Cellular Phone Electromagnetic Field Effects on Bioelectric Activity of
N. N. Lebedeva, A. V. Sulimov, O. P. Sulimova, T. I. Kotrovskaya, and
Professor at the Institute of Higher Nervous Activity and
Neurophysiogy, Russian Academy of Sciences (Moscow); 2Ph.D., senior
researcher at the Institute of Higher Nervous Activity and
Neurophysiogy, Russian Academy of Sciences (Moscow); 3Ph.D., researcher
at the Institute of Higher Nervous Activity and Neurophysiogy, Russian
Academy of Sciences (Moscow); 4Ph.D., researcher at the "Extremely High
Frequency" Medical and Technical .Association (Moscow); 5Ph.D., senior
researcher at Deutsche Telekom AG, Germany.
ABSTRACT:24 volunteers participated in the experiments. The
investigation of EEG reactions to cellular phone (EMF frequency 902.4
MHz and intensity 0.06 mW/cm2) was conducted. Two experiments were
performed with each subject ¾ cellular phone exposure and Placebo.
Duration of the experiment was 60 min: 15 min ¾ background; 15 min ¾
EMF exposure or Placebo; 30 min ¾ afterexposure. EEG was recorded in 16
standard leads with "eyes open" and "eyes closed". Special software
with non-linear dynamics was developed for EEG analyses. One parameter,
multichannel (global) correlation dimension, was calculated. The
changes of these parameters can be evidence of brain functional state
changes. As a result of EEG record processing, a significant increase
of global correlation dimension during the exposure and afterexposure
period was discovered, more pronounced in the case of "eyes closed".
That can be viewed as the manifestation of cortex activation under
phone EMF exposure.
Technical progress has given birth to a variety of antropogenic
factors, among which industrial electromagnetic fields (EMF) have a
significant place. These EMFs contribute significantly to environment
pollution and have a pronounced effect on living beings [1-3]. Recent
research testifies that biological effects of EMFs are determined by
their biotropic parameters: intensity, frequency, shape of signal,
place of application, exposition and others [2, 4-11] as well as
properties of the living being - initial functional state, age, sex and
physic characteristics (dielectric permeability, electric conductivity
and so on) [12-17].
A number of studies are devoted to the investigation of the responses
of different systems to EMF acting on a whole organism [18-22]. Some
authors report finding a relation among a number of diseases [23-28]
and neurological syndromes (fatigue, acute and chronic headache,
depression) [29-31] and levels of industrial EMF pollution. However,
other researchers communicate a lack of pathology or only small
deviations [2, 32, 33].
Direct measures of the degree of EMF penetration into different human
organs and tissues in terms of specific absorption rate (SAR) were
conducted. SAR was measured in the bodies, mainly in the central
nervous system, of the users of wireless communication systems under
exposure, essentially 900 MHz [4-37].
It was demonstrated that the central nervous system is most sensitive
to EMF effects [2, 38-41]. Significant changes of biochemical activity
of neurons were observed during direct and intermediate EMF application
to neurons and glia, and only neurons with a high level of activity
were sensitive to weak EMF [42-46]. Microelectrode investigation allows
the recording responses of neurons of different brain areas to EMF [11,
47-49]. The sensitivity of neurons and glia to EMF was supported by
histological studies [50-52].
A large body of data shows that EMF can produce a wide diversity of
physiological and behavioral effects, such as movement activity
changes, avoidance reactions and orienting responses to EMF [7, 33, 53,
Investigations concerned with EMF effects on conditional responses
demonstrated that EMF modified the period of elaboration of conditioned
responses to EMF [55-57] and transformed the conditional response in
itself [58, 59].
Investigation of a wide range of intensity (0.2…1000 mW/ñm2) of
electromagnetic microwave effects on bioelectrical brain activity of
animals revealed such phenomena as an increase of alpha spindles
numbers, an increase of EEG synchronization, tens and hundred of
milliseconds, prolonged desynchronization - a decrease of main rhythm
amplitudes; short-term desyncronization at the onset of EMF application
and, after that; an after-effect reaction that is similar to
desyncronization but arises during the long period after the
termination of EMF application; epileptic activity.
At decimeter and centimeter wave exposure on the lateral surface of
rabbits bodies, it was revealed that, at higher thermal intensities,
the stability of EEG reactions was lower and, at lower (non-thermal)
intensities, this EEG index did not greatly depend on intensity and
even has a tendency to increase while the latter decreased .
The response of the central nervous system (CNS) after 30 min, 3mW/cm2
exposure of rats to 2.45 GHz, 217 Hz was investigated by quantitative
EEG and Visual Evoked Potential (VEP) analysis. The above-mentioned
parameters were evaluated before and after (5 min and 20 min) exposure.
It was shown that the delta band of the EEG power spectrum was
increased definitely, the alpha and beta bands were decreased in the 5
min after the exposure. These alterations disappeared 20 min after
exposure. No changes were observed in VEP .
The experiments recording cortex neuronal activity during microwave
(40mV/cm2) exposure were carried out on rabbits with preliminarily
implanted microelectrodes in the sensomotory cortex under barbital
anesthesia. The EEG reactions to the microwave exposure manifested as
the pronounced enhancement of slow waves. The changes of pulse activity
of the cortex neurons' populations were observed during this reaction.
The mean values of the interspike intervals increased, i.e., the
enhancement of inhibitory processes took place. For these changes to
occur, microwave exposure of less than 1 min was sufficient. After
terminating of exposure, the changes arose again .
CNS responses to 60 min, 50 Hz, 100 mT and 500 mT magnetic field
exposure of freely moving rats was observed by quantitative EEG. There
were no significant changes in the EEG activity (the sum of EEG
spectral bands) at 100 mT during and after exposure. In the case of 500
mT flux density, EEG activity increased significantly immediately (1st
min) and in the 20th min of exposure and 20 min after exposure
(p<0.05). Significant changes of spectral components were found at
both flux densities. Mainly, the slow frequency components increased
and the higher components decreased .
In a number of investigations of different ranges EMF effects on
volunteers EEG spectral changes were discovered. In spite of great
between-subject variability of effects the most characteristic feature
was an increase of alpha, theta and, in some cases, delta power [12,
64-66]. Similar EEG spectral changes manifesting the dominance of
inhibitor processes have been discovered by other authors [67,68].
