Issue |
BIO Web Conf.
Volume 71, 2023
II International Conference on Current Issues of Breeding, Technology and Processing of Agricultural Crops, and Environment (CIBTA-II-2023)
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Article Number | 01114 | |
Number of page(s) | 9 | |
Section | Issues of Sustainable Development of Agriculture | |
DOI | https://doi.org/10.1051/bioconf/20237101114 | |
Published online | 07 November 2023 |
Determination of intracellular electrical parameters in bioelectrical impedance analysis
1 Azerbaijan State Oil and Industry University, Baku, Azerbaijan
2 Kuban State Agrarian University named after I.T. Trubilin, 13, Kalinina Street, Krasnodar, Russia
3 Samara State University of Economics, 141, Sovetskoi Armii St., Samara, Russia
* Corresponding author: qafarov1997@gmail.com
Creating a frequency characteristic curve for bioelectrical impedance analysis involves analyzing electrical resistance (impedance) values at different frequencies. This curve is used to evaluate the electrical properties of biological tissues or fluids. In the article, the impedance of the intracellular environment was evaluated and frequency dependence was established based on the electrical circuit model of the biological system. Xc = f(f), Z = f(f), φ= f(f) tgδ= f(f), dependencies were created for different frequency values of the intracellular environment in the Matlab program through a series-connected RC circuit. Regression and general statistical analyzes were performed. The most appropriate frequency range was determined to evaluate the impedance of the intracellular environment. The correlation relationship of electrical and dielectric parameters of the intracellular environment was also taken into account. Purpose: The main goal of the research is the selection of the optimal frequency range for bioimpedance analysis. In particular, the selection of the most optimal frequency was carried out in the assessment of intracellular electrical activity. The frequency range is determined depending on the electrical and dielectric parameters of the cell. Materials and Methods: Using the Matlab program, the equivalent circuit model of the cell was assembled. Frequency dependence of electrical and dielectric parameters characterizing intracellular processes was performed by model-based measurements. Conclusion: According to the obtained value, regression and general statistical analyzes were performed for the dependencies Xc=f(f), Z=f(f), φ=f(f), tgδ=f(f). Based on analysis of variance (Analysis of Variance-ANOVA) of the output variables, statistical parameters were determined for each dependency.
© The Authors, published by EDP Sciences, 2023
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