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Abstract

Background and Objective Human brain appears to be able to absorb, detect, and respond to low-level extremely low-frequency electromagnetic fields (ELF EMF). Controlled laboratory studies on human sleep under exposure to such fields are scarce. Only sleep-disturbing effects on nighttime sleep were reported for frequencies of 50/60 Hz, while lower frequencies (i.e., below 20 Hz) have not been tested. These frequencies overlap with the frequency range of the electroencephalographic (EEG) signal, and sleep researchers utilized the specific frequency patterns (1–15 Hz) for subdivision of the sleep-wake state continuum into wake and sleep stages. In particular, the deepest sleep stage (N3) is characterized by slow-wave EEG activity (1–4 Hz) and serves as an electrophysiological indicator of sleep restorative function. We examined the effects of exposure to a low-level ELF EMF on sleep architecture in afternoon naps. Methods Ten polysomnographic sleep characteristics obtained during two naps of 23 healthy volunteers, either with or without exposure to a 1 Hz/0.004 μT electromagnetic field, were compared. Results The effect of the 1 Hz/0.004 μT electromagnetic field exposure on amount of stage N3 was not significant despite the overlap of this intervention frequency with the frequency of slow waves. However, the total duration of sleep was significantly increased due to a significant increase of amount of stage N2. Thus, the exposure to an extremely slow (1 Hz) electromagnetic field did not reveal any sleep-disturbing effects. Instead, total duration of sleep increased due to increase of N2 amount. Conclusions A sleep-promoting action of exposure to the low-level 1 Hz electromagnetic field cannot be excluded.
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pISSN 2093-9175 / eISSN 2233-8853 https://doi.org/10.17241/smr.2019.00486
Effects of Exposure to a Weak Extremely Low
Frequency Electromagnetic Field on Daytime
Sleep Architecture and Length
Vladimir B. Dorokhov, PhD1,2, Anton I. Taranov1, Anna M. Narbut3, Dmitry S. Sakharov1, Svetlana S. Gruzdeva1,
Olga N. Tkachenko, PhD1, Gleb N. Arsen’ev1, Ilya S. Blochin1,2, Arcady A. Putilov, PhD1
1Laboratory of Sleep/Wake Neurobiology, Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow,
Russia 2Sleep & Wake Neurotech Center, Skolkovo, Russia
3Department of Nervous Diseases, Institute of Professional Education, Sechenov First Moscow State Medical University, Moscow, Russia
Background and ObjectiveaaHuman brain appears to be able to absorb, detect, and
respond to low-level extremely low-frequency electromagnetic fields (ELF EMF). Controlled
laboratory studies on human sleep under exposure to such fields are scarce. Only sleep-
disturbing effects on nighttime sleep were reported for frequencies of 50/60 Hz, while lower
frequencies (i.e., below 20 Hz) have not been tested. These frequencies overlap with the
frequency range of the electroencephalographic (EEG) signal, and sleep researchers utilized
the specific frequency patterns (1–15 Hz) for subdivision of the sleep-wake state continuum
into wake and sleep stages. In particular, the deepest sleep stage (N3) is characterized by
slow-wave EEG activity (1–4 Hz) and serves as an electrophysiological indicator of sleep
restorative function. We examined the effects of exposure to a low-level
Received: November 29, 2019
Revised: December 18, 2019
Accepted: December 18, 2019
Correspondence
Arcady A. Putilov, PhD
Laboratory of Sleep/Wake
Neurobiology,
Institute of Higher Nervous Activity
and Neurophysiology, Russian
Academy of Sciences, Moscow, 11
Nipkowst., Berlin 12489, Germany
Tel +49-30-53674643
Fax +49-30-53674643
E-mail putilov@ngs.ru
ORCID
Vladimir B. Dorokhov
https://orcid.org/0000-0003-3533-
9496 Anton I. Taranov
https://orcid.org/0000-0003-4905-
8249 Anna M. Narbut
https://orcid.org/0000-0003-2026-
5199 Dmitry S. Sakharov
https://orcid.org/0000-0001-9333-
586X Svetlana S. Gruzdeva
https://orcid.org/0000-0002-5647-
5684 Olga N. Tkachenko
https://orcid.org/0000-0002-5100-
8980 Gleb N. Arsen’ev
https://orcid.org/0000-0003-3723-
7354 Ilya S. Blochin
https://orcid.org/0000-0003-1083-
4255 Arcady A. Putilov
https://orcid.org/0000-0003-2779-
9046
ELF EMF on sleep architecture
in afternoon naps.