Experimental studies of peripheral exposure (30 min and 60 min) to low
intensity MM waves (5mW/cm2) on volunteers revealed that, at a
pronounced increase of alpha-rhythm power in occipital areas of the
cortex and heightening of coherence by theta-rhythm in the
frontal-central areas were observed in the EEG. Such a pattern of
bioelectric activity testifies the development of a non-specific cortex
activation reaction, i.e., the increase of cortical tone. It has also
been revealed that long-term exposure of MM radiation with l= 7.1 mm
produces a stabilizing effect on day-to-day variation of human cortical
biopotentials (most easily observable with alpha power and the inter-
and intrahemispheric mean coherence of delta, theta and alpha ranges)
[9, 10, 69].
It has been described peculiar EEG-effect of ELF EMF ¾ increasing
beta-activity in frontal and central areas and increasing alpha-power
mainly at occipital areas [64, 70].
The possibility of correcting human conditions by electromagnetic
exposure was investigated. EHF exposure brought the functional state of
the nervous and cardiac systems to equlibrium in persons with high and
middle plasticity of neurodynamic processes (determined by EEG
parameters), but, in persons with low neurodynamic plasticity, EHF
exposure was ineffective (functional reserves of the organism are low
for a long time) .
Investigations of EMF perception have demonstrated that people can
perceive EMF of low intensity. Human EMF-sensitivity, besides
individual features, is determined by the frequency and signal form of
the EM-signal and localization of its application. The modality of the
resulting sensation testifies to the participation of a cutaneous
analyzer in EMF reception. Latency of the reaction was 20-60 s. Sensory
asymmetry of perception was revealed: subjects distinguish between the
field and false trials much better with their non-leading hand
(right-handed ¾ by the left hand, left-handed ¾ by the right one). The
experimental data has shown the presence of a correlation between human
sensitivity to EMF and pain thresholds - the lower these thresholds,
the higher the sensitivity. There are some "critical" values of these
thresholds when subjects manifest no sensitivity to EMF of any
frequency ranges [9, 10, 72-74].
The correlation between human electromagnetic sensitivity and EEG
properties was investigated . Highly sensitive volunteers had an
optimally pronounced alpha rhythm with prominent topographic
differences. The low-sensitive volunteers have higher or lower level of
alpha rhythm without topographical differences.
The purpose of this work was to study EEG reactions to cellular phone
EMF exposure (intensity 0,06 mW/cm2, frequency 902,4 MHz).
24 healthy male volunteers aged from 20 to 30 years participated in the
experiments. Two experiments (mobile telephone exposure and placebo,
the order of the experiments was randomized) were performed with each
subject at the same time of day with a constant interval of 1 week
between them. Duration of the experiment was 60 min.: 15 min.
¾background, 15 min. ¾ EMF exposure or placebo, 15 min ¾ afterexposure
I and 15 min afterexposure II (Fig. 1). To exclude sleepness of the
subject, the closed-eyes periods of EEG recording alternate with
opened-eyes periods every 5 minutes. EEG was recorded in 16 electrodes
according to the international 10-20 system (Fz, F3, C3, P3, Pz, P4,
C4, F4, F7, T3, T5, O1, O2, T6, T4, F8) against Cz as the reference.
The EMF was directed to the back of head by a special antenna. The
subject and the EEG machine were shielded from the devices used. EEG
data were stored on magneto-optical disks for further processing.
To estimate EEG changes, we use the global dimensional complexity (a
measure derived from nonlinear dynamics) of EEG. Calculation of
dimensional complexity was performed for each 8-s artifact-free EEG
segment . Then these values were averaged across 10 segments.
Statistical comparisons were performed by analysis of variance (ANOVA).
The dynamics of mean multichannel (global) correlation dimension values
D2 in experiment time is shown in Fig. 2.
FIGURE 1. Protocol of experiments.
FIGURE 2. Multichannel correlation dimension values of baseline (1-12
epochs), exposure (13-24 epochs), afterexposure I (25-36 epochs),
afterexposure II (37-48 epochs) for the group.
The dynamics of D2 under cellular phone EMF is as follows. After
starting EMF, parameter D2 increases immediately; in 2 min, D2
decreases but stays higher than Placebo for 6-7 min; for the rest time
of EMF exposure, the difference between Placebo and EMF experiments
disappears. During the afterexposure period (30-45th min), D2 in EMF
experiments again exceeds that in Placebo.
The difference between D2 under cellular phone and Placebo is
significant in the periods of exposure, afterexposure 1 and
afterexposure 2 (Tabl. 1).
Table 1. The mean values of correlation dimension D2 in baseline (1),
exposure (2), afterexposure I (3) and afterexposure II (4) for the
after- exposure I
after- exposure II
The mean values of each period (baseline, exposure, afterexposure 1 and
afterexposure 2) are demonstrated on Fig. 3.
FIGURE 3. The mean values of correlation dimension D2 in baseline (1),
exposure (2), afterexposure I (3) and afterexposure II (4) for the
In Fig. 2, one can see sawtooth (5 min) oscillations of D2. These
oscillations are related to distinct neocortex functional states ¾
"open eyes" and "closed eyes" (Fig. 1). Separate EEG analysis of these
two functional states has revealed that the mean values of D2 (both of
EMF experiments and Placebo) are greater in "open eyes" (OE) state in
comparison with the "close eyes" (CE) state ¾ Fig. 4, Tabl. 2.
Table 2. The mean values of correlation dimension D2 in baseline (1),
exposure (2), afterexposure I (3) and afterexposure II (4) with open
and closed eyes
FIGURE 4. The mean values of correlation dimension D2 in baseline (1),
exposure (2), afterexposure I (3) and afterexposure II (4); A - closed
eyes, B - open eyes.
In "closed eyes" state, the cellular phone EMF effect (D2 increase in
compare with Placebo) is more pronounced (the difference is significant
for exposure and afterexposure). The "open eyes" increase of D2 is
significant only during the afterexposure 2 period.
So the data obtained indicate that bioelectric human brain activity (as
can be observed with D2) is modified under EMF cellular phone exposure.
