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Distributed wireless sensor networks (WSNs) are widely used to enhance the quality and safety of various applications. These networks consist of numerous sensor nodes, often deployed in challenging terrains where maintenance is difficult. Efficient monitoring approaches are essential to maximize the functionality and lifespan of each sensor node, thereby improving the overall performance of the WSN. In this study, we propose a method to efficiently monitor radiofrequency electromagnetic fields (RF-EMF) exposure using WSNs. Our approach leverages sensor nodes to provide real-time measurements, ensuring accurate and timely data collection. With the increasing prevalence of wireless communication systems, assessing RF-EMF exposure has become crucial due to public health concerns. Since individuals spend over 70% of their time indoors, it is vital to evaluate indoor RF-EMF exposure. However, this task is complicated by the complex indoor environments, furniture arrangements, temporal variability of exposure, numerous obstructions with unknown dielectric properties, and uncontrolled factors such as people's movements and the random positioning of furniture and doors. To address these challenges, we employ a sensor network to monitor RF-EMF exposure limits using embedded sensors. By integrating Internet of Things-embedded sensors with advanced modeling techniques, such as kriging, we characterize and model indoor RF-EMF downlink (DL) exposure effectively. Measurements taken in several buildings within a few hundred meters of base stations equipped with multiple cellular antennas (2G, 3G, 4G, and 5G) demonstrate that the kriging technique using the spherical model provides superior RF-EMF prediction compared with the exponential model. Using the spherical model, we constructed a high-resolution coverage map for the entire corridor, showcasing the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Objectives Assessing occupational exposure to radiofrequency electromagnetic fields (RF-EMF) presents significant challenges due to the considerable variability in exposure levels within and between occupations. This spatial and temporal variability complicates the reliable evaluation of potential health risks associated with RF-EMF exposure in the workplace. Accurate assessment methods are crucial to understand the extent of exposure and to evaluate potential health risks, especially given the potential for higher exposures in occupational settings compared to the general population. This study compares the historical RF-EMF exposure estimates in the INTEROCC RF-EMF job-exposure matrix (RF-JEM) with recent personal measurement data collected in 2 countries as part of the OccRF-Health study, to assess the broader applicability of the RF-JEM. Methods Weighted kappa (k w) coefficients and Spearman rank correlation tests were performed to assess the alignment between RF-JEM estimates and measurements for 8 h time-weighted average exposure intensity and prevalence estimates across various occupations. The comparisons were mainly based on 22 jobs having ≥5 measured workers in the OccRF-Health study. Results Poor agreement was found for both exposure prevalence and intensity between both methods (k w < 0.1). RF-JEM values likely overestimated exposure levels for both electric (E) and magnetic (H) fields (mean percentage difference >194%) compared to current personal measurements. Conclusions Findings suggest that the INTEROCC-JEM likely overestimates current exposure intensity levels in the measured jobs. Adopting a semiquantitative JEM could also mitigate misclassification errors due to exposure variability, improving accuracy in exposure assessment. These findings indicate the need for more targeted personal measurements, including among highly exposed workers, and for potentially considering new exposure metrics to more accurately assess occupational RF-EMF exposures in occupational epidemiological research. [ABSTRACT FROM AUTHOR]

Electromagnetic hypersensitivity (EHS), known also as an idiopathic environmental intolerance attributed to electromagnetic fields (IEI-EMF) or a microwave sickness, is not considered by the World Health Organization (WHO) as being caused by the exposures to electromagnetic fields (EMF). EHS is not recognized as a disease anywhere in the world. Some studies have roughly estimated that 1–10% of the population might experience some form of EHS. However, because of the lack of diagnostic criteria for EHS, these estimates might be either under- or over-estimates. Because the vast majority of human population is exposed to EMF, the possibility of developing EHS from the EMF is a substantial public health issue that should be dealt with globally, even if the individual risk of developing EHS might be small. The WHO recognizes that the symptoms experienced by the EHS persons might be severe and might significantly hamper everyday life. However, after a broad analysis of international and national documents, there seems to be currently no effort to develop health policies for the dealing with EHS, no matter what causes it. National governments, follow the opinions of the WHO and the EMF safety standards setting organizations, the International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Institute of Electrical and Electronics Engineers – International Committee on Electromagnetic Safety (IEEE-ICES), are not developing any practical health policy advisories for self-declared EHS sufferers. However, symptoms experienced by the self-declared EHS persons affect their well-being and, according to the Constitution of the WHO, are a health problem. Hence, independently of what causes EHS symptoms, this admitted well-being-impairment should be dealt with globally by developing an uniform health policy. Furthermore, WHO, ICNIRP and IEEE-ICES should be advocating and supporting research that would generate a reliable scientific evidence on what are the possible cause(s) of EHS. Without such research there is not possible to develop diagnostic methods as well as any possible mitigation approaches. There is an urgent need for the WHO to advocate for the national governments to urgently develop a comprehensive and common EHS health policy. [ABSTRACT FROM AUTHOR]

Distributed wireless sensor networks (WSNs) are widely used to enhance the quality and safety of various applications. These networks consist of numerous sensor nodes, often deployed in challenging terrains where maintenance is difficult. Efficient monitoring approaches are essential to maximize the functionality and lifespan of each sensor node, thereby improving the overall performance of the WSN. In this study, we propose a method to efficiently monitor radiofrequency electromagnetic fields (RF-EMF) exposure using WSNs. Our approach leverages sensor nodes to provide real-time measurements, ensuring accurate and timely data collection. With the increasing prevalence of wireless communication systems, assessing RF-EMF exposure has become crucial due to public health concerns. Since individuals spend over 70% of their time indoors, it is vital to evaluate indoor RF-EMF exposure. However, this task is complicated by the complex indoor environments, furniture arrangements, temporal variability of exposure, numerous obstructions with unknown dielectric properties, and uncontrolled factors such as people’s movements and the random positioning of furniture and doors. To address these challenges, we employ a sensor network to monitor RF-EMF exposure limits using embedded sensors. By integrating Internet of Things-embedded sensors with advanced modeling techniques, such as kriging, we characterize and model indoor RF-EMF downlink (DL) exposure effectively. Measurements taken in several buildings within a few hundred meters of base stations equipped with multiple cellular antennas (2G, 3G, 4G, and 5G) demonstrate that the kriging technique using the spherical model provides superior RF-EMF prediction compared with the exponential model. Using the spherical model, we constructed a high-resolution coverage map for the entire corridor, showcasing the effectiveness of our approach.