MethodsaaTen
polysomnographic sleep
characteristics obtained during
two naps of 23 healthy volunteers, either with or without exposure to a 1 Hz/0.004 μT
electromagnetic field, were compared.
ResultsaaThe effect of the 1 Hz/0.004 μT electromagnetic field exposure on amount of stage
N3 was not significant despite the overlap of this intervention frequency with the frequency
of slow waves. However, the total duration of sleep was significantly increased due to a
significant increase of amount of stage N2. Thus, the exposure to an extremely slow (1 Hz)
electromagnetic field did not reveal any sleep-disturbing effects. Instead, total duration of
sleep increased due to increase of N2 amount.
ConclusionsaaA sleep-promoting action of exposure to the low-level 1 Hz electromagnetic
field cannot be excluded. Sleep Med Res 2019;10(2):97-102
Key Wordsaa Extremely low-frequency electromagnetic fields, Post-lunch dip, Daytime
sleep quality, Slow wave sleep, Sleep stages.
INTRODUCTION
Life has evolved in an environment with exposure to extremely low-frequency
electromagnetic fields (ELF EMF) of low-level intensity from natural sources, such as
magnetic activity of the sun and fields from the earth. The total field intensity produced
by sunspots and geomagnetic field in temperate latitudes are equal to 0.3 T and 50 µT,
respectively. The human brain appears to be able to absorb, detect, and respond to low-
level ELF EMF [1]. Over the last 140 years, permanently increasing exposures to the
man-made sources have been brought, e.g., from generation, transmission, and use of
electricity for power, heating, and lighting. [2] The strengths of fields from all man-
made sources can exceed those from natural sources by several orders of magnitude. It
was estimated [3] that a modern time long-term exposure to EMF can reach several
tenths of μT. For example, in such densely populated country as the
Netherlands app. 23000 of the 7 million dwellings are situated within the 0.4 μT
magnetic
97
ORIGINAL
ARTICLE
Napping under Week Low Frequency Electromagnetic Field
Copyright © 2019 The
Korean Society of Sleep
Medicine
field zone [4].
The studies of the effects
of EMF on sleep
architecture provided
results that are often
inconclusive and/or
contradictory. For example,
the analysis of
epidemiological data on
sleep quality collected
during 10 years in the area
surrounding a short-wave
(6–22 MHz) broadcasting
station, revealed a sleep-
disturbing response to EMF
field exposure, but in poor
rather than good sleepers
[5]. Since the effects might
be mediated by either
electro-magnetic radiation
at discrete frequencies or
by broadband white noise
across the ELF spectrum,
such epidemiological
findings raise questions
regarding whether there is a
causal link between ELF
and reported effects on
human sleep (for more
details on these discussions
the review by Ohayon et al.
[6]).
To date, there have been
few controlled laboratory
studies on sleep under ELF
EMF produced in a narrow
frequency range. They were
inspired by the concerns
about exposure to EMF
generated by the electrical
power grid and electrical
devices with a frequency of
50 Hz (e.g., in Europe) or
60 Hz (e.g., in North
America). For instance, in a
double-blind placebo-
controlled study of 18
healthy volunteers
Åkerstedt et al. [7] reported
that night sleep was
impaired by exposure to a
50 Hz/1 μT EMF, but all
changes in sleep
characteristics were still
within a normal range. In the study with between-subjects design reported by Graham
and Cook [8], continuous, intermittent (1-h off/1-h on), and sham exposure of 7–9
healthy men to a 60 Hz/28.3 μT magnetic field was associated with an altered sleep
architecture in one of three (intermittent) exposure group.