There is wide experience using spectral analysis of the bioelectric
activity of the brain cortex to evaluate its functional state [76-78].
The dynamics of two main measures is most commonly investigated:
spectral power of each EEG range (delta, theta, alpha and beta) and
coherence for each pair of EEG. For multichannel EEG records, these
measures give the possibility to estimate changes of spatio-temporal
patterns of brain cortex biopotentials due to external factors - to
determine the power of separate EEG frequency components of different
cortex areas and coherence (i.e. statistical dependence) of the
electrical processes of both hemispheres - inter- and intra-hemisphere
connections. Employing these methods of EEG analysis, the researcher
obtains knowledge of the functioning of brain cortex areas that allows
some conclusions about neurophysiological mechanisms of CNS response to
affective factors and an evaluation of changes arising in the cortex
However, to state definitely that the brain functional state has been
changed, the researcher needs to account for a variety of parameters
and interdepencies among them, and identification of the functional
state is highly subjective. In addition, sometimes this method is not
sufficiently responsive, especially for evaluating the bioeffects of
weak nonspecific stimuli. This method implies the linear stochastic
nature of EEG. Chaotic dynamics propose an alternative model of EEG as
nonlinear deterministic processes [79-82].
It was shown that the use of nonlinear techniques of EEG analysis
presents a way to determine some pathological states and some
functional states of healthy subjects .
A number of authors suggest that chaotic EEG components are related to
CNS information processes and reflect the spatial-temporal organization
of underlying brain processes. These methods extract information that
cannot be obtained from spectral analysis [84-87].
Processing of EEG records by methods of nonlinear dynamics with the
calculation of the multichannel (global) correlation dimension allows
the evaluation of changes of the functional state of the brain at
whole. The measure obtained as a result of such processing is highly
sensitive to the effects of low-intensity EMF produced by cellular
phone. The significant increase of global correlation dimension
obtained during and after exposition (in comparison with Placebo)
suggests a change of functional state of the human brain. This can be a
result of brain cortex activation that begins with EMF onset and
continues after termination of EMF exposure. On the other hand, some
brain activation can be viewed as a positive factor that helps
intellectual performance. However, taking into consideration the fact
that this activation was produced by short-term (15-min) exposure to
cellular phone EMF, the data obtained cannot be treated unambiguously.
There is a neurophysiological phenomenon known to
occur when repeated application of the weak stimulus produce stable
focus of excitation that has a number of properties [88-90], for
stability for some period of time;
capacity to produce extinction of nearby areas of the
capacity to use other stimuli to enhance its own activity.
On long standing, such a dominant focus violates balanced relations
between different regions of the brain and disturbs normal brain
functioning, producing different CNS diseases. So, if the cellular
phone is used repeatedly in the course of the day, it can be such a
weak stimulus that will produce dominant focus. To draw inferences
about the usefulness or damage of cellular phone EMF for humans, it is
necessary to conduct more extensive research on the responses of CNS
and other systems, but it is apparent that much attention must be given
to this problem.
1. Presman, A.S., Electromagnetic signalization in living nature.
Moscow, Sovetskoe radio, 1974 (in Russian).
2. Plekhanov, G.F., Basic laws of electromagnetobiolody. Tomsk. T.G.U.
(The Tomsk State University), 1990, 187 p. (in Russian).
3. Tenforde, T,. Interaction of ELF magnetic fields with living matter.
Handbook of biological effects of electromagnetic fields. /Ed.C.Polk, E
Postow.Boca Raton; CRS press Inc., 1986; pp.197-225.
4. Adey, W.R., Frequency and power window in tissue interactions with
weak electromagnetic fields, Proc. IEEE. 1980, 68 (1): 119.
5. Temuryants, N.A., Nervous and humoral mechanisms of adaptation to
action of non-ionizing radiation, Moscow: D.Sc. thesis, 1989 (in
6. Sidyakin, V.G., Effect of global ecological factors on nervous
system, Kiev: Naukova Dumka, 1986 (in Russian).
7. Temuryants, N.A., Vladimirsky, B.M., Tishkin, O.G., Extremely low
frequency signals in biological world, Kiev: Naukova Dumka, 1992, 188
p. (in Russian).
8. Lebedeva, N.N., Reaction of human CNS on electromagnetic fields with
various biotropic parameters, Moscow: D.Sc. thesis, 1992 (in Russian).
9. Lebedeva, N.N., Sensory and subsensory reactions of a healthy man on
peripheral effects of low intensity MM-waves, Zh. Millimetrovye volny v
biologii i meditsine (J. Millimeter Waves in Medicine and Biology),
1993, no. 2, pp. 5-23 (in Russian).
10. Kolomytkin, O.V., et al., High sensetivity of brain receptor system
to low intensity microwaves. 2-nd International Scientific Meeting
"Microwaves in medicine 1993", Rome, 1993.
11. Pakhomov, A.G., Prol, H.K., Mathur, S.P., et al., Frequency and
intensity dependence of the Millimeter-wawe radiation effect on
isolated nerve function. BEMS. Abstract Book. Eighteenth Annual
Meeting, Canada, June 9-14, 1996.
12. Kholodov, Yu.A., Lebedeva, N.N., Nervous systems reactions to
electromagnetic fields, Moscow: Nauka, 1992; 135 p. (in Russian).
13. Demetskiy, A.M., Zukov, B.N., and Tsetsocko, A.V., Electromagnetic
fields in medicine. Samara, 1991; 157 p. (in Russian).
14. Devyatkov, N.D., Golant, M.B., and Betskii, O.V., Millimeter waves
and their role in life-giving processes, Moscow: Radio i Svyaz, 1991
15. Golovacheva, T.V., Chronobiological Aspects of EHF-therapy of the
Ischemic Heart Disease, XI Ross.simp. (with participation of foreign
scientists), "Millimeter Waves in Medicine and Biology", Moscow, 1997
16. Gordon, D.S., Merkulova, L.M., et al., Hystochemistry of thymus
monoamins in local EHF action, Magnitologiya (Magnetology), 1994, no. 1
17. Gordon, B.M., Merkulova, L.M., et al., Status of bioamins in rat
thymus cells after acute pain stress and MM-therapy, X Russian
Symposium (with participation of foreign scientists) "Millimeter Waves
in Medicine and Biology", Moscow, 1995 (in Russian).