The latest cellular technology, known as 5G-NR, is intended to significantly speed up and improve the effectiveness of wireless systems. A revolution in the telecom industry has been sparked by the widespread use of and increased reliance on cellular communication technology. Moreover, 5G and B5G technologies are expected to utilize an even higher-frequency range to achieve faster data transmission and lower latency communication. Consequently, while transmitting signals across various types of equipment and infrastructure, the general public is exposed to much higher frequencies of electromagnetic radiation. The increasing need for 5G NR base stations (gNodeB) has heightened public anxiety over potential negative health impacts. This study reviews recent research on the effects of electromagnetic waves on humans, particularly focusing on how these effects influence cognitive functions. Most research to date has not found significant differences in cognitive performance due to ubiquitous mobile communications. However, current research has largely been limited to 4G technologies, and the health effects of exposure to 5G user equipment (UE) and base stations in higher-frequency bands remain unexplored. If subsequent research suggests that exposure to high-frequency wireless networks significantly impacts cognitive functions, the deployment and acceptance of these technologies may face challenges and constraints. Therefore, such investigations are crucial for determining whether next-generation technologies pose no risk to individuals. [ABSTRACT FROM AUTHOR]

Radio-frequency electromagnetic field (RF-EMF) forecasting plays an important role in the evaluation of regulatory compliance, network planning and system optimization. The knowledge of RF-EMF levels is essential to ensure compliance with standards and avoid public health concerns, especially with the arrival of new frequencies and scenarios in fifth-generation (5G) and sixth generation (6G) wireless networks. This work provides a comprehensive study on time series forecasting for RF-EMF measured in frequency from 100 kHz - 3 GHz. The state-of-the-art deep learning model architectures consist of deep neural network (DNN), convolutional neural network (CNN), long-short term memory (LSTM), and transformer are applied for time series forecasting. The prediction performance is evaluated under three different scenarios - namely single-step input single-step output (SISO), multi-step input single-step output (MISO), and multi-step input multi-step output (MIMO). The findings from the simulation demonstrate that SISO forecasting is inadequate in predicting long-term radio-frequency electromagnetic fields (RF-EMF) data as it lacks accuracy while MISO and MIMO forecasting scenarios offer more precise predictions. Specifically, in these two scenarios where the input width and label width are both set to 20 steps, the LSTM and CNN models exhibit superior performance compared to other models. Nonetheless, as the input width and label width in a MIMO scenario increase, the accuracy of both CNN and LSTM models decline considerably, whereas the transformer model consistently maintains good performance. Additionally, the transformer model continues to deliver accurate predictions as the label width and shift length increase, which is not the case for DNN, CNN, and LSTM models.

The latest cellular technology, known as 5G-NR, is intended to significantly speed up and improve the effectiveness of wireless systems. A revolution in the telecom industry has been sparked by the widespread use of and increased reliance on cellular communication technology. Moreover, 5G and B5G technologies are expected to utilize an even higher-frequency range to achieve faster data transmission and lower latency communication. Consequently, while transmitting signals across various types of equipment and infrastructure, the general public is exposed to much higher frequencies of electromagnetic radiation. The increasing need for 5G NR base stations (gNodeB) has heightened public anxiety over potential negative health impacts. This study reviews recent research on the effects of electromagnetic waves on humans, particularly focusing on how these effects influence cognitive functions. Most research to date has not found significant differences in cognitive performance due to ubiquitous mobile communications. However, current research has largely been limited to 4G technologies, and the health effects of exposure to 5G user equipment (UE) and base stations in higher-frequency bands remain unexplored. If subsequent research suggests that exposure to high-frequency wireless networks significantly impacts cognitive functions, the deployment and acceptance of these technologies may face challenges and constraints. Therefore, such investigations are crucial for determining whether next-generation technologies pose no risk to individuals.

Accurate predictions of radio frequency electromagnetic field (RF-EMF) levels can help implement measures to reduce exposure and check regulatory compliance. Therefore, this study aims to predict the RF-EMF levels in the medium using an artificial neural network (ANN). The work was conducted at Ondokuz Mayis University, Kurupelit Campus, where the measurement location has line-of-sight to the base stations. Band selective measurements were also performed to assess the contribution of 2G/3G/4G services to the total RF-EMF level, which was found to be the highest among all services within the total band. Long-term RF-EMF measurements were carried out for 35 days within the frequencies of 100 kHz to 3 GHz. Then, an ANN model with Levenberg–Marquardt (LM) and Bayesian Regulation (BR) algorithms was proposed, which utilized inputs from real-time RF-EMF measurements. The performance of the models was assessed in terms of mean squared error (MSE) and regression performance. The average MSE and regression performances of the models were similar, with the lowest testing MSEs of 2.78 × 10−3 and 3.76 × 10−3 for LM and BR methods, respectively. The analysis of the models showed that the proposed models help to predict the RF-EMF level in the medium with up to 99% accuracy. [ABSTRACT FROM AUTHOR]

5G is the next-generation mobile communication technology that is expected to deliver better data rates than Long-Term Evolution (LTE). It offers ultra-low latency and ultra-high dependability, enabling revolutionary services across sectors. However, 5G mmWave base stations may emit harmful radiofrequency electromagnetic fields (RF-EMF), raising questions about health and safety. Our research suggests that the RF-EMF prediction model lacks sufficient papers or publications. Therefore, this study employs IEEE and ICNIRP standards for assessment and exposure limits. The measuring campaign analyses one sector of a 5G base station (5G-BS) operating on 29.5 GHz in Cyberjaya, Malaysia. This study proposes two prediction models. The first model predicts the signal beam RF-EMF, while the second predicts the base station RF-EMF. Each model contains three machine learning techniques to forecast RF-EMF values: Approximate-RBFNN, Exact-RBFNN, and GRNN. The results are analysed and compared with the measured data, determining which algorithm is more accurate by calculating the RMSE of each algorithm. As a result, it can be observed that the Exact-RBFNN algorithm is the best algorithm to predict the RF-EMF because it shows good agreement with the measured value. Moreover, in a 1-minute duration, the difference between the predicted and measured values reached 0.2 less channels. However, in 6 minutes and 30 minutes, it can observe more accurate results since the differences between values reach 0.1 in these situations. Additionally, the ICNIRP standard was used and compared with the results and validation values of the algorithms.