It remains untested experimentally whether a low-level intensity ELF EMF with
profoundly lower than 50–60 Hz frequencies (e.g., between 1 Hz and 20 Hz) may
interfere with human sleep characteristics. These frequencies are of special interest
because they are typical for natural ELF EMF and, in the same time, they overlap with
the frequency range of the electroencephalographic (EEG) signal recorded from the
surface of human scalp. The specific frequency patterns emitted by the brain in the
range between 1 Hz and 20 Hz were utilized by sleep researchers for subdivision of
the sleep-wake state continuum into wake and sleep stages. Namely, the low frequency
activity (< 10 Hz) and the sleep spindle frequency activity (app. 12–15 Hz) are two
silent features of non-rapid eye movement (NREM) sleep. They serve for
distinguishing between stages N1, N2, and N3 of NREM sleep [9] and as markers of
the underlying sleep-wake regulating processes [10]. In particular, the deepest stage of
sleep, N3, is characterized by slow waves in 1–4 Hz frequency range. It is believed
that amplitude of these waves reflects intensity of the process of payment of sleep debt
accumulated during preceding wakefulness [10].
Therefore, we examined whether an exposure to a low-level intensity 1 Hz EMF can
increase amount of this and other stages of NREM sleep.
A rather big proportion of daytime working people can benefit from afternoon nap
[11] that regarded a potent behavioral
98 Sleep Med Res 2019;10(2):97-102
strategy minimizing sleepiness, fatigue, and impairments of cognitive and physical
functioning [12-14]. In general, the conditions of the today daytime environment are far
from being optimal for napping (e.g., due to high level of environmental noise, absence
of a comfortable bedroom near a working place, etc.). Therefore, it is of both practical
and theoretical importance to determine whether efficacy of nap can be increased by
exposure to low-level 1 Hz EMF that falls in the frequency range of slow waves (1–4
Hz) generated by the brain during the deepest sleep stage. To our knowledge, such a
possibility has not been yet experimentally examined.
Consequently, we hypothesized that, due to the overlap of the frequency of this field
with the frequency of brain waves, such an intervention might promote stage N3 and
other NREM sleep stages in a 50-min afternoon nap.
METHODS
Study volunteers (23, 19 females) were recruited among students of Moscow
Universities and young researchers. The exclusion criteria included reporting age of 18
years or younger, pregnancy or breastfeeding, colds during the previous month,
involvement in shift or night work, crossing several meridians during the previous
month, irregular sleep-wake schedule (i.e., more than 1-h difference in bedtimes
throughout the preceding week) or frequent sleep deprivation (i.e., at least, one case of
total or partial sleep deprivation in the previous week). The recruited volunteers denied
history of mental or sleep disorder and did not complain about poor physical condition
and functioning. Majority of them were familiar with the laboratory environment and
experimental napping procedure because they previously participated in a larger nap
study [15].
Each participant was informed in detail about the experimental procedures and gave
his/her written consent. The study protocol was approved by the Ethics Committee of the
Institute of Higher Nervous Activity and Neurophysiology (No. 046/19), and all
experimental procedures were performed in accordance with the ethical standards laid
down in the Declaration of Helsinki.
The participants visited
twice the sleep laboratory at
the Institute of Higher
Nervous Activity and
Neurophysiology for having
two afternoon napping
attempts with, at least, 1-
week interval between the
attempts. Each visit lasted for
less than 2 hours (between 1
p.m. and 3 p.m.). The
participants were randomly
assigned to either sham or 1
Hz/0.004 μT EMF exposure
condition. They were
uninformed about an
exposure condition and order,
and approximately a half of
them was exposed to 1 Hz
EMF during the first napping
attempt. Thus, the
experimental protocol
consisted of two 2-h visits in
the sleep laboratory divided
by, at least, 1-week interval
between 1-h afternoon
napping attempts under
randomly assigned
exposures, either sham then
treatment condition or
treatment then sham
condition. The conditions did
not differ on the number of
female participants in either
follicular or luteal phase of
their menstrual cycle.
