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Electrical conduction models for cochlear implant stimulation

Kai Dang 1, 2 
Abstract : Computational models have been widely used to improve the knowledge of the current distribution behavior in cochlear implant stimulations, optimizing electrode designs and stimulation strategies. The existing models employed no or simple electrochemical interface models and took current intensity on the electrodes as input. Therefore they have difficulties in making time domain simulations and simulating the stimulation modes that have voltage constraints, such as the Common Ground and the Multi-Mode Grounding modes. In this PhD work, a new parametric surface mesh model of the cochlea has been developed. The shape of the model is controlled by a set of input parameters which can be tuned to fit the cochlear shape acquired from histological images, CT scans or existing cochlear mesh models. The symmetric boundary element method, which was implemented in OpenMEEG, has been applied on the model to simulate the current distribution of the cochlear implant stimulation. Using the parametric model, comparisons on the current field has been made between the existing electrode layouts and a new transmodiolar electrodes. The new model can take either current or voltage as input for each electrode to simulate the common ground and multi-mode grounding modes. By coupling the surface model with lumped capacitor and constant phase element models, time domain simulation of the stimulation waveform has also been achieved. To validate the simulation results and calibrate the parameters of the model, in-situ and in-vitro measurements have been carried out with self-made devices. The recorded data proved the effectiveness of combining lumped components with the surface model.
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Submitted on : Thursday, September 14, 2017 - 4:17:02 PM
Last modification on : Saturday, June 25, 2022 - 11:27:41 PM


Version validated by the jury (STAR)


  • HAL Id : tel-01562277, version 2



Kai Dang. Electrical conduction models for cochlear implant stimulation. Other. Université Côte d'Azur, 2017. English. ⟨NNT : 2017AZUR4043⟩. ⟨tel-01562277v2⟩



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