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Entropy of gas-discharge image correlates with the entropies of EEG, immunocytogram and leukocytogram but not HRV
Background. In implementing the project of verification gas discharge visualization (kirlianography, biophotonics) method, we documented the significant correlation of the gas discharge image parameters with the parameters of electroencephalogram, heart rate variability (HRV), dexterity and spastici...
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Published in: | Pedagogy and psychology of sport 2020-04, Vol.6 (2), p.30-39 |
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Main Authors: | , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
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Summary: | Background. In implementing the project of verification gas discharge visualization (kirlianography, biophotonics) method, we documented the significant correlation of the gas discharge image parameters with the parameters of electroencephalogram, heart rate variability (HRV), dexterity and spasticity of brush, blood pressure, as well as blood levels of adaptive hormones. As part of a project to investigate the physiological nature of entropy, we have shown that EEG entropy is related to a number of its amplitude-frequency and spectral parameters, as well as to the parameters HRV, blood leukocytogram and immunocytogram and their entropies. The purpose of this study is to analyze the relationships between the entropies of the listed information systems. Material and research methods. The object of observation were 20 volunteers: 10 women and 10 men aged 33-76 years without clinical diagnose but with dysfunction of neuro-endocrine-immune complex and metabolism. We registered twice kirlianogram by the method of GDV by the device of “GDV Chamber” (“Biotechprogress”), EEG (“NeuroCom Standard”, KhAI Medica), HRV ("CardioLab+HRV", "KhAI-Medica"), Leukocytogram and Immunocytogram. Than we calculated the entropies of the listed information systems. Results. By stepwise exclusion, 5 variables were included in the canonical GDV root structure, and 6 variables were included in the root EEG structure. Overall, GDI entropy determines the SPD EEG entropy by 33%. The additional inclusion in the dependent set the parameters of HRV, LCG and ICG entropies gives a increase in determination to 48%. HRV entropy was found outside the model. Conclusion. We have documented the relationship between the entropy parameters of electroencephalogram, blood leukocytogram and immunocytogram but not HRV on the one hand, and gas-discharge images on the other. However, the question of the causal nature of this relationship remains open. What is primary: electrical activity of the brain, excretion of cytokines and hormones by immunocytes, or emission of photons and free electrons by acupuncture points (circulation of vital energy)? |
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ISSN: | 2450-6605 2450-6605 |
DOI: | 10.12775/PPS.2020.06.02.003 |