After a brief pre-nap
interview, the 8-item
Epworth Sleepiness Scale (ESS) [16] was administered and then the electrodes for
polysomnographic recordings were applied. During the electrodes’ application
procedure, the participant was lying in bed in the sleep laboratory under dim light (<
10 lux). He/she was instructed to try to nap after light off for the following 50 min and,
after hearing the awakening signal at the 50th minute, to remain lying in bed, already
without sleep, for the final 10 min of resting polysomnographic recordings.
A researcher switched off the light using a remote light con-troller, and the recording
started with the first 10-min interval without any interventions. For the next 40 min
(until the signal asking for awakening), an EMF emitting device (the ELF EMF
generator “EcoSleep CUBE” manufactured by Center of Neurotechnology of Sleep
and Wakefulness, Skolkovo Innovation Center, Moscow, Russia; certified by the State
standard GOST R0159555 from 15. 12. 2017) was set by a researcher either on or off.
This device was placed at the distance of 700 mm from the participant’s head to allow
the generation of the 0.004 μT EMF around the head. It was unseen from the bed, and,
during any of two napping attempts, the participant cannot recognize whether it was
switched on or off. An alternating magnetic field (inductance L = 0.5 µH with the
resistance R = 15 Ω) was generated by the bifilar planar spiral coils (a coil diameter is
50 mm). The highest possible voltage of the field inductor was approximately 3 V.
The current had the form of square 1 Hz pulses with the duty factor equal to 0.5. To
calculate intensity of EMF at the distance of 700 mm from the device, the field
parameters
Dorokhov VB, et al.
were measured with the BE-METP-AT-002 (“indicator of parameters of electric and
magnetic fields,” verification certificate №AA 3442920/07356, OOO NTM-Zaschita,
Moscow, Russia). The intensity of EMF in the center of inductor B0 was 22 µT. The field
B induced at the distance r was calculated as:
B = B0 × (r0/r)2,
where r0 was equal to 10 mm. Thus, on the distance of 700 mm, EMF intensity was
found to be equal to 0.004 μT.
The polysomnographic recordings were performed via a 16-channel wireless system
(“Neuropolygraph 24,” Neurotech, Taganrog, Russia). A standard monitoring montage
was used for polysomnographic recordings, namely, the EEG channels, one chin
electromyogram channel, and two electro-oculogram channels. All electrodes were
placed in accord with the international 10–20 system of electrode placement. For
99
Table 1. Daytime sleep architecture in sham and 1 Hz/0.2 μT electromagnetic fields exposure conditions
Exposure Sham 1 Hz Difference Paired t-test
Min Mean SEM Mean SEM Mean SEM t22 p
Latency to
N1 13.09 1.85 10.63 1.29 3.16 2.62 1.033 0.313
N2 30.87 3.89 25.17 3.48 6.66 4.52 1.485 0.152
N3 42.26 3.37 41.30 3.67 2.13 4.62 0.233 0.818
Sleep length 35.20 3.05 41.13 2.18 -7.53 3.02 -2.114 0.046
Amount of
W33.89 3.10 29.11 2.84 4.78 2.87 1.665 0.110
WASO 9.09 1.85 10.24 1.57 -1.15 1.75 0.658 0.518
N1 11.30 1.58 11.28 1.75 0.02 2.23 0.010 0.992
N2 7.83 1.20 11.87 1.54 -4.04 1.70 -2.378 0.027
N3 6.44 1.77 7.17 1.83 -0.74 2.47 -0.299 0.768
R 0.54 0.54 0.57 0.40 -0.02 0.69 -0.031 0.975
N1, N2, N3, and R: sleep stages; W: wakefulness; WASO: W after sleep onset; Sleep length: time interval between the first and last
occurrence of any sleep stage; Mean and SEM: sample-averaged value of a sleep characteristic and standard error of mean. Sham and
1 Hz: the alternative conditions with the device either off or on between 10th and 50th min of 1-h napping attempt. Values of any
sleep characteristic are given in minutes. See the 60-min time courses of W, N1, N2, N3, and R in Fig. 1.
