Characterization of Levels of Extremely Low Frequency Magnetic Fields Emitted From Portable Hand‐Held Fans

2019 ◽  
Vol 40 (8) ◽  
pp. 569-577
Author(s):  
Sangjun Choi ◽  
Soyeon Kim ◽  
Seoyoun Bae ◽  
Won Kim ◽  
Ju‐Hyun Park ◽  
...  
Keyword(s):  
Magnetic Fields ◽  
Low Frequency ◽  
Extremely Low Frequency

scholarly journals Characterization of Extremely Low Frequency Magnetic Fields from Diesel, Gasoline and Hybrid Cars under Controlled Conditions

2015 ◽  
Vol 12 (2) ◽  
pp. 1651-1666 ◽  
Author(s):  
Ronen Hareuveny ◽  
Madhuri Sudan ◽  
Malka Halgamuge ◽  
Yoav Yaffe ◽  
Yuval Tzabari ◽  
...  
Keyword(s):  
Magnetic Fields ◽  
Low Frequency ◽  
Extremely Low Frequency ◽  
Controlled Conditions

scholarly journals Characterization of Children’s Exposure to Extremely Low Frequency Magnetic Fields by Stochastic Modeling

2018 ◽  
Vol 15 (9) ◽  
pp. 1963 ◽  
Author(s):  
Marta Bonato ◽  
Marta Parazzini ◽  
Emma Chiaramello ◽  
Serena Fiocchi ◽  
Laurent Le Brusquet ◽  
...  
Keyword(s):  
Magnetic Fields ◽  
Childhood Leukemia ◽  
Low Frequency ◽  
Stochastic Approach ◽  
Mean Value ◽  
P Value ◽  
Extremely Low Frequency ◽  
Increased Risk ◽  
Children’S Exposure

In this study, children’s exposure to extremely low frequency magnetic fields (ELF-MF, 40–800 Hz) is investigated. The interest in this thematic has grown due to a possible correlation between the increased risk of childhood leukemia and a daily average exposure above 0.4 µT, although the causal relationship is still uncertain. The aim of this paper was to present a new method of characterizing the children’s exposure to ELF-MF starting from personal measurements using a stochastic approach based on segmentation (and to apply it to the personal measurements themselves) of two previous projects: the ARIMMORA project and the EXPERS project. The stochastic model consisted in (i) splitting the 24 h recordings into stationary events and (ii) characterizing each event with four parameters that are easily interpretable: the duration of the event, the mean value, the dispersion of the magnetic field over the event, and a final parameter characterizing the variation speed. Afterward, the data from the two databases were divided in subgroups based on a characteristic (i.e., children’s age, number of inhabitants in the area, etc.). For every subgroup, the kernel density estimation (KDE) of each parameter was calculated and the p-value histogram of the parameters together was obtained, in order to compare the subgroups and to extract information about the children’s exposure. In conclusion, this new stochastic approach allows for the identification of the parameters that most affect the level of children’s exposure.

The characteristics and present state for Extremely Low Frequency-Magnetic Fields of metropolitan subway

2015 ◽  
Vol 14 (1) ◽  
pp. 7-15
Author(s):  
Dae-kwan Jung ◽  
◽  
Joon-sig Jung ◽  
Kyu-mok Lee ◽  
Hyung-kyu Park ◽  
...  
Keyword(s):  
Magnetic Fields ◽  
Present State ◽  
Low Frequency ◽  
Extremely Low Frequency

Occupational Exposure to Electric Shocks and Extremely Low-Frequency Magnetic Fields and Motor Neurone Disease

2020 ◽  
Author(s):  
Grace X Chen ◽  
Andrea’t Mannetje ◽  
Jeroen Douwes ◽  
Leonard H Berg ◽  
Neil Pearce ◽  
...  
Keyword(s):  
Occupational Exposure ◽  
Magnetic Fields ◽  
Low Frequency ◽  
Population Based ◽  
Motor Neurone ◽  
Motor Neurone Disease ◽  
Cumulative Exposure ◽  
Spine Injury ◽  
Extremely Low Frequency ◽  
Electric Shocks

Abstract In a New Zealand population-based case-control study we assessed associations with occupational exposure to electric shocks, extremely low-frequency magnetic fields (ELF-MF) and motor neurone disease using job-exposure matrices to assess exposure. Participants were recruited between 2013 and 2016. Associations with ever/never, duration, and cumulative exposure were assessed using logistic regression adjusted for age, sex, ethnicity, socioeconomic status, education, smoking, alcohol consumption, sports, head or spine injury and solvents, and mutually adjusted for the other exposure. All analyses were repeated stratified by sex. An elevated risk was observed for having ever worked in a job with potential for electric shocks (odds ratio (OR)=1.35, 95% confidence interval (CI): 0.98, 1.86), with the strongest association for the highest level of exposure (OR=2.01, 95%CI: 1.31, 3.09). Analysis by duration suggested a non-linear association: risk was increased for both short-duration (<3 years) (OR= 4.69, 95%CI: 2.25, 9.77) and long-duration in a job with high level of electric shock exposure (>24 years; OR=1.88; 95%CI: 1.05, 3.36), with less pronounced associations for intermediate durations. No association with ELF-MF was found. Our findings provide support for an association between occupational exposure to electric shocks and motor neurone disease but did not show associations with exposure to work-related ELF-MF.

Effects of extremely low frequency magnetic fields on pain thresholds in mice: roles of melatonin and opioids

2000 ◽  
Vol 20 (4) ◽  
pp. 259-264 ◽  
Author(s):  
J. H. Jeong ◽  
K. B. Choi ◽  
B. C. Yi ◽  
C. H. Chun ◽  
K.-Y. Sung ◽  
...  
Keyword(s):  
Magnetic Fields ◽  
Low Frequency ◽  
Pain Thresholds ◽  
Extremely Low Frequency
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