Background: A preliminary job-exposure matrix (JEM) for radiofrequency electromagnetic fields (RF-EMF) was created based on self-reported occupational information from a multi-country population-based study of approximately 10,000 participants combined with available measurement data compiled in a source-exposure matrix (spot measurements). In order to address the limited personal occupational RF-EMF measurement data available in the literature, we performed a measurement campaign among workers in various occupations in Spain and France. Methods: Personal full-shift measurements were conducted using RadMan 2XT™ (Narda) devices. A worker diary was used to capture information on occupational and background sources of RF exposure during the shift. Inclusion of occupations to be measured was initially based on exposure prevalence and level information in the preliminary JEM and expert judgment. Results: Personal full-shift measurements were conducted among 333 workers representing 46 ISCO88 occupations. Exposure to electric (E) and magnetic (H) fields was infrequent with >99% of measurements below the detection limit of the device (≥1% of the 1998 ICNIRP standards). A total of 50.2% and 77.2% of workers were ever exposed to E and H fields respectively (having at least one recorded 1-second measurement above the detection limit). Workers in elementary occupations, technicians and associate professionals, plant and machine operators and assemblers had somewhat greater numbers of measurements above the detection limit, higher maximum values and longer exposure durations. A small proportion of measurements were ≥100% of the standards, though these exceedances were brief (generally a few seconds in duration). Female workers and workers reporting use of any RF-EMF emitting source were more likely to have a measured exposure to E and H fields. Conclusion: We conducted personal RF-EMF measurements among workers in various occupations in Spain and France. Overall, RF-EMF exposure ≥1 % ICNIRP was infrequent, despite some intermittent exposures ≥100% observed among workers in some occupations.

This paper deals with the assessment of induced specific absorption rate (SAR) in various human models under different exposure scenarios, including both laboratory measurements and simulations. Firstly, SAR values were measured in a standardized SAR laboratory using a phantom for two radiofrequency electromagnetic field (RF-EMF) sources at 900 MHz and 1800 MHz. These laboratory measurements served as a reference for SAR calculations conducted on a specific anthropomorphic mannequin (SAM) using a computer simulation technology (CST) program, thus enabling the determination of antenna location and excitation signal levels for further evaluation. Subsequently, simulations were carried out with CST to evaluate average SAR for the head and for specific head tissues such as the brain, muscles, and fat. Realistic computational human models were also used alongside SAM in CST to explore the influence of gender, age, and tissue type on SAR. Various power levels representing low, moderate, and high RF-EMF exposure were applied to the human models to compare against basic restrictions and reference levels. The simulation results indicate significantly higher SAR values calculated for 1800 MHz compared with 900 MHz. The ratio of the highest SAR values at 1800 MHz to 900 MHz is approximately 1.70 for a baby, 2.59 for a child, and 2.84 for both adult female and adult male. While the SAR values for the brain, fat, muscle, and head are comparable at 900 MHz for the baby, the brain's SAR value at 1800 MHz stands out significantly from the other tissues. In contrast with the baby, the difference in SAR values between 900 MHz and 1800 MHz is more pronounced for the child, adult female and adult male. The lowest SAR values at 900 MHz and 1800 MHz were obtained for brain tissue in all human models, while the head has the highest SAR value. The maximum SAR change ratio between the brain and the head is calculated to be 4.44 for the male at 1800 MHz. The results reveal that, although the applied electromagnetic field levels were below reference levels for general public local exposure, some local SAR values exceeded the International Commission of Non-Ionizing Radiation Protection's basic restriction for the general public at certain power levels, particularly at 1800 MHz. The SAR analysis derived from this study is significant in understanding the impact of wireless technologies on health, establishing safety standards, guiding technology advancement, conducting risk assessments, and increasing public awareness. [ABSTRACT FROM AUTHOR]

With the increasing use of wireless communication systems, assessment of exposure to radio-frequency electromagnetic field (RF-EMF) has now become very important due to the rise of public risk perception. Since people spend more than 70% of their daily time in indoor environments, including home, office, and car, the efforts devoted to indoor RF-EMF exposure assessment has also increased. However, assessment of indoor exposure to RF-EMF using a deterministic approach is challenging and time consuming task as it is affected by uncertainties due to the complexity of the indoor environment and furniture structure, existence of multiple reflection, refraction, diffraction and scattering, temporal variability of exposure, and existence of many obstructions with unknown dielectric properties. Moreover, it is also affected by the existence of uncontrolled factors that can influence the indoor RF-EMF exposure such as the constant movement of people and random movement of furniture and doors as people are working in the building. In this study, a statistical approach is utilized to characterize and model the total indoor RF-EMF down-link (DL) exposure from all cellular bands on each floor over the length of a wing since the significance of distance is very low between any two points on each floor in a wing and the variation of RF-EMF DL exposure is mainly influenced by the local indoor environment. Measurements were conducted in three buildings that are located within a few hundred meters vicinity of two base station sites supporting several cellular technologies (2G, 3G, 4G, and 5G). We apply the one-sample Kolmogorov–Smirnov test on the measurement data, and we prove that the indoor RF-EMF DL exposure on each floor over the length of a wing is a random process governed by a Gaussian distribution. We validate this proposition using leave-one-out cross validation technique. Consequently, we conclude that the indoor RF-EMF DL exposure on each floor over the length of a wing can be modeled by a Gaussian distribution and, therefore, can be characterized by the mean and the standard deviation parameters. [ABSTRACT FROM AUTHOR]

This paper compares different low-cost sensors that can measure (5G) RF-EMF exposure. The sensors are either commercially available (off-the-shelf Software Defined Radio (SDR) Adalm Pluto) or constructed by a research institution (i.e., imec-WAVES, Ghent University and Smart Sensor Systems research group (S³R), The Hague University of Applied Sciences). Both in-lab (GTEM cell) and in-situ measurements have been performed for this comparison. The in-lab measurements tested the linearity and sensitivity, which can then be used to calibrate the sensors. The in-situ testing confirmed that the low-cost hardware sensors and SDR can be used to assess the RF-EMF radiation. The variability between the sensors was 1.78 dB on average, with a maximum deviation of 5.26 dB. Values between 0.09 V/m and 2.44 V/m were obtained at a distance of about 50 m from the base station. These devices can be used to provide the general public and governments with temporal and spatial 5G electromagnetic field values. [ABSTRACT FROM AUTHOR]

The outcome of electromagnetic Radiated Emissions has risky result on human health. However, telecom service providers are bothered about quality of service of mobile services after fulfilment of firm rules about cell tower radiations. In this paper we have studied the electromagnetic radiation exposure under the super cyclone storm yaas and also we have observed electric field strength, magnetic field strength, power density and also some atmospheric parameters. Analyses has been captured by using Electromagnetic field strength Meter- KM 195. Electromagnetic radiation is produced primarily by GSM (Global System for Mobile Communication) technology of wireless communication built on the electromagnetic emitters (GSM antennas) necessary for encompassing wider territorial areas. Base Transceiver Stations (BTS) generate non-ionizing Radio Frequency (RF) energy that is radiated across its antennas into space.