www.sleepmedres.org
Napping under Week Low Frequency Electromagnetic Field
providing a possibility of
conventional sleep stage
scoring, the placement
included a central channel
referenced to an ear mastoid
site (C4-M1), a central
channel referenced to an ear
mastoid site (C3-M2), an
occipital channel referenced
to an ear mastoid site (O1-
M2), and an occipital channel
referenced to an ear mastoid
site (O2-M1). The recorded
signals were conditioned by
the high-pass, low-pass, and
notch filters (frequencies of
0.5, 35, and 50 Hz,
respectively). The signals
were sampled and stored on a
hard disc with a frequency of
500 Hz. Conventional
scoring procedure [8] was
performed visually on 30
epochs of each 60-min
recording by two experienced
scorers. They were
uninformed about an
exposure condition. Each
record was scored by the
scorers independently, the
initial disagreement varied,
depending upon a stage, from
80% to 95%, and, thereafter,
they reexamined together all
intervals with discrepant
scores in order to produce
consensus scores. The epochs
were classified into stages
including wakefulness stage
(W), REM sleep (R), and
three stages of NREM sleep
(stage 1 sleep or N1, stage 2
sleep or N2, and slow-wave
sleep or N3). In the present
report, 10 traditional
polysomnographic
characteristics of sleep
architecture were analyzed
and reported in Table 1.
Statistical analyses were
performed with the SPSS
22.0 statistical software
package (IBM Corp.,
Armonk, NY, USA). A
Student’s paired t-test was
applied to reveal pairwise
differences between two
conditions. Additionally, two-way repeated measure analysis of variances (rANOVAs)
were run on 6 10-min intervals of each sleep stage. For each such rANOVA,
Mauchly’s test was conducted to assess the sphericity and, if necessary, the
Greenhouse-Geiser correction was used to adjust the degrees of freedom. To compare
number of participants who either entered or did not enter into stages N2 and N3, χ2-
test was employed.
RESULTS
Mean age ± standard deviation for 23 study participants was 22.09 ± 4.55.
Interestingly, after a napping attempt more than a half of them denied that they slept
during the 50-min interval, while sleep, at least, N1 (stage 1 sleep) for, at least, one
min was detected during any of napping attempts (n = 46) as suggested by the results
of scoring the polysomnographic recordings. The majority of those who reported they
were able to fall asleep usually claimed that, at the 50th min (after hearing the
awakening signal), they wish to further remain asleep. Indeed, the polysomnographic
data suggested that, at least, one of the last 20 scoring epochs (minutes from 51st to
60th, after hearing the awakening signal) was classified as a sleep stage in more than a
half of all recordings.
However, 5 study participants did not reach stage N2 (stage 2 sleep) in the sham
condition. Two of these 5 reached this stage in the treatment condition. Nevertheless, χ2-
test did not reveal a statistically significant difference between conditions (χ2 = 0.605, p
= 0.437). Almost a half of study participants did not reach stage N3, the deepest slow
wave sleep stage (10 vs. 11 in the sham vs. treatment condition, respectively). The
difference between conditions in number of participants without and with N3 also did
not reach a statistically significant level (χ2 = 0.088, p = 0.767).
Among 10 pairwise comparisons of nap characteristics shown in Table 1, a significant
increase of sleep length under exposure to 1 Hz/0.004 μT EMF was revealed by paired t-
test. This increase occurred mostly due to a significant increase in amount of N2. An
amount of N3 did not change significantly in the 1 Hz/0.004 μT EMF exposure
condition compared to the sham condition (Table 1).
