*4.2.3. Full simulation of the electromagnetic field distribution*

Beside the analytical approach, we are interested in the detailed temporal evolution of the electromagnetic fields inside and outside the human thorax. To this end, we investigated complex arrangements mimicking the illumination of a realistic human torso [75] model incorporating the geometry of the antennas by finite-difference time-domain method (FDTD) simulations. By FDTD simulation, we studied, e.g., the dependence of the illumination and detection angles of the transmission and receiving antennas on the quality of the received signal, *i.e.* the correlation result. In this way, an estimate of the optimized antenna placement can be found. Furthermore, by varying organs' boundaries by changing their thickness or/and placement of one or more tissue layers, different functional states can be investigated, e.g. the end-systolic and end-diastolic phase of the myocardium, which consequently determines a characteristic change of the received signals.

**Figure 29.** Extra- and intra-corporal electrical field distribution in an axial cross-section of the upper human body **a)** with tissue mesh; **b)** without the mesh showing the wave propagation intra-corporal. The thorax's contour is highlighted by the white line.

An example of the complex wave propagation inside the human torso is shown in Fig. 29. Due to the higher permittivity inside the body, the propagation velocity is slowed down according to *c* = *c*0/ . Hence, a bending of the extra- and intra-corporal wave fronts results. The transmitted spherical wave fronts are refracted towards the center of the thorax, which is beneficial for the illumination of the myocardial section lying deeper inside the thorax. By these simulations, we achieve an in-depth understanding of the complex electromagnetic field distribution and the dependencies of the resulting output signal of the receiving antenna [73]. Therefore, the results of these simulations are helpful to increase the accuracy of reconstructed physiological signatures from deep sources by finding the optimized antenna position regarding the better penetrability of selected body areas. This, of course, requires the adaptation of the model to the actual thorax geometry of the patient as obtained by MRI scans.
