Existing indoor navigation solutions for pedestrian complement Global Navigation Satellite System (GNSS) in GNSS-compromised areas. Recently, these solutions rely on pre-installed wireless sensor networks (WSN) where received signal strength (RSS) based techniques are the most spread due to their availability and cost. However, neither of the RSS based positioning techniques take into account the shadow effect of the human body who carries the RSS meter since the presence of the human body alters the pattern of wave propagation in its immediate proximity. In this paper, we assess the human shadow effect in a theoretical approach based on the finite-difference time-domain (FDTD) method to weight the RSS information that feeds inertial navigation system (INS) based on the human body attitude.