Similarly, N2 was the only sleep stage for which two-way rANOVA with repeated
measures “condition” (either without or with exposure to 1 Hz/0.004 μT EMF between
the 10th and 50th min of napping attempt) and “10-min time interval” (6 10min
intervals) yielded a significant main effect of “condition” (Fig. 1). Such main effect was
significant for neither N1 nor N3 nor R nor W (Fig. 1).
In comparison of the pairs
of polysomnographic
measures representing the
first and second napping
attempts, a significant
influence of order of
exposure to 1 Hz EMF was
not found
(p > 0.05 for all 10 paired t-
tests).
The difference between
ESS scores obtained prior
napping attempts in two
(sham and treatment)
exposure conditions was
very small and non-
significant (mean ±
standard deviation equal to
-0.087 ± 1.756, t22 =
-0.238, p = 0.814). The
Spearman’s rank
correlation coefficient
between scores for these
two conditions attained the
value of 0.921 (p < 0.001).
Mean score ± standard
deviation was 8.87 ± 4.67.
In accord with cut-points
suggested by Johns [16]
and Aurora et al. [17], only
4 of 23 participants of the
study had ESS score of 11
or higher indicating either
mild (11 and 12) or
moderate excessive daytime sleepiness (13 and 15). However, this small group did not
differ significantly from the remaining sample on the polysomnographic sleep
characteristics.
DISCUSSION
Controlled laboratory studies on human sleep under lowlevel intensity ELF EMF are
scarce, and sleep-disturbing rather than sleep-promoting effects were reported in the
experiments examining frequencies generated by the electrical power grid and
electrical devices (50 and 60 Hz) [7,8]. Since lower frequency range (1–20 Hz)
overlaps with the frequency range of the most powerful spectral components of EEG
signal emitted by the brain during NREM sleep, it seems to be of special interest to
examine whether a 1 Hz EMF of close to natural intensity interferes with human sleep.
Particularly, one can speculate that the EMF of the particular frequency range (1–4
Hz) might increase an amount of the deepest sleep stage (N3) distinguished from other
stages by high amplitude slow waves and associated with slow wave activity (1–4 Hz),
an indicator of sleep restorative function. In the present pilot study, we tested
possibility to increase an amount of N3 and other NREM sleep stages by exposing 23
healthy volunteers during minutes 10– 50th of an afternoon napping attempt to a low-
level (0.004 μT) 1-Hz EMF. Although amount of N3 remained unchanged in this
exposure condition, the total duration of sleep become longer due to increase of N2
amount.
It seems that using a larger sample for further examination of the sleep-promoting
effects of exposure to a low-level 1 Hz EMF on daytime sleep quality is necessary for
demonstration of replicability of the revealed effects. Moreover, a possible
sleeppromoting rather than sleep-disturbing action of exposure to low-level ELF EMF
below 20 Hz on sleep might be further examined experimentally by comparison of
different (lower vs. higher) frequencies (e.g., in the ranges of 1–20 Hz and 33–64 Hz).
However, it has to be noted that, if the differential response to lower and higher
frequencies has been found, this finding would raise the next question regarding
whether this is due to a beneficial effect of lower frequency exposure or due to an
adverse effect of higher frequency exposure. Finally, further examination
Dorokhov VB, et al.