18. Kholodov, Yu.A., Nociception system and living being reactions to
EMF. Magnitologya (Magnetology), 1991, no. 2 (in Russian).
19. Jacobson, J.I., Electromagnetism in medicine, Indian.J.Med.Sci.,
1992; no. 6(11), pp. 321-327.
20. Lambroso, J., Champs electromagnetiques et sante. Un conte de fies?
Energ.sante/ serv. atud/ med., 1994, pp. 5-115.
21. Lebedeva, N.N. and Sulimova, O.P., MM-waves modifying effect on
human central nervous system functional state under stress, Zh.
Millimetrovye volny v biologii i meditsine (J. Millimeter waves in
biology and medicine), 1994, no. 3, pp. 16-21 (in Russian).
22. Sulimova, O.P., Low intensity EHF EMF peripheral exposure on heart
rate dynamics. Problemy electromagnitnoy bezopasnosti cheloveka, (The
problem of human electromagnetic safety), The 1-st Russian conference
with international participation. 28-29 November 1996, Moscow (in
23. Ahlbom, A., A review of the epidemiology literature on magnetic
fields and cancer, Scand.J.Work Environ.Health, 1988, vol. 14, pp.
24. Calle, E. and Savitz, D.A., Leukemia in occupational groups with
exposure to electrical and magnetic fields, New Engl.J.Med, 1985, vol.
23, pp. 1476-1477.
25. Juutilainen, J., Bjork, E., and Saali, K., Epilepsy and
electromagnetic fields: effects of stimulated atmospherics and 100 Hz.
Int.J., Biometeorology, 1988, vol. 32, pp. 17-22.
26. Feychting, M. and Ahlbohm, A., Magnetic fields and cancer in
children residing near Swedish high-voltage power lines,
Am.J.Epidimiol, 1993, vol. 138, pp. 467-481.
27. London, S.J., Thomas, D.S., Bowman, J.D., et al., Exposure to
residential electric and magnetic fields and risk of childhood
leukemia, Am.J.Epidemiol, 1991, vol. 134, pp. 923-937.
28. Michaelis, J., Schuz, J., Meinert, R., et al., A population-based
case-control study on electromagnetic fields and childhood leukemia,
BEMS. Abstract Book. Eiteenth Annual Meeting, Canada, June 9-14, 1996.
29. Polk, C., Biological effects of low-level low-frequency electric
and magnetic fields, IEEE Transact Edue, 1991, vol. 34, pp. 243-249.
30. Poole, Ch., Kavet, R., Funch, D.P., et al., Depressive symptoms and
headaches in proximity of residence to an alternating-current
transmission line right-of-way, Am.J. of Epidemiology, 1991, vol. 137,
31. Cobb, B.L., Mason, P.A., Miller, S.A., et al., A teratologic study
of ultrawideband electromagnetic field exposure, BEMS. Abstract Book.
Eighteenth Annual Meeting, Canada, June 9-14, 1996.
32. Davis, C.C., Katona, G.A., Taylor, L.S., et al., Dielectric
measurement of tissues in the mammalian head at cellular telephone
frequencies, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada,
June 9-14, 1996.
33. Douglas, M.G., Okoniewski, M., and Stuchly, S.S., Antennas for
cellular telephones with reduced power deposition in the body of the
user, BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June
34. Bao, J.-Z., Lu, S.-T., Hurt, W.D., et al., Dielectric measurements
of brain tissues in the frequency range between 45 MHz and 26.5 GHz,
BEMS. Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
35. Burkhardt, M., Spinelli, Y., and Kuster, N., Exposure setup totest
the effects on the CNS of wireless communications systems, BEMS.
Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
36. Kholodov, Yu.A., Nervous systems reactions to electromagnetic
fields. Moscow: Nauka, 1975, 207 p. (in Russian).
37. Kholodov, Yu.A., The brain in electromagnetic fields, Moscow:
Nauka, 1982; 123 p. (in Russian).
38. Kholodov, Yu.A., MM-radiation in neurobiology, X Ross.simp. (with
participation of foreign scientists) "Millimeter Waves in Medicine and
Biology", Moscow, 1995, pp. 115-117 (in Russian).
39. Graham, C., Cook, M.R., Cohen, H.D., et al., Dose responce study of
human exposure to 60 Hz electric and magnetic fields,
Bioelectromagnetics, 1994, vol. 15, pp. 447-463.
40. Kaznacheev, V.P. and Michailova, L.P., Extremely weak radiations in
intercellular interactions, Novosibirsk: Nauka, 1981, 144 p. (in
41. Bravarenko, N.I., Balaban, P.M., Kuznetsov, A.N., et al., Glia role
in reactions of snail neurons to constant magnetic field, Problemy
electromag. neurobiol (The electromagnetic neurobiology problems),
Moscow: Nauka, 1988; pp. 64-73 (in Russian).
42. Chizhenkova, R.A., Low intensity EHF radiation and pulse trains of
cortex neurons, Problemy electromag. Neurobiol, (The electromagnetic
neurobiology problems), Moscow: Nauka, 1988 (in Russian).
43. Blackman, C.F., Benane, S.G., and Elliot, D.J., Importance of
alignment between local DC magnetic and an oscillating magnetic field
in responses of brain tissue in vitro and in vivo, Bioelectromagnetics,
1990; vol. 11, pp. 159-167.
44. Sheppard, A.R., Effects of 60 Hz magnetic field on a spontaneously
active neuronal system, Proceedings of the 9th Annual conference of the
IEEE engineering in medicine and biology society, Boston, 1987, pp.
45. Khitrova-Orlova, T.V., Pavlenko, V.B., Ilyicheva, T.V., et al., EHF
effects on background and evoked activity of cortex neurons of cat
brain, Magnitobiologiya i magnitotherapiya, (Magnetobiology and
magnetotherapy), 1991 (in Russian).
46. Burkhardt, M., Spinelli, Y., and Kuster, N., Exposure setup totest
the effects on the CNS of wireless communications systems, BEMS.
Abstract Book. Eighteenth Annual Meeting, Canada, June 9-14, 1996.
