Analysis of biomedical signals by flicker-noise spectroscopy: Identification of photosensitive epilepsy using magnetoencephalograms

Тимашев, С. Ф.; Polyakov, Yuriy; Yulmetyev, Renat M.; Demin, Sergey; Panischev, O. Yu.; Shimojo, Shinsuke; Bhattacharya, Joydeep

doi:10.1134/s1054660x09040434

Cited by 26 publications

(19 citation statements)

References 28 publications

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“…An example that is often quoted as evidence of this fact is the application of FNS in the analysis of the effect of different types of medical treatment on the dynamics of index finger tremor in Parkinsonian patients [65]. Moreover, Timashev et al [52] used FNS for the identification of the photosensitive epilepsy. Their results suggest that FNS is a promising method of early diagnosis, not only for the photosensitive epilepsy but also for other neurodegenerative diseases such as Parkinson’s, Alzheimer’s, Huntington’s, amyotrophic lateral sclerosis and schizophrenia.…”

Section: Introductionmentioning

confidence: 99%

Analysis of EEG signal by flicker-noise spectroscopy: identification of right-/left-hand movement imagination

Broniec

2016

Med Biol Eng Comput

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Flicker-noise spectroscopy (FNS) is a general phenomenological approach to analyzing dynamics of complex nonlinear systems by extracting information contained in chaotic signals. The main idea of FNS is to describe an information hidden in correlation links, which are present in the chaotic component of the signal, by a set of parameters. In the paper, FNS is used for the analysis of electroencephalography signal related to the hand movement imagination. The signal has been parametrized in accordance with the FNS method, and significant changes in the FNS parameters have been observed, at the time when the subject imagines the movement. For the right-hand movement imagination, abrupt changes (visible as a peak) of the parameters, calculated for the data recorded from the left hemisphere, appear at the time corresponding to the initial moment of the imagination. In contrary, for the left-hand movement imagination, the meaningful changes in the parameters are observed for the data recorded from the right hemisphere. As the motor cortex is activated mainly contralaterally to the hand, the analysis of the FNS parameters allows to distinguish between the imagination of the right- and left-hand movement. This opens its potential application in the brain–computer interface.

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Section: Introductionmentioning

confidence: 99%

Analysis of EEG signal by flicker-noise spectroscopy: identification of right-/left-hand movement imagination

Broniec

2016

Med Biol Eng Comput

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“…In the latter cases, this concerns not only an analysis of known atmospheric aerosol components, but also an analysis of biological and medical responses of flora and fauna of the biosphere to the impacts of aerosols. Such studies are feasible, because the FNS method has demonstrated its capabilities in analyzing of responses of native systems [20,21].…”

Section: Discussionmentioning

confidence: 99%

Dynamic state of the atmosphere in aerosol components

Zagainov

Timashev

Biryukov

et al. 2012

Russ. J. Phys. Chem. B

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An approach to analyzing experimental data on the size distribution and concentrations of atmo spheric aerosol particles and meteorological parameters by using the flicker noise spectroscopy is proposed. This approach makes it possible to identify the character of evolution of the measured parameters due to the processes underlying their variation, to trace the relationship between measured quantities, and, based on this, to determine the mechanisms of interactions between aerosol particles and gaseous components of the atmosphere. As an example, the behavior of the concentration, average particle size, and relative humidity of the atmosphere is examined. Atmospheric measurements were carried out at the recreation center in Tishk ovo (Moscow Region). The proposed approach may prove useful in solving ecological and environmental problems.

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“…It is widely known that the disease received after cases of mass attacks in Japan during the demonstration of the animated series "Pokemon." Previously, the individual characteristics of the subjects' reactions have been identified based on the method of flickernoise spectroscopy on a red-blue and red-green incentive, and set the degree of contribution of various types of irregularities in normal and pathological dynamics of brain activity signals [29]. The Fractal Analysis of the Images and Signals in Medical Diagnostics http://dx.doi.org/10.5772/intechopen.68167…”

Section: Self-similar Mechanism Neuromagnetic Dynamics Of Brain Activitymentioning

confidence: 99%

The Fractal Analysis of the Images and Signals in Medical Diagnostics

Albertovich¹,

Aleksandrovna²

2017

Fractal Analysis - Applications in Health Sciences and Social Sciences

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In the present chapter, we summarize our results concerning fractal analysis of some medical data. The aim of this study is to identify the inherent human body "chaotic" dynamics and insufficient disclosure of the physical essence of the processes observed, depending on the extent of developing a pathology that is characterized by a decrease or increase in the degree of complexity and as a consequence-randomness, for which, in some cases, hidden fractal. The proposed approach based on identifying the presence of the properties of self-similarity can be useful in preliminary clinical trials for the diagnosis of cancerous epithelial diseases, blood, and liver in the initial stage, the analysis of digital images, the structure of correlations biomedical parameters, as well as in the study of pathologies of the central nervous system-the neurological, neurodegenerative disorders, psychiatric disorders, and may be the basis for the development of the interface "brain-computer", on the basis of electroencephalography and magnetoencephalography. Additional measures are proposed to study the presence of self-similar properties in the form of self-similarity and magnitude SRGB ratio (area of a triangle in the coordinate system of the properties).

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Analysis of biomedical signals by flicker-noise spectroscopy: Identification of photosensitive epilepsy using magnetoencephalograms

Cited by 26 publications

References 28 publications

Analysis of EEG signal by flicker-noise spectroscopy: identification of right-/left-hand movement imagination

Analysis of EEG signal by flicker-noise spectroscopy: identification of right-/left-hand movement imagination

Dynamic state of the atmosphere in aerosol components

The Fractal Analysis of the Images and Signals in Medical Diagnostics

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