Exposure to radiofrequency (RF) electromagnetic fields (EMFs) in indoor environments depends on both outdoor sources such as radio, television and mobile phone antennas and indoor sources, such as mobile phones and wireless communications applications. Establishing the levels of exposure could be challenging due to differences in the approaches used in different studies. The goal of this study is to present an overview of the last ten years research efforts about RF EMF exposure in indoor environments, considering different RF-EMF sources found to cause exposure in indoor environments, different indoor environments and different approaches used to assess the exposure. The highest maximum mean levels of the exposure considering the whole RF-EMF frequency band was found in offices (1.14 V/m) and in public transports (0.97 V/m), while the lowest levels of exposure were observed in homes and apartments, with mean values in the range 0.13–0.43 V/m. The contribution of different RF-EMF sources to the total level of exposure was found to show slightly different patterns among the indoor environments, but this finding has to be considered as a time-dependent picture of the continuous evolving exposure to RF-EMF.

Extremely Low Frequency Electric (ELF-EF) and Magnetic Field (ELF-MF) exposure is caused by different types of sources, from those related to the production, transmission, and distribution of electric currents, to technologies of common use, such as domestic appliances or electric transportation. Establishing the levels of exposure for general public is a fundamental step in the health risk management process but could be challenging due to differences in the approaches used in different studies. The goal of this study is to present an overview of the last years research efforts (from 2015 to nowadays) about ELF-EF and MF exposure in everyday environments, considering different sources and different approaches used to assess the exposure. All ELF-EMF exposure levels were found to be below the ICNIRP guidelines for general public exposure. The higher MF levels were measured in apartments very close to built-in power transformers. Household electrical devices showed high levels of MF exposure in their proximity, but the duration of such exposure is extremely limited.

Deep Transcranial Magnetic Stimulation (dTMS) is a neurostimulation technique for deep brain structures that has recently been successfully applied in the clinic for treatment of addiction. In contrast to conventional magnetic stimulation, which uses planar coils (figure-of-8) to target specific superficial regions of the brain, dTMS requires the design of complex three-dimensional coils in order to induce deeply penetrating fields. Recent clinical studies have focused on the use of H4 coils, which utilizes a left-right symmetric structure for bilateral stimulation of the prefrontal cortex, and demonstrated efficacy for therapy such as smoking cessation. The mechanism of activity, however, remains poorly understood, in part because the affected regions of the brain are not known in detail. To this purpose, computational techniques applied to highly detailed inhomogeneous tissue phantoms, provide a powerful tool for testing coil efficacy. In this work we quantified both electric field E distribution and its penetration depth in the prefrontal cortex, induced by a specific Hesed-coil, H4, designed for the addiction treatment and by the traditional figure-of-8 coil for comparison. Results show that H4 coil preferentially targets insula and cingulate cortex. Moreover, it can induce in the deepest tissues E amplitude ranging between the 20-40% of the cortical peak and it can penetrate the cortex up to 4 cm with a E>50% of the cortical peak, thus noticeably increasing the penetration depth of the traditional TMS systems.

Objective. Recently developed magnetoelectric nanoparticles (MENPs) provide a potential tool to enable different biomedical applications. They could be used to overcome the intrinsic constraints posed by traditional neurostimulation techniques, namely the invasiveness of electrodes-based techniques, the limited spatial resolution, and the scarce efficiency of magnetic stimulation. Approach. By using computational electromagnetic techniques, we modelled the behaviour of recently designed biocompatible MENPs injected, in the shape of clusters, in specific cortical targets of a highly detailed anatomical head model. The distributions and the tissue penetration of the electric fields induced by MENPs clusters in each tissue will be compared to the distributions induced by traditional transcranial magnetic stimulation (TMS) coils for non-invasive brain stimulation positioned on the left prefrontal cortex (PFC) of a highly detailed anatomical head model. Main results. MENPs clusters can induce highly focused electric fields with amplitude close to the neural activation threshold in all the brain tissues of interest for the treatment of most neuropsychiatric disorders. Conversely, TMS coils can induce electric fields of several tens of V m⁻¹ over a broad volume of the PFC, but they are unlikely able to efficiently stimulate even small volumes of subcortical and deep tissues. Significance. Our numerical results suggest that the use of MENPs for brain stimulation may potentially led to a future pinpoint treatment of neuropshychiatric disorders, in which an impairment of electric activity of specific cortical and subcortical tissues and networks has been assumed to play a crucial role.

Cars are rapidly evolving into smart connected objects that can communicate not only with the infrastructure but also with other cars through vehicle-to vehicle (V2V) communication. By the end of 2023, more than 72 million vehicles worldwide will be equipped with devices and technologies that enable to exchange data and communicate with other cars. This challenging scenario is raising cross-cutting issues, such as those related to new radio-frequency exposures of the human body also when travelling. We evaluate the Specific Absorption Rate (SAR) induced in a realistic smart mobility communication scenario operated at 5.9 GHz. V2V antennas were modeled and placed on a realistic 3D model of a city-car to numerically estimate SAR in the body regions and tissues of a human phantom (adult male) inside the car. We found that both local and whole-body average exposures were below the ICNIRP and IEEE limits for the general public in the 100 kHz-6 GHz band, being equal in the worst case scenario to 1.58 W/kg (head) and 0.008 W/kg, respectively. The highest SAR was found in the most superficial tissues (the skin) of body regions very close to the sources. The distance of the passenger from the antennas played an important role in the resulting SAR. This research has a potentially great clinical impact as it contributes to new and realistic knowledge on the exposure scenario in smart mobility communication to assess possible health effects and for the design of policies for public health management.

Characterization of children exposure to extremely low frequency (ELF) magnetic fields is an important issue because of the possible correlation of leukemia onset with ELF exposure. Cluster analysis—a Machine Learning approach—was applied on personal exposure measurements from 977 children in France to characterize real-life ELF exposure scenarios. Electric networks near the child’s home or school were considered as environmental factors characterizing the exposure scenarios. The following clusters were identified: children with the highest exposure living 120–200 m from 225 kV/400 kV overhead lines; children with mid-to-high exposure living 70–100 m from 63 kV/150 kV overhead lines; children with mid-to-low exposure living 40 m from 400 V/20 kV substations and underground networks; children with the lowest exposure and the lowest number of electric networks in the vicinity. 63–225 kV underground networks within 20 m and 400 V/20 kV overhead lines within 40 m played a marginal role in differentiating exposure clusters. Cluster analysis is a viable approach to discovering variables best characterizing the exposure scenarios and thus it might be potentially useful to better tailor epidemiological studies. The present study did not assess the impact of indoor sources of exposure, which should be addressed in a further study.