47. Pavlenko, V.B., Khitrova-Orlova, T.V., Kopilov, A.N., et al.,
Alternating EHF fields effects on neuron activity of cat brain,
Magnitobiologiya i magnitotherapiya (Magnitobiology and
magnetotherapy), 1991 (in Russian).
48. Alekseev, S.I., Kochetkova, N.V., Bolshakova,M.A., et al.,
Influence of EMF EHF on neuron membrans, IX Ross.simp. (with
participation of foreign scientists), "Millimeter Waves in Medicine and
Biology", Moscow, 1991 (in Russian).
49. Semm, P., Marhold, S., Dombek, K.-P., et al., Neuronal responses to
low-intencity electromagnetic fields at 900 MHz, BEMS. Abstract Book.
Eighteenth Annual Meeting, Canada, June 9-14, 1996.
50. Sigalevi, L.A., Balaban, P.M, Dementev, V.A., et al., CMF influence
on identific neurons and interglianeuronal interactions in isolated
neural system of grapes snail. //Inf. of USSR Academy of Science, 1983,
no. 4 (in Russian).
51. Artyukhina, N.I., The reactions of structure elements of the rat
brain on magnetic fields exposure. Problemy electromag. neurobiol. (The
electromagnetic neurobiology problems), Moscow: Nauka, 1988, pp. 42-47
52. Hansson, H.A., Effects on the nervous system by exposure to
electromagnetic fields: experimental and clinical studies, Prog. Clin.
Biol. Res., 1988, vol. 257, pp. 119-134.
53. Hansson, H.A., Effects on nervous tissue of exposure to
electromagnetic fields. In Adey W.R., Leurence A.F.(eds): "Nonlinear
electrodynamics in biological systems", New York: Plenum Press, 1994,
54. Khromova, S.V., Modification of rat behavior by millimeter
radiation, Thesis. Ph. D., Moscow, 1990 (in Russian).
55. Sienkiewicz, Z.J., Haylock, R.G., and Saunders, R.D., Prior
exposure to A 0.75 mT, 50 Hz Magnetic fields impairs spatial learning
in adult male mice, BEMS. Abstract Book. Eighteenth Annual Meeting,
Canada, June 9-14, 1996.
56. Michailovsky, V.N., Voychishin, K.S., and Grabar', L.I., About
human perception of MF ELF oscillation and protection means, Biological
system reactions on weak MF. Moscow: Nauka, 1991 (in Russian).
57. Lukyanova, S.N., Rinskov, V.V., and Makarov, V.P., Analysis of CNS
reactions to low intensity short-term microwave radiation, Problemy
electromagnitnoy bezopasnosti cheloveka, The 1-st Russian conference
with international participation, 28-29 november, Moscow, 1996 (in
58. Ziriax, J.M., MacCullum, M., and Hurt, W., Detection of 94,5 GHz
radio frequency fields by Rhesus Monkeys, BEMS. Abstract Book.
Eighteenth Annual Meeting, Canada, June 9-14, 1996.
59. Norekyan, T.P. and Matukhina, I.A., Alternating magnetic field and
conditional reflex. Problemy electromag. neurobiol (The electromagnetic
neurobiology problems), Moscow: Nauka, 1988; pp. 5-11 (in Russian).
60. Sidyakin, V.G. and Yanova, N.P., Modifying effect of extremely low
frequency alternating magnetic field on animal conditioned reflex
activity, Problemy electromag. Neurobiol. (The electromagnetic
neurobiology problems), Moscow: Nauke, 1988 (in Russian).
61. Kholodov, Yu.A., Influence of EMF and MF on CNS, Moscow: Nauka,
1966 (in Russian).
62. Thuroczy, G., Kubinyi, G., Nagy, N., and Szabo, L.D., Measurements
of visual evoked potentials (VEP) and brain electrical activity (EEG)
on freely moving rats exposed to 50 Hz, 100 *Ò and 500 *T magnetic
fields, BEMS, Abstract Book. Seventeenth Annual Meeting, USA, June
63. Chizhenkova, R.A. and Safroshkina, A.A., Cortex neuronal activity
during EEG reaction to microwave irradiation, BEMS. Abstract Book.
Seventeenth Annual Meeting, USA, June 18-22, 1995.
64. Thuroczy, G., Kubinyi, G., Nagy, N., and Szabo,. L.D., Acute
changes in brain electrical activity (EEG) after GSM modulated
microwave exposure on rats, BEMS. Abstract Book. Sixteennth Annual
Meeting, Denmark, June 12-17, 1994.
65. Bell, G.B., Marino, A.A., and Chesson, A.L., Alterations in brain
electrical activity caused by magnetic fields: Detecting the detection
process, Electroencephalogr. Clin. Neurophysiol., 1992; vol. 83, pp.
66. Bell, G.B., Marino, A.A., Chesson, A.L., and Struve F.A., Human
sensitivity to weak magnetic fields, Lancet. 1991, vol. 338, pp.
67. Selitskiy, G.V., Karlov, V.A., and Sorokina, N.D., Mechanisms of
human magnetic field perception, Fisiologiya cheloveka (Human
physiology), 1996; vol. 22(7), pp. 66-72 (in Russian).
68. Levillain, D. and Picat, J., Interet de l'analyse spectrale dans
l'evaluation des effects sur le rythme alpha des champs magnepulses,
Ann. Med.Psychol., 1985, vol. 143, pp. 235-254.
69. Lyskov, E., ELF magnetic fields alter the sentral nervous system
activity. Neurophusiological evidens, Abstracts till 3:e Nordiska
Arbetsmotet. Biologiska effekter av lagfrkventa elektromagnetiska falt,
Umeo, March, 13-14. 1994, p.16.
70. Sulimova, O.P., Electro and psychophysiological human reactions to
EHF electromagnetic fields, Ph.D.thesis, Simferopol, 1992 (in Russian).
71. Lyskov, E., The change of human CNS functional state in complex
action of constant and ultralowfrequency magnetic field of low power
density, Moscow: D. Sc. Thesis, 1996 (in Russian).