101
Fig. 1. Time courses of amount of wakefulness and sleep stages in sham and 1 Hz/0.004 μT electromagnetic fields (EMF) exposure
conditions. Each polysomnographic record of napping attempt was divided into 6 10-min intervals; 10, 20, 30, 40, 50, and 60 min:
amount of stage for each of 6 10-min intervals of 1-h (60-min) napping attempt with the signal of waking up at the 50th min (30-s scoring
epochs 1–20, 21–40, 41–60, 61–80, 81–100, and 101–120); W: wake state; N1, N2, N3, and R: sleep stages. Mean amounts of stages
per 10 min and standard error of mean (SEM) were obtained by applying two-way rANOVAs with repeated measures “condition” (either
without or with exposure to 1 Hz/0.004 μT EMF between the 10th and 50th min of napping attempt) and “10-min time interval” (6 10-min
intervals). The rANOVA yielded a significant main effect of “condition” (F1,22 = 5.655, p = 0.027) for N2 only, with the effect size (partial eta
squared) of 0.341. See also averaged over the whole napping attempt amounts of sleep stages in Table 1. rANOVAs: repeated measure
analysis of variances. 100 Sleep Med Res 2019;10(2):97-102
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Napping under Week Low Frequency Electromagnetic Field
might be also aimed on
testing a possibility of
reducing latency to N2 by
switching an EMF emitting
device in the very beginning
of napping attempt rather
than on its 10th minute. If
such further experimental
studies will lend support for
the assumption of sleep-
promoting rather than sleep-
disturbing action of exposure
to low-level ELF EMF, such
a non-invasive intervention
might be recommended for
improving condition of
afternoon naps aimed on
reducing daytime sleepiness
and fatigue.
In sum, results of the
present pilot study seem to
differ from the previously
reported results showed that
exposure to a lowlevel EMF
with frequencies 50 and 60
Hz has an adverse rather than
beneficial effect on human
sleep. In contrast, we found
that the exposure to a much
slower (1 Hz) EMF did not
produce any sleep-disturbing
effects. Even more, we
observed the increase of total
sleep duration due to the
increase of amount of N2.
This result suggests a
possibility of sleep-
promoting action of 1
Hz/0.004 μT EMF exposure.
A somewhat stronger
evidence for such action
might be provided by further
(confirmation) experiments
with samples of a larger size
exposed to EMF in frequency
range 1–20 Hz and by the
new experiments aimed on
comparing the effects of low-
level EMF in this frequency
range with the effects of EMF
in higher frequency range,
e.g., from 33 Hz to 64 Hz.
Acknowledgments
The studies were supported by
grants from the Russian
Foundation for Basic Research (VBD by grant number 17-36-00025-OGN-MOL-A1 and AAP by grant
number 19-013-00424).
The authors thank Ekaterina V. Tiunova and Irina A. Piletskaya form the Moscow State Pedagogical
University (Moscow, Russia) for help in conducting the experiments and the authors are very grateful to
23 unpaid volunteers for their participation in the study.
Conflicts of Interest
The authors have no financial conflicts of interest.
Authors’ Contribution
VBD, AIT, AMN, DSS, SSG, ONT, GNA, ISB, and AAP equally contributed to data collection, analysis,
and interpreting the results, and the manuscript was mostly written by AAP.
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... In two previous studies, we tested the influence of EMF of even lower frequencies (from 1 Hz to 8 Hz) on sleep of healthy young people during afternoon napping attempts. We found that sleep might be intensified under the exposure to the fields with frequencies 1 Hz or 2 Hz, as indicated by an increase in the amounts of stages N2 (Dorokhov et al. 2019) or N3 (Dorokhov et al. 2021). For instance, in the latter study the action of the sham exposure did not differ from the action of the 2 Hz and 8 Hz/0.004 μT exposures only during the first 30 min of nap, while, for the remaining 20 min, amount of N3 and EEG powers in delta and theta ranges (1 Hz-8 Hz) continued to build up under the 8 Hz/ 0.004μT exposure and, especially, under the 2 Hz/0.004μT ...
