## 1 Introduction
Since it has been discussed that the dielectric parameters of the cochlea layers are frequency-dependent [20; 21], more accurate results may be obtained using a transient solution (TS) by considering the capacitive effect of the time-dependent dielectric parameters. Thus, there is a need for a systematic study to show what extent these parameters affect the outcome. Using animal and human cadaveric models presents significant challenges as it is not possible to obtain a comprehensive systematic testing of dielectric parameters and their effects on the outcome. Alternatively, three-dimensional (3D) bio-computational models of the inner ear can be utilized to assist in investigating the impedance variation that influences CI outcomes [3; 22; 23; 24; 25]. Over the past decade, substantial research progress has been made to advance inner ear computational modeling. The first cochlea model was  
Figure 1: **(A)** shows the external components of the CI and insertion of the electrode array (EA) into the scala typnani. The EA and its contacts are highlighted. **(B)** shows an overview of experimental CI simulation and recording procedures. _(i)_ shows the applied current to the electrode contacts. The associated tissue capacitance and resistance are represented with \(C_{t}\) and \(R_{t}\), respectively. **GND**: ground, **Z**: impedance, and **E1**: electrode contact 1.  
developed based on a fixed grid. The grid size, and therefore the resolution of the model, was mainly limited due to computation. Semiautomatic and automatic segmentation image methods were generated to construct a cochlea volume conductor using finite element (FE) or boundary element methods [15]. The finite element modeling (FEM) allows the intricacies of the inner ear's mechanics to be reduced to simpler phenomena that can be verified with clinical results [26]. The impedance variation can be readily investigated using available commercial FEM software packages, such as COMSOL Multiphysics V5.2 (COMSOL, Ltd., Cambridge, UK), which includes many matured numerical toolsets for solving bioelectric phenomena problems [17; 27; 28; 29]. This paper develops an accurate human cochlea model that can be used to investigate the impact of the dielectric properties of tissue layers for the cochlea electrode insertion guidance based on the impedance variation as shown in Figure 2A. The models are implemented in FEM involving a volume conductor model representing various anatomical structures and the electrodes by their respective dielectric features and appropriate boundary conditions as shown in Figure 2. The impact of the dielectric properties on the outcome was defined by the following:  
1. Impedance variation based on the EAs that are placed at the center and border of the ST by considering both capacitive and static (resistive) effects;
2. Variation in the electrical potential waveform to observe the capacitive effect;
3. Parametrizing the ST conductivity by keeping constant other layers' dielectric properties to examine the impact of this layer on the results;
4. Showing smooth electrical potential and current density variations over the outer wall of the ST based on QS and TS. Figure 2: (**A**) shows the anatomical-based cochlea model. The holes are shown in the micro-CT data in (**A.1**). These holes cause extra layers during image processing as shown in (**A.2**). These small layers are observed in both meshing (**A.3**) and simulation (**A.4**) processes. (**B**) shows a multi-layered geometrical-based cochlea model without any extra layers and holes. The model is generated (**B.1**), the electrode model is merged with the cochlea model (**B.2**), and after applying the meshing process (**B.3**), the FEM results are calculated (**B.4**). The CI layers are scala typnani (ST), scala vestibular (SV), basilar membrane layer (BM), spiral ligament (SL), and cochlea wall (CW). The paper is organized as follows.