72. Vassilevsky, N.N. and Suvorov, N.B., Electromagnetic correction of
human state, BEMS, Abstract Book. Seventeenth Annual Meeting, USA, June
73. Lebedeva, N.N., Vekhov, A.V., and Bazhenova, S.I., On human
electromagnetic perception. Problemy electromag. neurobiol (The
electromagnetic neurobiology problems), Moscow: Nauka, 1988, pp.85-93
74. Lebedeva, N.N., Neurophysiological mechanisms of biological effects
on peripherical action of non-ionizing electromagnetic fields, X
Russian Symposium (with participation of foreign scientists)
"Millimeter Waves in Medicine and Biology", Moscow. 1995 (in Russian).
75. Kotrovskaya, T.I., Human electromagnetic perception and its
relation with individual properties, Moscow: Ph.D.thesis, 1996 (in
76. Stam, K.J., Tavy, D.L.J., Jettes, B., et al., Non-linear dynamical
analysis of multichannel EEG: clinical applications in Dementia and
Parkinson's disease, Brain Topography, 1994, vol. 7(2), pp. 141-150.
77. Boldyreva, G.N. and Zhavoronkova, L.A., EEG inter-hemispheric
relationship for estimation of Human brain functional state,
Jh.Vyssh.Nerv.Deyat. im I.P.Pavlova (Journal of the higher nervous
activity named by I.P.Pavlov), 1989, vol. 39-2 (in Russian).
78. Rusinov, V.S., Grindel, O.M., Boldyreva, G.N., el al., Human brain
biopotentials, Moscow: Meditsina (Medicine), 1987 (in Russian).
79. Sviderskaya, N.E., Synchronous electric activity of brain and
psychical processes, Moscow: Nauka, 1987, pp. 61-81 (in Russian).
80. Grassberger, P. and Procaccia, I., Measuring the strangeness of
strange attractors, Physica D., 1983, vol. 9(1-2).
81. Aranson, I.S., Reyman, À.N., and Shechov, V.G., The methods of
measuring of correlation dimension in the experiment, Nelineynyye
volny, Dinamika i evolutsiya (Nonlinear waves. Dynamics and evolutia.),
Moscow: Nauka, 1989 (in Russian).
82. Osovets, S.M., Ginsburg, D.A., Gurfinkel, V.S., et al., Electric
activity of brain, Uspekhi fis.nauk (The evidences of fisical science),
1983, vol. 141(1) (in Russian)
83. Rapp, P.E., Zimmerman, I.D., Albano, A.M., et al., Dynamics of
spontaneous neural activity in the simian motor cortex: the dimension
of chaotic neurons, Phys. Lett. A., 1985, vol. 110(6).
84. Belskii, U.A., Vedenin, A.B., and Dmitriev, A.S., Diagnostics of
brain pathology by the method of non-linear dynamics, Radiotekhnika i
Electronika (Radio engeneering and Electronics), 1993, vol. 38(9) (in
85. Skarda, Ch.A. and Freeman, W.J., How brains make chaos in order to
make sense of the world Behav, Brain. Sci., 1987; 10.
86. Efremova, T.M., Kulikov, M.A., and Rezvova, I.R., The participation
of non-linear dynamical processes in forming of the high frequency
rabbit EEG component, Zh. Vyssh. Nerv. Deyat. im I.P.Pavlova (Journal
of the higher nervous activity named by I.P.Pavlov), 1991; 41(5) (in
87. Mann, K. and Roschke, J., REM-suppression induced by digital mobile
radio telephone, Wien-Med-Wochenschr.,1996, vol. 146, pp. 13-14.
88. Ulbikas, Yu.K., Davydov, V.I., and Levedeva, N.N., Application of
the methods of chaotic dynamics to investigate EHF exposure effects on
human bioelectric brain activity, Millimetrovye volni v Meditsine
(Millimeter Waves in Medicine), vol. 2, Moscow, 1991 (in Russian).
89. Dominanta: electrophysiological study, Moscow: Medicine, 1969 (in
90. Pavligina, R.A., Dominanta and its role in animal behaviour,
Uspekhi physiol.nauk (The evidence of fisiological science), 1982, vol.
13 (in Russian).
91. Pavligina, R.A., Lebedeva, N.N., Davidov, V.I., Study of human
locomotory dominanta, Zh. Vyssh. Nerv. Deyat. im I.P.Pavlova (Journal
of the higher nervous activity named by I.P.Pavlov), 1998, no. 6 (in
Investigation of Brain Potentials in Sleeping Humans Exposed to the
Electromagnetic Field of Mobile Phones
Doctor of Biological Sciences, Principal Scientist at the Institute of
Higher Nerve Activity and Neurophysiology, Russian Academy of Sciences.
E-mail: N.Leb@relcom.ru; 2Candidate of Medical Science, Senior
Researcher at the Institute of Higher Nerve Activity and
Neurophysiology, Russian Academy of Sciences.; 3Researcher at the
Institute of Higher Nerve Activity and Neurophysiology, Russian Academy
of Sciences; 4Deputy Director of the "Extremely High Frequency" Medical
and Technical Association; 5Biological Department Head at the Deutsche
Telekom AG (Germany).
ABSTRACT: An investigation was made of 8-hour EEG tracings of sleeping
humans exposed to the electromagnetic field of a GSM-standard mobile
phone. To analyze the EEG-patterns, manual scoring, nonlinear dynamics,
and spectral analysis were employed. It was found that, when human
beings were exposed to the electromagnetic field of a cellular phone,
their cerebral cortex biopotentials revealed an increase in the a-range
power density as compared to the placebo experiment. It was also found
that the dimension of EEG correlation dynamics and the relation of
sleep stages changed under the influence of the electromagnetic field
of a mobile phone.
Normal sleep is made up of cyclic variations in the functional state of
the brain. The most salient and invariable feature of sleep consists in
that the brain shows a decrease in the cerebral cortex activity on the
scale "sleep-wakefulness". The functional state of the brain is usually
studied by means of an electroencephalogram (EEG). An analysis of
electroencephalograms made earlier demonstrated that sleep is an
inhomogeneous process. It has a complex structure and a certain
sequence of alternating patterns. There are many classifications of
sleep due to numerous approaches to the description of EEG patterns.