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An ever-growing number of electromagnetic (EM) emission sources elicits health concerns, particularly stemming from the ubiquitous low to extremely low frequency fields from power lines and appliances, and the radiofrequency fields emitted from telecommunication devices. In this article we review the state of knowledge regarding possible impacts of electromagnetic fields on melatonin secretion and on sleep structure and the electroencephalogram of humans. Most of the studies on the effects of melatonin on humans have been conducted in the presence of EM fields, focusing on the effects of occupational or residential exposures. While some of the earlier studies indicated that EM fields may have a suppressive effect on melatonin, the results cannot be generalized because of the large variability in exposure conditions and other factors that may influence melatonin. For instance, exposure to radiofrequency EM fields on sleep architecture show little or no effect. However, a number of studies show that pulsating radiofrequency electromagnetic fields, such as those emitted from cellular phones, can alter brain physiology, increasing the electroencephalogram power in selective bands when administered immediately prior to or during sleep. Additional research is necessary that would include older populations and evaluate the interactions of EM fields in different frequency ranges to examine their effects on sleep in humans.
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This paper estimates the change in the average exposure of the population of England and Wales to power-frequency magnetic fields between 1949 and 1989. If magnetic fields are causally linked to disease with a linear exposure - response relationship, this quantity is related to the incidence rate of the disease. The exposure is divided into components attributable to a number of sources, principally residential background fields and fields from domestic appliances and the transmission system. The 1989 average exposures from these sources are estimated as 45 nT, 20 nT and 4.2 nT respectively. For each source, an understanding of how fields arise is combined with statistics on the use of electricity and demographic statistics to estimate the change in exposure from that source. These individual changes are then combined, weighted according to the average exposure from that source. The estimated increase in overall average exposure is by a factor of 4.5, which applies to the whole population and also just to children. This increase is slightly greater than the result obtained by the simpler method of taking average domestic electricity demand per consumer, and can be treated with more confidence. There are still numerous approximations involved, some of which are identified and discussed, with the conclusion that the estimated increase is probably an underestimate.
Article
The Epworth Sleepiness Scale (ESS) and multiple sleep latency test (MSLT) are the most commonly used measures of subjective and objective sleepiness, respectively. The strength of the association between these measures as well as the optimal ESS threshold that indicates objective sleepiness remains a topic of significant interest in the clinical and research arenas. The current investigation sought to: (a) examine the association between the ESS and the average sleep latency from the MSLT using the techniques of survival analysis; (b) determine whether specific patient factors influence the association; (c) examine the utility of each ESS question; and (d) identify the optimal ESS threshold that indicates objective sleepiness. Cross-sectional study. Patients (N = 675) referred for polysomnography and MSLT. Using techniques of survival analysis, a significant association was noted between the ESS score and the average sleep latency. The adjusted hazard ratios for sleep onset during the MSLT for the ESS quartiles were 1.00 (ESS < 9), 1.32 (ESS: 10-13), 1.85 (ESS: 14-17), and 2.53 (ESS ≥ 18), respectively. The association was independent of several patient factors and was distinct for the 4 naps. Furthermore, most of the ESS questions were individually predictive of the average sleep latency except the tendency to doze off when lying down to rest in the afternoon, which was only predictive in patients with less than a college education. Finally, an ESS score ≥ 13 optimally predicted an average sleep latency < 8 minutes. In contrast to previous reports, the association between the ESS and the average sleep latency is clearly apparent when the data are analyzed by survival analysis, and most of the ESS questions are predictive of objective sleepiness. An ESS score ≥ 13 most effectively predicts objective sleepiness, which is higher than what has typically been used in clinical practice. Given the ease of administering the ESS, it represents a relatively simple and cost-effective method for identifying individuals at risk for daytime sleepiness.
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Napping is a cross-cultural phenomenon which occurs across the lifespan. People vary widely in the frequency with which they nap as well as the improvements in alertness and well-being experienced. The systematic study of daytime napping is important to understand the benefits in alertness and performance that may be accrued from napping. This review paper investigates factors that affect the benefits of napping such as duration and temporal placement of the nap. In addition, the influence of subject characteristics such as age and experience with napping is examined. The focus of the review is on benefits for healthy individuals with regular sleep/wake schedules rather than for people with sleep or medical disorders. The goal of the review is to summarize the type of performance improvements that result from napping, critique the existing studies, and make recommendations for future research.