# Wearable Flexible Antenna for UWB On-Body and Implant Communications
## 3 Methodology
### Simulations  
The antenna is designed and its performance is evaluated using Dassault Simulia CST Studio suite software [55], which is based on finite integration technique (FIT) [56]. Since the antenna is designed to operate tightly attached on the human skin, the performance is evaluated using two human tissue models, namely (a) a planar tissue layer model, and (b) CST's anatomical voxel model Laura, which are presented in Figure 2a,b, respectively. The thicknesses of the different tissue layers in the planar model are presented in Table 2, where also the relative permittivity of the tissues (\(\epsilon_{\text{r}}\)) and wavelength (\(\lambda\)) in the tissues are presented at the selected frequencies [57]. As can be seen, the relative permittivity and wavelength varies significantly from tissue to tissue, which has a clear impact on the propagation characteristics, as will be described through the paper. Figure 2b presents the torso of [PERSON] voxel model used in the simulations. Laura voxel resembles a young, lean female. Only the part of the voxel model's abdomen area is included in the simulations to save simulation time. The pixel resolution of the Laura voxel is \(1.88\times 1.88\times 1.25\) mm\({}^{3}\). \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Parameter** & **X** & **Y** & **R** & **f1** & **g1** & **g2** & **g3** & **x1** & **x2** \\ \hline Dimension [mm] & 20 & 30 & 8.1 & 11 & 9.1 & 10 & 5.7 & 0.4 & 0.6 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Dimensions of the antenna structure. Figure 1: Flexible antenna (**a**) simulation model, (**b**) prototype. The layered tissue models and voxel models have their own advantages and disadvantages in the evaluations as described, e.g., in [58]. The layered tissue model provides possibility to verify antenna performance and radio channel characteristics with a lower complexity. Additionally, the thickness of the tissue layers is easy to vary in the simple layer models. However, the deficiency of the layer model is the simplicity, especially in the in-body propagation studies: it cannot exploit multipath rich in-body propagation environment similar to the realistic human voxel models, in which the tissue thicknesses and thickness variations are designed according to a real human body. With anatomical voxel models, more realistic performances can be obtained. For instance, in the capsule endoscopy evaluations, it is crucial to use the realistic models since the abdominal muscles have certain shape with clear thickness variation. The areas with thinner/none muscle \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Tissue**} & \multicolumn{5}{c}{**Relative Permitivity \(\epsilon_{\text{r}}\)/Wavelength \(\lambda\) [m] at Selected Frequencies**} \\ \cline{2-7}  & \multicolumn{5}{c}{**Frequency [GHz]**} \\ \cline{2-7}  & **2.45** & **3.1** & **5.8** & **7** & **9** & **10.6** \\ \hline Skin (1.4 mm) & 38.0/0.022 & 37.4/0.015 & 35.1/0.009 & 33.1/0.42 & 32.0/0.42 & 30.7/0.005 \\ Fat (outer:15 mm, inner 7.5 mm) & 5.28/0.053 & 5.21/0.04 & 4.95/0.023 & 4.84/0.20 & 4.68/0.015 & 4.58/0.013 \\ Muscle (15.13 mm) & 55.0/0.04 & 51.9/0.013 & 48.5/0.072 & 46.8/0.006 & 44.12/0.05 & 42.0/0.0042 \\ Small intestine (15 mm) & 59.4/004 & 53.8/0.013 & 48.5/0.007 & 46.7/0.006 & 43.6/0.049 & 41.2/0.0042 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Thickness of the tissue layers, relative permittivity (\(\epsilon_{\text{r}}\)) of tissue and wavelength in the tissue (\(\lambda\)) at different frequencies. Figure 2: (a) Tissue layer model, (b) CST’s anatomical voxel model Laura. layer, e.g., in the central line of the abdomen, can provide \"easier\" propagation paths for the signal since the signal can avoid traveling through the muscle layer which has high propagation loss [59]. With layer modes, such realistic evaluations are not possible. Besides, fat as a propagation channel can be studied more efficiently with the voxel models [59].