Statistical perturbations in personal exposure meters caused by the human body in dynamic outdoor environments.

Personal exposure meters (PEM) are routinely used for the exposure assessment to radio frequency electric or magnetic fields. However, their readings are subject to errors associated with perturbations of the fields caused by the presence of the human body. This paper presents a novel analysis method for the characterization of this effect. Using ray-tracing techniques, PEM measurements have been emulated, with and without an approximation of this shadowing effect. In particular, the Global System for Mobile Communication mobile phone frequency band was chosen for its ubiquity and, specifically, we considered the case where the subject is walking outdoors in a relatively open area. These simulations have been contrasted with real PEM measurements in a 35-min walk. Results show a good agreement in terms of root mean square error and E-field cumulative distribution function (CDF), with a significant improvement when the shadowing effect is taken into account. In particular, the Kolmogorov-Smirnov (KS) test provides a P-value of 0.05 when considering the shadowing effect, versus a P-value of 10⁻¹⁴ when this effect is ignored. In addition, although the E-field levels in the absence of a human body have been found to follow a Nakagami distribution, a lognormal distribution fits the statistics of the PEM values better than the Nakagami distribution. As a conclusion, although the mean could be adjusted by using correction factors, there are also other changes in the CDF that require particular attention due to the shadowing effect because they might lead to a systematic error.