(1) Background: This work aims to assess human exposure to EMF due to two different wearable antennas tuned to two 5G bands. (2) Methods: The first one was centered in the lower 5G band, around f = 3.5 GHz, whereas the second one was tuned to the upper 5G band, at 26.5 GHz. Both antennas were positioned on the trunk of four simulated human models. The exposure assessment was performed by electromagnetic numerical simulations. Exposure levels were assessed by quantifying the specific absorption rate averaged on 10 g of tissue (SAR10g) and the absorbed power density (Sab), depending on the frequency of the wearable antenna. (3) Results: the higher exposure values that resulted were always mainly concentrated in a superficial area just below the antenna itself. In addition, these resulting distributions were narrowed around their peak values and tended to flatten toward lower values in farther anatomical body regions. All the exposure levels complied with ICNIRP guidelines when considering realistic input power. (4) Conclusions: This work highlights the importance of performing an exposure assessment when the antenna is placed on the human wearer, considering the growth of wearable technology and its wide variety of application, particularly regarding future 5G networks. [ABSTRACT FROM AUTHOR]

Accurate predictions of radio frequency electromagnetic field (RF-EMF) levels can help implement measures to reduce exposure and check regulatory compliance. Therefore, this study aims to predict the RF-EMF levels in the medium using an artificial neural network (ANN). The work was conducted at Ondokuz Mayis University, Kurupelit Campus, where the measurement location has line-of-sight to the base stations. Band selective measurements were also performed to assess the contribution of 2G/3G/4G services to the total RF-EMF level, which was found to be the highest among all services within the total band. Long-term RF-EMF measurements were carried out for 35 days within the frequencies of 100 kHz to 3 GHz. Then, an ANN model with Levenberg–Marquardt (LM) and Bayesian Regulation (BR) algorithms was proposed, which utilized inputs from real-time RF-EMF measurements. The performance of the models was assessed in terms of mean squared error (MSE) and regression performance. The average MSE and regression performances of the models were similar, with the lowest testing MSEs of 2.78 × 10−3 and 3.76 × 10−3 for LM and BR methods, respectively. The analysis of the models showed that the proposed models help to predict the RF-EMF level in the medium with up to 99% accuracy.

Due to the ever-increasing use of mobile communications in India, health risks associated with exposure to radiofrequency electromagnetic field (RF-EMF) transmitted by mobile phones and base stations has become the focus of research. Internationally, there have been numerous studies on RF-EMF risk perception, but this issue is scarcely addressed in India. The present study evaluates the level of risk perception of Indians associated with RF-EMF exposure from mobile phones and base stations and assesses the underlying reasons for their concerns. We conducted a qualitative study on a small group of Indians (n = 25) from varied socioeconomic backgrounds, followed by a large-scale population (n = 500) survey to identify the primary issues of concern. The results show that many participants, irrespective of their social group, have a positive attitude towards mobile phones and are willing to accept the risks of using them, but are against the installation of base stations. Our study confirms that lack of knowledge about mobile communications technology, health concerns about mobile phones and base stations, community concern regarding base station deployment and media influence have a significant impact on risk perception among Indians. Carefully planned communication techniques are required to decrease risk perceptions and increase acceptance of mobile communications infrastructure. [ABSTRACT FROM AUTHOR]

Part of the population considers themselves as sensitive to the man-made electromagnetic radiation (EMF) emitted by powerlines, electric wiring, electric home appliance and the wireless communication devices and networks. Sensitivity is characterized by a broad variety of non-specific symptoms that the sensitive people claim to experience when exposed to EMF. While the experienced symptoms are currently considered as a real life impairment, the factor causing these symptoms remains unclear. So far, scientists were unable to find causality link between symptoms experienced by sensitive persons and the exposures to EMF. However, as presented in this review, the executed to-date scientific studies, examining sensitivity to EMF, are of poor quality to find the link between EMF exposures and sensitivity symptoms of some people. It is logical to consider that the sensitivity to EMF exists but the scientific methodology used to find it is of insufficient quality. It is time to drop out psychology driven provocation studies that ask about feelings-based non-specific symptoms experienced by volunteers under EMF exposure. Such research approach produces only subjective and therefore highly unreliable data that is insufficient to prove, or to disprove, causality link between EHS and EMF. There is a need for a new direction in studying sensitivity to EMF. The basis for it is the notion of a commonly known phenomenon of individual sensitivity, where individuals' responses to EMF depend on the genetic and epigenetic properties of the individual. It is proposed here that new studies, combining provocation approach, where volunteers are exposed to EMF, and high-throughput technologies of transcriptomics and proteomics are used to generate objective data, detecting molecular level biochemical responses of human body to EMF. [ABSTRACT FROM AUTHOR]

This paper deals with the assessment of induced specific absorption rate (SAR) in various human models under different exposure scenarios, including both laboratory measurements and simulations. Firstly, SAR values were measured in a standardized SAR laboratory using a phantom for two radiofrequency electromagnetic field (RF-EMF) sources at 900 MHz and 1800 MHz. These laboratory measurements served as a reference for SAR calculations conducted on a specific anthropomorphic mannequin (SAM) using a computer simulation technology (CST) program, thus enabling the determination of antenna location and excitation signal levels for further evaluation. Subsequently, simulations were carried out with CST to evaluate average SAR for the head and for specific head tissues such as the brain, muscles, and fat. Realistic computational human models were also used alongside SAM in CST to explore the influence of gender, age, and tissue type on SAR. Various power levels representing low, moderate, and high RF-EMF exposure were applied to the human models to compare against basic restrictions and reference levels. The simulation results indicate significantly higher SAR values calculated for 1800 MHz compared with 900 MHz. The ratio of the highest SAR values at 1800 MHz to 900 MHz is approximately 1.70 for a baby, 2.59 for a child, and 2.84 for both adult female and adult male. While the SAR values for the brain, fat, muscle, and head are comparable at 900 MHz for the baby, the brain’s SAR value at 1800 MHz stands out significantly from the other tissues. In contrast with the baby, the difference in SAR values between 900 MHz and 1800 MHz is more pronounced for the child, adult female and adult male. The lowest SAR values at 900 MHz and 1800 MHz were obtained for brain tissue in all human models, while the head has the highest SAR value. The maximum SAR change ratio between the brain and the head is calculated to be 4.44 for the male at 1800 MHz. The results reveal that, although the applied electromagnetic field levels were below reference levels for general public local exposure, some local SAR values exceeded the International Commission of Non-Ionizing Radiation Protection’s basic restriction for the general public at certain power levels, particularly at 1800 MHz. The SAR analysis derived from this study is significant in understanding the impact of wireless technologies on health, establishing safety standards, guiding technology advancement, conducting risk assessments, and increasing public awareness.