One of the first classifications made it possible to analyze EEG
patterns in sleeping subjects . However, the application of this
classification can only show how deep is the subject's sleep. In other
words, this classification is capable of revealing only two stages of
sleep, such as drowsiness and deep (slow-wave) sleep. The discovery of
the rapid-eye-movement (REM) stage
of sleep allowed the development of a new classification . According
to this classification, sleep was divided into orthodox sleep, which
does not involve rapid eye movements, and into paradoxical, or REM,
The most complete classification of polysomnographic sleep records is
given in . It uses electroencephalograms, electromyograms,
electrooculograms, and some other techniques. This approach made it
possible to recognize five alternating stages of sleep with certain EEG
correlates for every stage.
The first stage is marked by a relatively low amplitude and mixed
frequencies with a pronounced activity at 2 to 7 Hz. The duration of
this stage is relatively short and it ranges from 1 to 7 min. This
stage occurs mostly when a person starts to fall asleep or between
other stages of sleep. The second stage is recognized by a relatively
low amplitude, "sleep spindles", and K-complexes arising either due to
responses to unexpected stimuli or in the absence of any differentiable
stimuli. This stage constitutes approximately a half of the total
sleeping time. The third stage is characterized by slow high-amplitude
waves, which account for 20 to 50% of the whole analyzed period. The
fourth stage shows high-amplitude waves with a frequency of 2 Hz. These
waves make up more than 50% of the whole analyzed period. The fifth
stage (or REM-stage) is distinguished by a relatively low amplitude and
by mixed EEG frequencies periodically interrupted by episodes of REM
Presently, researchers make use of all the enumerated classifications
of sleep stages depending on the solved problem.
In healthy adults, night sleep is made up of 4 to 6 sleep cycles that
include all five stages. Each cycle begins with a period of slow-wave
sleep. On the average, each cycle lasts for 90 min. However, the first
cycle lasts longer than the final ones.
However, night sleep of healthy people can be affected by many kinds of
things in the environment. For example, sleep is dependent on
personality and it was found to be different in morning types and
evening types [4-7]. Apart from that, sleep depends on the time when a
person goes to bed and on the time during which he or she stayed awake
before going to bed [8, 9]. In addition, sleep depends on the
surroundings , age , subject's geomagnetic orientation [12,
13], and other conditions.
In view of a constantly aggravating electromagnetic
pollution of the environment, it seems essential to study the effect of
various electromagnetic devices and equipment on the activity of the
central nervous system of human beings , for example, during their
Our investigation was conducted on 20 volunteers (20 men aged from 20
to 28). We made two runs of experiments, in which the volunteers were
exposed to simulated (sham) and actual electromagnetic fields of a
mobile phone in random order. Two-channel EEG tracings were recorded
during an 8-hour laboratory sleep. The EEG tracings were recorded in
the CZ and PZ leads, with the reference electrode being placed in the
As soon as electroencephalograms were recorded, sleep stages were
scored manually and then their duration and alternation were analyzed.
After that, nonlinear dynamics methods were employed to calculate
correlation dimension and then FFT-based spectral analysis was used. We
left out of account periods affected by muscular motion or winking
artifacts. For normal EEG periods, we calculated the absolute spectral
power in the d-, q-, a-, and b-ranges and the correlation dimension D2
for each lead. The secondary statistical treatment was carried out with
the aid of variance analysis (ANOVA).
The spectral analysis of EEG patterns obtained from sleeping humans
demonstrated that reliable variations in the spectral power indices
were observed only in the a-range for the PZ lead (Figure 1, Table 1).
An increased spectral power in the a-range can be explained by the fact
that this range is most reactive to the influence of electromagnetic
fields [16, 17]. A similar tendency of changes was also observed in the
d- and q-ranges. However, the b-range did not exhibit significant
variations or tendencies. It was also found that volunteers exposed to
the actual electromagnetic field of a mobile phone showed a significant
decrease (p < 0.05) in the two-channel correlation dimension D2
during an 8-hour sleep as compared to the placebo experiment with a
simulated electromagnetic field (Figure 2).
The mean values of correlation dimension indices D2 for EEG tracings
recorded during an 8-hour sleep from the CZ and PZ leads are presented
in Figure 3 and in Table 2. Although the decrease in D2 was significant
(p < 0.05) for both leads, it was more pronounced for the CZ lead.
Table 1. Mean values of the spectral power indices in the a-range for
simulated and actual electromagnetic fields of a mobile phone.
FIGURE 1. Mean values of the EEG spectral power density in the a-range
obtained from the CZ and PZ leads during an 8-hour sleep for simulated
and actual electromagnetic fields of a mobile phone (pPz < 0.05).
FIGURE 2. Mean values of the two-channel correlation dimension D2
during an 8-hour sleep.
FIGURE 3. Mean values of the correlation dimension indices D2 obtained
from the CZ and PZ leads during an 8-hour sleep.
Table 2. Mean values of the correlation dimension indices D2 for
simulated and actual electromagnetic fields of a mobile phone.
The dynamics of the correlation dimension indices D2 during an 8-hour
sleep for simulated and actual electromagnetic fields of a mobile phone
is shown in Figure 4. Similar patterns were observed for every lead.
Manual scoring demonstrated that, when volunteers were
exposed to simulated and actual electromagnetic fields of a mobile
phone, they exhibited insignificant differences in sleep stages.
However, one can see that the percentage of slow-wave sleep during the
whole 8-hour sleep revealed a tendency to decrease in volunteers
exposed to the actual electromagnetic field (Figure 5, Table 3).
Table 3. Percentage of the slow-wave sleep for simulated and actual
electromagnetic fields of a mobile phone.
FIGURE 4. Dynamics of the mean correlation dimension indices D2
obtained from the CZ and PZ leads during an 8-hour sleep for simulated
and actual electromagnetic fields of a mobile phone (p < 0.05).
It is known that the structure of night sleep includes deep
synchronized slow-wave sleep (SSWS), which takes a large part of the
first half of a sleep cycle. SSWS percentage then decreases and EEG
tracings reveal desynchronization processes. These processes are
typical of nonsynchronized slow-wave sleep (NSSWS), which includes the
first, the second, and the fifth (or REM) stages .
