Anchored Hearing Aid (BAHA) is known as the surgically implantable hearing aid for patients whose medical conditions are beyond the stage of wearing the conventional air conductive hearing aid (ACHA) or those who suffer from bone diseases or chronic inflammation of the outer or middle ear. Numerous studies have been conducted to investigate the bone conduction mechanism. Nowadays, with the help of computational mechanics such as the Finite-Element Method (FEM), the performance of BAHA can be improved before the actual costly physical models are built. This thesis aims to develop FE head models that are readily available for commercial use. This thesis presents two different head models, which enable the simulation of the vibration phenomenon, specifically the mechanical point impedance of the skull bone. One model addresses the artificial head model, and the other originates from the direct segmentation of CT scan with new segmentation software. The final goal is to identify critical parameters for effective bone conduction as well as to improve the current BAHA model. The simulation results were compared with both test data and literature. This study concludes that both models were successfully able to reproduce results with the test data. Antiresonance frequencies in the simulation results were present at approximately 70 — 90 Hz in the simulator FE model and approximately 200 Hz in the actual human FE model. The proposed modelling approach will be a stepping stone to quantitatively investigate the biomechanical behavior of bone conduction and provide platforms for the patient-specific optimization of the BAHA configuration with future improvements.

Nyckelord: Bone Anchored Hearing Aid (BAHA), Bone Conduction, Finite Element Method (FEM), Frequency response analysis, Mechanical Point Impedance, Nonstructural Mass, Fluid-Structure, MSC Nastran, ANSA, RETOMO, Medical Image Segmentation



Publikationen registrerades 2017-10-03. Den ändrades senast 2017-10-03

CPL ID: 252221

Detta är en tjänst från Chalmers bibliotek