Wireless phones (both mobile and cordless) emit not only radiofrequency (RF) electromagnetic fields (EMF) but also extremely low frequency (ELF) magnetic fields, both of which should be considered in epidemiological studies of the possible adverse health effects of use of such devices. This paper describes a unique algorithm, developed for the multinational case-control MOBI-Kids study, that estimates the cumulative specific energy (CSE) and the cumulative induced current density (CICD) in the brain from RF and ELF fields, respectively, for each subject in the study (aged 10–24 years old). Factors such as age, tumour location, self-reported phone models and usage patterns (laterality, call frequency/duration and hands-free use) were considered, as was the prevalence of different communication systems over time.Median CSE and CICD were substantially higher in GSM than 3G systems and varied considerably with location in the brain. Agreement between RF CSE and mobile phone use variables was moderate to null, depending on the communication system. Agreement between mobile phone use variables and ELF CICD was higher overall but also strongly dependent on communication system. Despite ELF dose distribution across the brain being more diffuse than that of RF, high correlation was observed between RF and ELF dose.The algorithm was used to systematically estimate the localised RF and ELF doses in the brain from wireless phones, which were found to be strongly dependent on location and communication system. Analysis of cartographies showed high correlation across phone models and across ages, however diagonal agreement between these cartographies suggest these factors do affect dose distribution to some level. Overall, duration and number of calls may not be adequate proxies of dose, particularly as communication systems available for voice calls tend to become more complex with time.

The outcome of electromagnetic Radiated Emissions has risky result on human health. However, telecom service providers are bothered about quality of service of mobile services after fulfilment of firm rules about cell tower radiations. In this paper we have studied the electromagnetic radiation exposure under the super cyclone storm yaas and also we have observed electric field strength, magnetic field strength, power density and also some atmospheric parameters. Analyses has been captured by using Electromagnetic field strength Meter- KM 195. Electromagnetic radiation is produced primarily by GSM (Global System for Mobile Communication) technology of wireless communication built on the electromagnetic emitters (GSM antennas) necessary for encompassing wider territorial areas. Base Transceiver Stations (BTS) generate non-ionizing Radio Frequency (RF) energy that is radiated across its antennas into space. [ABSTRACT FROM AUTHOR]

The growing concerns regarding the adverse biological effects of radiofrequency electromagnetic fields (RF-EMFs), which are generated by common electronic devices, on the human brain led us to investigate their impact on Alzheimer’s disease (AD). We aimed to establish the effects of RF-EMF on the expression of molecular markers associated with amyloid precursor protein (APP), cell death, and clonogenic survival in HT22 and APP-overexpressing 7w-PSML cells. We compared the effects of RF-EMF at a high specific absorption rate (SAR) level with the neuronal-cell-death-inducing effects of ionizing radiation (IR). RF-EMF exposure (8 W/kg SAR) promoted the protein expression of ADAM10 (α-secretase) in the HT22 cells (p < 0.05) and downregulated the APP mRNA level in the 7w-PSML cells (p < 0.01). In contrast, IR (10 Gy) significantly reduced the APP and a disintegrin and metalloproteinase 10 (ADAM10) levels without altering their respective mRNA levels in these cells. Interestingly, IR exposure significantly upregulated BACE1 (β-secretase) at both the protein and mRNA levels, suggesting adverse effects in AD. IR induced cell death and reduced clonogenic survival in both cell lines. Although RF-EMF (high SAR level) influenced APP processing, it did not induce any deleterious change in either cell line. Thus, further studies are necessary to clarify the influence of RF-EMF on AD.

Background: Although there have been many studies investigating the effects of electromagnetic fields on humans cells and tissues, the effects of radiofrequency electromagnetic fields exposure on the cells of the immune system are still controversial. Objective: To investigate the effects of 1800 MHz RF-EMF exposure on peripheral blood mononuclear cells by measuring T helper cells count and the cytokine profile under different conditions of durations and distances. Methods: The peripheral blood mononuclear cells (PBMCs) from healthy human subjects were exposed to 1800 MHz RF-EMF, with durations of 15, 30, 45, and 60 minutes and distances of 5 and 25 cm. The effects of RFEMF exposure on the number of CD4+ T cells, and the expression of IL-2,IL-10, and IL-17a after 48 hours of culture were evaluated using flow cytometry. Results: Our findings indicated that closer distance and longer exposure inducedlower number of CD4+ T cells. Similarly the percentagesof IL-2, IL-10 and IL-17a expressing CD4+ T cells weredecreased significantly. The number of IL-2 expressing CD4+T cells wasincreased significantly as the duration of exposure was increased, but the number was decreased after 60 minutes exposure when compared with control group with no exposure. Conclusions: Exposure to RF-EMF for 60 minutes at 5 cm distance causes a significant reduction in the number of CD4+ T cells, IL-2, IL-10 and IL-17a expressing T cells.

This paper compares different low-cost sensors that can measure (5G) RF-EMF exposure. The sensors are either commercially available (off-the-shelf Software Defined Radio (SDR) Adalm Pluto) or constructed by a research institution (i.e., imec-WAVES, Ghent University and Smart Sensor Systems research group (S³R), The Hague University of Applied Sciences). Both in-lab (GTEM cell) and in-situ measurements have been performed for this comparison. The in-lab measurements tested the linearity and sensitivity, which can then be used to calibrate the sensors. The in-situ testing confirmed that the low-cost hardware sensors and SDR can be used to assess the RF-EMF radiation. The variability between the sensors was 1.78 dB on average, with a maximum deviation of 5.26 dB. Values between 0.09 V/m and 2.44 V/m were obtained at a distance of about 50 m from the base station. These devices can be used to provide the general public and governments with temporal and spatial 5G electromagnetic field values.

With the increasing use of wireless communication systems, assessment of exposure to radio-frequency electromagnetic field (RF-EMF) has now become very important due to the rise of public risk perception. Since people spend more than 70% of their daily time in indoor environments, including home, office, and car, the efforts devoted to indoor RF-EMF exposure assessment has also increased. However, assessment of indoor exposure to RF-EMF using a deterministic approach is challenging and time consuming task as it is affected by uncertainties due to the complexity of the indoor environment and furniture structure, existence of multiple reflection, refraction, diffraction and scattering, temporal variability of exposure, and existence of many obstructions with unknown dielectric properties. Moreover, it is also affected by the existence of uncontrolled factors that can influence the indoor RF-EMF exposure such as the constant movement of people and random movement of furniture and doors as people are working in the building. In this study, a statistical approach is utilized to characterize and model the total indoor RF-EMF down-link (DL) exposure from all cellular bands on each floor over the length of a wing since the significance of distance is very low between any two points on each floor in a wing and the variation of RF-EMF DL exposure is mainly influenced by the local indoor environment. Measurements were conducted in three buildings that are located within a few hundred meters vicinity of two base station sites supporting several cellular technologies (2G, 3G, 4G, and 5G). We apply the one-sample Kolmogorov–Smirnov test on the measurement data, and we prove that the indoor RF-EMF DL exposure on each floor over the length of a wing is a random process governed by a Gaussian distribution. We validate this proposition using leave-one-out cross validation technique. Consequently, we conclude that the indoor RF-EMF DL exposure on each floor over the length of a wing can be modeled by a Gaussian distribution and, therefore, can be characterized by the mean and the standard deviation parameters.