It is also known  that EEG correlation dimension indices D2 of SSWS
are significantly lower than those of NSSWS. This is associated with
the fact that processes occurring in the brain at the third and fourth
stages take a simplified course. During the second half of night sleep,
NSSWS becomes dominating and the cerebral cortex's bioelectrical
processes get more complicated. This gives rise to increased values of
D2. It is this dynamics of D2 that was seen during sleep in human
beings exposed to a simulated electromagnetic field (Figure 4).
FIGURE 5. Percentage of the slow-wave sleep (the third and the fourth
stages) with respect to the whole 8-hour sleep structure for simulated
and actual electromagnetic fields of a mobile phone.
However, when volunteers were exposed to the actual electromagnetic
field of a mobile phone, they exhibited a different EEG pattern.
Although during the first half of their sleep the dynamics of D2 was
virtually identical to that of the control group, it did not show the
expected increase in D2 during the second half of their sleep.
Moreover, it remained invariable to the end of our experiment. Thus,
the dynamics of D2 provided evidence for a changed sleep structure,
which was related to the NSSWS depression. Similar results were
reported in , in which healthy people were exposed to the
electromagnetic field of a cellular phone and they also revealed a
suppressed REM-stage (which is one of NSSWS stages). Apart from that,
one can see from Figure 5 that the slow-wave sleep cycle (the third and
fourth stages) revealed a tendency to decrease under the influence of
the actual electromagnetic field, although this effect was not
Thus, taking into account the results obtained in  and results
presented in Figures 4 and 5, one can postulate that a prolonged
exposure to the electromagnetic field of a mobile phone brings about a
pronounced sleep structure transformation. In this case, sleep is
largely made up of the first and second sleep stages, which involve no
dreaming. Bearing in mind that the first stage is rather short and that
it mainly accompanies the REM-stage, one can conclude that, when human
beings were exposed to the actual electromagnetic field of a mobile
phone, a great part of their sleep consisted of the second sleep stage,
which is typical of aged people .
It is known that the fundamental biological role of sleep in live
organisms is directed to providing adaptive regulation. On the one
hand, sleep reduces functional loads on various bodily systems, such as
the nervous system, the cardiovascular system, and the muscular system,
with this reduction taking place during the third and the fourth sleep
stages. On the other hand, the adaptive role of dreaming, which occurs
during the REM-stage, is also of great importance because dreaming
helps people to process stored information and to reduce psychological
Hence, the electromagnetic field of a mobile phone affects the sleep
structure and reduces slow-wave and REM-stage sleep percentage, which
is able to decrease the adaptive reactions of human beings and to
impair their state of health as a result of this.
1. Loomis, A. L., Harvey, E. N., and Hobart, G. A., Cerebral states
during sleep as studied by human brain potentials. J. Exper. Phychol.,
2. Dement, W. and Kleitman, N., Cyclic variations in EEG during sleep
and their relation to eye movements, body motility, and dreaming.
Electroencephal. Clin. Neurophysiol., No. 9, 1957.
3. Rechtshaffen, A. and Kales, A., A manual of Standardized Terminology
Techniques and Scoring System for Sleep Stages of Human Subjects.
National Institutes of Health. Publication No. 204, Washington, 1968.
4. Akerstedt, T., Kecklund, G., and Knutsson, A., Manifest sleepiness
and spectral content of the EEG during shift work. Sleep, Vol. 14, No.
3, pp. 221-225, 1991.
5. Lancel, M. and Kerkhof, G. A., Sleep structure and EEG power density
in morning types and evening types during a simulated day and night
shift. Physiol. Behav., Vol. 49, No. 6, 1991.
6. Kerkhof, G. A., Differences between morning types and evening types
in the dynamics of EEG slow-wave activity during night sleep.
Electroencephal. Clin. Neurophysiol. Vol. 78, No. 3, 1991.
7. Armitage, R. and Roffwarg, H. P., Distribution of period-analyzed
delta activity during sleep. Sleep, Vol. 15, No. 6, 1992.
8. Aeschbach, D., Dijk, D. J., and Borbely, A. A., Dynamics of EEG
spindle frequency activity during extended sleep in humans:
relationship to slow-wave activity and time of day. Brain-Res., Vol.
9. Gillberg M., and Akerstedt, T., The dynamics of the first sleep
cycle. Sleep, Vol. 14, 1991.
10. McCall, W. V., Erwin, C. W., Edinger J. D., et al., Ambulatory
polysomnography: technical aspects and normative values. J. Clin.
Neurophysiol., Vol. 9, No. 1, 1992.
11. Dijk, D. J., Beersma, D. G. and van den Hoofdakker ,R. H., All
night spectral analysis of EEG sleep in young adult and middle-aged
male subjects. Neurobiol. Aging. Vol. 10, No. 6, 1989.
12. Ruhenstroth-Bauer, G., Ruther, E., and Reinertshofer, T.,
Dependence of a sleeping parameter from the N-S or E-W sleep direction.
Z. Naturforsh [C], Vol. 42, No. 9-10, 1987.
13. Ruhenstroth-Bauer, G., Gunther, W., Hantschk, I., et al., Influence
of the Earth’s magnetic field on resting and activated EEG mapping in
normal subjects. Int. J. Neurosci., Vol. 73, No. 3-4, 1993.
14. Lebedeva, N. N., Reactions of the central nervous system to
electromagnetic fields with various biotropic parameters.
Biomeditsinskaya Radioelektronika, No. 1, 1998 (in Russian).
15. Mann, K. and Roschke, J., REM suppression induced by digital mobile
radio telephones. Wein. Med. Wochenschr., Vol. 146, No. 13-14, 1996.
16. Lebedeva, N. N., Sulimov, A. V., Sulimova, O. V., and Kotrovskaya,
T. I., Effect of the electromagnetic field of a mobile phone on the
bioelectrical activity of the human brain. Biomeditsinskaya
Radioelektronika, No. 4, 1998 (in Russian).
17. Sulimova, O. P., Electrical and Psychophysiological Reactions of
the Human Being on the Peripheral Influence of Low-intensity EHF
Electromagnetic Radiation. Abstract of Thesis for the Candidate of
Biological Science. Simferopol State University, 1992 (in Russian).
18. Fell, J. and Roschke, J., Nonlinear dynamical aspects of human
sleep EEG. Int. J. Neurosci., Vol. 76, No. 1-2, 1994.
Copied from microwave.com. not sure if you have seen this.