Automated identification of human-body model parameters

The paper presents the exploitation of a lowest-order algorithm of evolutionary computing (EStra) for identifying the parameters of a simplified human body model (phantom). A simplified model is well suited in view of the computationally-expensive field simulation of wearable antennas located in a close proximity to the human body. In the paper, an automated procedure based on evolutionary computing and Finite Difference Time Domain (FDTD) computational electrodynamics method is proposed to identify the parameters of the simplified model. Subsequently, after identifying the parameter values, the simplified model is compared to a heterogeneous anthropomorphic human-body model. The comparison is based on the analysis of impedance matching of the same dipole antenna located on both the anthropomorphic and simplified phantoms.