Background: Exposure to radiofrequency electromagnetic fields (RF-EMF) is often measured with personal exposimeters, but the accuracy of measurements can be hampered as carrying the devices on-body may result in body shielding. Further, the compact design may compromise the frequency selectivity of the sensor. The aim of this study was to compare measurements obtained using a multi-band body-worn distributed-exposimeter (BWDM) with two commercially available personal exposimeters (ExpoM-RF and EmeSpy 200) under real-life conditions. Methods: The BWDM measured power density in 10 frequency bands (800, 900, 1800, 2100, 2600 MHz, DECT 1900 MHz, WiFi 2.4 GHz; with separate uplink/downlink bands for 900, 1800 and 2100 MHz); using 20 separate antennas integrated in a vest and placed on diametrically opposite locations on the body, to minimize body-shielding. RF-EMF exposure data were collected from several microenvironments (e.g. shopping areas, train stations, outdoor rural/ urban residential environments, etc.) by walking around pre-defined areas/routes in Belgium, Spain, France, the Netherlands and Switzerland. Measurements were taken every 1–4 s with the BWDM in parallel with an ExpoM-RF and an EmeSpy 200 exposimeter. We calculated medians and interquartile ranges (IQRs) and compared difference, ratios and correlations of geometric mean RF-EMF exposure levels per microenvironment as measured with the exposimeters and the BWDM. Results: Across 267 microenvironments, medians and IQR of total BWDM measured RF-EMF exposure was 0.13 (0.05–0.33) mW/m2. Difference: IQR of exposimeters minus BWDM exposure levels was −0.011 (−0.049 to 0.0095) mW/m2 for the ExpoM-RF and −0.056 (−0.14 to −0.017) for the EmeSpy 200; ratios (exposimeter/BWDM) of total exposure had an IQR of 0.79 (0.55–1.1) for the ExpoM-RF and 0.29 (0.22–0.38) for the EmeSpy 200. Spearman correlations were 0.93 for the ExpoM-RF vs the BWDM and 0.96 for the EmeSpy 200 vs the BWDM. Discussion and conclusions: Results indicate that exposimeters worn on-body provide somewhat lower total RF-EMF exposure as compared to measurements conducted with the BWDM, in line with effects from body shielding. Ranking of exposure levels of microenvironments showed high correspondence between the different device types. Our results are informative for the interpretation of existing epidemiological research results.

(1) Background: This work aims to assess human exposure to EMF due to two different wearable antennas tuned to two 5G bands. (2) Methods: The first one was centered in the lower 5G band, around f = 3.5 GHz, whereas the second one was tuned to the upper 5G band, at 26.5 GHz. Both antennas were positioned on the trunk of four simulated human models. The exposure assessment was performed by electromagnetic numerical simulations. Exposure levels were assessed by quantifying the specific absorption rate averaged on 10 g of tissue (SAR10g) and the absorbed power density (Sab), depending on the frequency of the wearable antenna. (3) Results: the higher exposure values that resulted were always mainly concentrated in a superficial area just below the antenna itself. In addition, these resulting distributions were narrowed around their peak values and tended to flatten toward lower values in farther anatomical body regions. All the exposure levels complied with ICNIRP guidelines when considering realistic input power. (4) Conclusions: This work highlights the importance of performing an exposure assessment when the antenna is placed on the human wearer, considering the growth of wearable technology and its wide variety of application, particularly regarding future 5G networks.

The aim of this study was to examine the potential effects of long-term evolution (LTE) radiofrequency electromagnetic fields (RF-EMF) on cell proliferation using SH-SY5Y neuronal cells. The growth rate and proliferation of SH-SY5Y cells were significantly decreased upon exposure to 1760 MHz RF-EMF at 4 W/kg specific absorption rate (SAR) for 4 hr/day for 4 days. Cell cycle analysis indicated that the cell cycle was delayed in the G0/G1 phase after RF-EMF exposure. However, DNA damage or apoptosis was not involved in the reduced cellular proliferation following RF-EMF exposure because the expression levels of histone H2A.X at Ser139 (γH2AX) were not markedly altered and the apoptotic pathway was not activated. However, SH-SY5Y cells exposed to RF-EMF exhibited a significant elevation in Akt and mTOR phosphorylation levels. In addition, the total amount of p53 and phosphorylated-p53 was significantly increased. Data suggested that Akt/mTOR-mediated cellular senescence led to p53 activation via stimulation of the mTOR pathway in SH-SY5Y cells. The transcriptional activation of p53 led to a rise in expression of cyclin-dependent kinase (CDK) inhibitors p21 and p27. Further, subsequent inhibition of CDK2 and CDK4 produced a fall in phosphorylated retinoblastoma (pRb at Ser807/811), which decreased cell proliferation. Taken together, these data suggest that exposure to RF-EMF might induce Akt/mTOR-mediated cellular senescence, which may delay the cell cycle without triggering DNA damage in SH-SY5Y neuroblastoma cells. [ABSTRACT FROM AUTHOR]

Abstract Introduction Due to public concerns about deleterious biological consequences of radiofrequency electromagnetic fields (RF‐EMF), the potential effects of RF‐EMF on the central nervous system have received wide consideration. Methods Here, two groups of C57BL/6 mice, aged 2 and 12 months, were exposed to 1,950‐MHz RF‐EMF at a specific absorption rate of 5.0 W/kg for chronic periods (2 hr/day and 5 days/week for 8 months). Behavioral changes were then assessed in the mice at 10 months (sham‐ or RF‐10M) and 20 months (sham‐ or RF‐20M), on the open‐field test, the Y‐maze test, and an object recognition memory task, while biological effects were analyzed via microarray gene profiling of the hippocampus. Results Open‐field test results showed a decrease in the time duration spent at the center while there was a decrease in enhanced memory shown by the Y‐maze test and the novel object recognition test in the RF‐20M mice, compared to sham‐exposed mice, but no significant changes in the RF‐10M group. Based on a 2‐fold change cutoff, the microarray data revealed that 15 genes, which are listed as being involved in neurogenesis on Gene Ontology, were altered in both groups. Quantitative real‐time PCR for validation showed increased expression of Epha8 and Wnt6 in the hippocampi of RF‐20M group mice, although 13 additional genes showed no significant changes following RF‐EMF exposure. Conclusion Therefore, cognitive enhancement following chronic exposure for 8 months to RF‐EMF from middle age may be associated with increases in neurogenesis‐related signals in the hippocampus of C57BL/6 mice.

Introduction: Due to public concerns about deleterious biological consequences of radiofrequency electromagnetic fields (RF‐EMF), the potential effects of RF‐EMF on the central nervous system have received wide consideration. Methods: Here, two groups of C57BL/6 mice, aged 2 and 12 months, were exposed to 1,950‐MHz RF‐EMF at a specific absorption rate of 5.0 W/kg for chronic periods (2 hr/day and 5 days/week for 8 months). Behavioral changes were then assessed in the mice at 10 months (sham‐ or RF‐10M) and 20 months (sham‐ or RF‐20M), on the open‐field test, the Y‐maze test, and an object recognition memory task, while biological effects were analyzed via microarray gene profiling of the hippocampus. Results: Open‐field test results showed a decrease in the time duration spent at the center while there was a decrease in enhanced memory shown by the Y‐maze test and the novel object recognition test in the RF‐20M mice, compared to sham‐exposed mice, but no significant changes in the RF‐10M group. Based on a 2‐fold change cutoff, the microarray data revealed that 15 genes, which are listed as being involved in neurogenesis on Gene Ontology, were altered in both groups. Quantitative real‐time PCR for validation showed increased expression of Epha8 and Wnt6 in the hippocampi of RF‐20M group mice, although 13 additional genes showed no significant changes following RF‐EMF exposure. Conclusion: Therefore, cognitive enhancement following chronic exposure for 8 months to RF‐EMF from middle age may be associated with increases in neurogenesis‐related signals in the hippocampus of C57BL/6 mice. [ABSTRACT FROM AUTHOR]

In this study, we investigated the effects of short-term Long-Term Evolution(LTE) radio-frequency electromagnetic field(RF-EMF) exposure on mouse behavior and dopamine signaling to identify the relationship between RF-EMFs and attention deficit hyperactivity disorder(ADHD). In a reverberation chamber, eight-week-old male mice were exposed to EMFs of 1,760 MHz(whole-body average spe- cific absorption rate of 6 W/kg, 12 h/day) for five consecutive days. Behavioral tests were performed before and after the EMF exposure to evaluate the activity, attention, and memory of the mice. Neuro-positron emission tomography imaging targeting dopamine was also performed before and after the RF-EMF exposure. The protein expression levels of dopamine receptors(D1R and D2R), dopamine trans- porter(DAT), and tyrosine hydroxylase(TH) were analyzed in the striatum of mice. It was observed that the short-term RF-EMF exposure did not significantly affect the behavioral and dopamine signaling systems in adult mice. In this study, we optimized the behavioral test and neurological analysis of mice to investigate the effect of the RF-EMF on ADHD. Our finding can be used to investigate the relationship between RF-EMF and ADHD further under various EMF exposure conditions. [ABSTRACT FROM AUTHOR]

In this study, rats were exposed to code division multiple access(CDMA) signals at a whole-body average specific absorption rate of 2 W/kg for 1 or 8 h for five days for two weeks to evaluate the effect of exposure to 848.5 MHz CDMA signals(848.5 MHz, 77.5 V/m) on the protein expression of hippocampal HSP70. The rats in all experimental groups did not have access to food or water during exposure to radiofrequency radiation. It was found that the protein expression of hippocampal HSP70 significantly increased in the 1 h CDMA-exposed rats compared to those in the sham-exposed group. No significant change in 8 h CDMA-exposed rats was observed. [ABSTRACT FROM AUTHOR]

The specific biological effect of electromagnetic field (EMF) remains unknown even though devices present in our daily lives, such as smartphones and Wi-Fi antennae increase the environmental level of electromagnetic radiation. It is said that the human immune system is able to react to discrete environmental stimuli like EMF. To investigate the effect of 900 MHz microwave stimulation on the immune system our research aimed to analyze lymphocyte proliferation and observe and assess the basic immunoregulatory activities using a newly developed and improved anechoic chamber. Samples of mononuclear cells (PBMC) isolated from the blood of healthy donors were exposed to 900 MHz pulse-modulated radiofrequency radiation (20 V/m, SAR 0.024 W/kg) twice (15 min each) or left without irradiation (control group). Subsequently, the control and exposed cells were set up to determine several parameters characterizing T cell immunocompetence and monocyte immunogenic activity. Although the microcultures of PBMC exposed to radiofrequency radiation demonstrated higher immunogenic activity of monocytes (LM index) and T-cell response to concanavalin A than control cultures after first exposure, this parameter decreased after a second stimulation. Saturation of the interleukin-2 (IL-2) receptor rose significantly after the second day of exposure. On the other hand, response to mitogen dropped after EMF stimulation. The results suggest that PBMC are able to overcome stress caused by mitogens after stimulation with 900 MHz radiation. [ABSTRACT FROM AUTHOR]

With the rapidly increasing use of mobile phones and their close-contact usage to the brain, there are some concerns about the possible neuronal effects induced by exposure to excessive electromagnetic radiation. Exposure to a radiofrequency electromagnetic field (RF-EMF) of 835 MHz (4.0 W/kg specific absorption rate (SAR) 5 h/day for 12 weeks) may affect hypothalamic presynaptic neurons in C57BL/6 mice. The number and size of the synaptic vesicles (SVs) in the hypothalamic presynaptic terminals were significantly decreased after RF-EMF exposure. Further, the density (SVs numbers/µm) of docking and fusing SVs in the active zones of the presynaptic terminal membrane was significantly decreased in hypothalamic neurons. The expression levels of synapsin I/II and synaptotagmin 1, two regulators of SV trafficking in neurons, were also significantly decreased in the hypothalamus. In parallel, the expression of calcium channel was significantly decreased. These changes in SVs in the active zones may directly decrease the release of neurotransmitters in hypothalamic presynaptic terminals. Therefore, we further studied the possible changes in hypothalamic function by testing the core body temperature and body weight and performed the buried pellet test. The trafficking of SVs was changed by RF-EMF; however, we could not find any significant phenotypical changes in our experimental condition. [ABSTRACT FROM AUTHOR]

Background: As the use of mobile phones is increasing, public concern about the harmful effects of radiation emitted by these devices is also growing. In addition, protection questions and biological effects are among growing concerns which have remained largely unanswered. Stem cells are useful models to assess the effects of radiofrequency electromagnetic fields (RF-EMF) on other cell lines. Stem cells are undifferentiated biological cells that can differentiate into specialized cells. Adipose tissue represents an abundant and accessible source of adult stem cells. The aim of this study is to investigate the effects of GSM 900 MHz on growth and proliferation of mesenchymal stem cells derived from adipose tissue within the specific distance and intensity. Materials and Methods: ADSCs were exposed to GSM mobile phones 900 MHz with intensity of 354.6 µW/cm2 square waves (217 Hz pulse frequency, 50% duty cycle), during different exposure times ranging from 6 to 21 min/day for 5 days at 20 cm distance from the antenna. MTT assay was used to determine the growth and metabolism of cells and trypan blue test was also done for cell viability. Statistical analyses were carried out using analysis of one way ANOVA. P

The spread of radiofrequency electromagnetic fields (RF-EMF) is rising and health effects are still under investigation. RF-EMF promote oxidative stress, a condition involved in cancer onset, in several acute and chronic diseases and in vascular homeostasis. Although some evidences are still controversial, the WHO IARC classified RF-EMF as "possible carcinogenic to humans", and more recent studies suggested reproductive, metabolic and neurologic effects of RF-EMF, which are also able to alter bacterial antibiotic resistance. In this evolving scenario, although the biological effects of 5G communication systems are very scarcely investigated, an international action plan for the development of 5G networks has started, with a forthcoming increment in devices and density of small cells, and with the future use of millimeter waves (MMW). Preliminary observations showed that MMW increase skin temperature, alter gene expression, promote cellular proliferation and synthesis of proteins linked with oxidative stress, inflammatory and metabolic processes, could generate ocular damages, affect neuro-muscular dynamics. Further studies are needed to better and independently explore the health effects of RF-EMF in general and of MMW in particular. However, available findings seem sufficient to demonstrate the existence of biomedical effects, to invoke the precautionary principle, to define exposed subjects as potentially vulnerable and to revise existing limits. An adequate knowledge of pathophysiological mechanisms linking RF-EMF exposure to health risk should also be useful in the current clinical practice, in particular in consideration of evidences pointing to extrinsic factors as heavy contributors to cancer risk and to the progressive epidemiological growth of noncommunicable diseases. [ABSTRACT FROM AUTHOR]

Purpose: To systematically evaluate the effects of 1800MHz radiofrequency electromagnetic fields (RF-EMF) exposure on DNA damage and cellular functions in primary cultured neurogenic cells. Materials and methods: The primary cultured astrocytes, microglia and cortical neurons were exposed to RF-EMF at a SAR of 4.0 W/kg. The DNA damage was evaluated by γH2AX foci formation assay. The secretions of pro-inflammatory cytokines (TNF-α, IL-6 and IL-1β) in astrocytes and microglia, microglial phagocytic activity and neuronal development were examined by enzyme-linked immunosorbent assay, phagocytosis assay and immunofluorescent staining on microtubule-associated protein tau, microtubule-associated protein 2, postsynaptic density 95 and gephyrin, respectively. Results: RF-EMF exposure did not significantly induce γH2AX foci formation in three primary cultured neurogenic cells. Furthermore, RF-EMF exposure did not significantly affect the secretion of cytokines in astrocytes and microglia, and the morphological indicators of dendrites or synapses of cortical neurons. However, the exposure significantly reduced the phagocytic activity of microglia and inhibited the axon branch length and branch number of cortical neurons. Conclusions: Our data demonstrated that exposure to RF-EMF did not elicit DNA damage but inhibited the phagocytic ability of microglia and the axon branch length and branch number of cortical neurons. [ABSTRACT FROM AUTHOR]

Given the increased public concern about the deleterious biological consequences of radiofrequency electromagnetic fields (RF-EMFs), the involvement of RF-EMFs in neurodegenerative diseases, especially Alzheimer’s disease (AD), has received increased consideration. To investigate the effect of long-term RF-EMF exposure on AD progression, we exposed 5xFAD mice to 1950 MHz RF-EMF at a specific absorption rate of 5.0 W/kg for 2 h/day and 5 days/week for 8 months. Behavioral changes were assessed by an open field test and an object recognition memory task after RF exposure was terminated. In addition, cerebral glucose metabolism was analyzed in the brains of the 5xFAD mice using 18F-deoxyglucose positron emission tomography. The hyperactivity-like and anxiolytic behaviors of the 5xFAD mice in open field tests were rescued by RF exposure. Furthermore, long-term RF-EMF exposure improved the cognitive deficits of 5xFAD mice that were observed in the object recognition memory test. Consistent with the behavioral changes, glucose metabolism in the hippocampus and amygdala regions of the brains of 5xFAD mice following RF exposure was significantly increased compared to glucose metabolism in the brains of sham-exposed mice. These data suggest that long-term exposure to RF-EMF might exert beneficial effects on AD in 5xFAD mice. [ABSTRACT FROM AUTHOR]

Cell phones and electronic appliances and devices are inseparable from most people in modern society and the electromagnetic field (EMF) from the devices is a potential health threat. Although the direct health effect of a cell phone and its radiofrequency (RF) EMF to human is still elusive, the effect to unicellular organisms is rather apparent. Human microbiota, including skin microbiota, has been linked to a very significant role in the health of a host human body. It is important to understand the response of human skin microbiota to the RF-EMF from cell phones and personal electronic devices, since this may be one of the potential mechanisms of a human health threat brought about by the disruption of the intimate and balanced host-microbiota relationship. Here, we investigated the response of both laboratory culture strains and isolates of skin bacteria under static magnetic field (SMF) and RF-EMF. The growth patterns of laboratory cultures of Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus epidermidis under SMF were variable per different species. The bacterial isolates of skin microbiota from 4 subjects with different cell phone usage history also showed inconsistent growth responses. These findings led us to hypothesize that cell phone level RF-EMF disrupts human skin microbiota. Thus, the results from the current study lay ground for more comprehensive research on the effect of RF-EMF on human health through the human-microbiota relationship. [ABSTRACT FROM AUTHOR]

Introduction Modern sensor technology makes it possible to collect vast amounts of environmental, behavioural and health data. These data are often linked to contextual information on for example exposure sources which is separately collected with considerable lag time, leading to complications in assessing transient and/or highly spatially variable environmental exposures. Context-Sensitive Ecological Momentary Assessments 1 1 CS-EMA: Context-Sensitive Ecological Momentary Assessment. (CS-EMAs) could be used to address this. We present a case study using radiofrequency-electromagnetic fields (RF-EMF) exposure as an example for implementing CS-EMA in environmental research. Methods Participants were asked to install a custom application on their own smartphone and to wear an RF-EMF exposimeter for 48 h. Questionnaires were triggered by the application based on a continuous data stream from the exposimeter. Triggers were divided into four categories: relative and absolute exposure levels, phone calls, and control condition. After the two days of use participants filled in an evaluation questionnaire. Results 74% of all CS-EMAs were completed, with an average time of 31 s to complete a questionnaire once it was opened. Participants reported minimal influence on daily activities. There were no significant differences found between well-being and type of RF-EMF exposure. Conclusions We show that a CS-EMA based method could be used in environmental research. Using several examples involving environmental stressors, we discuss both current and future applications of this methodology in studying potential health effects of environmental factors. [ABSTRACT FROM AUTHOR]