Keywords: simplified physical model of mediastinum, electrical impedance tomography, newborns, process of global and regional ventilation, lungs
Simplified physical models of the mediastinum of newborns for electrical impedance tomography
UDC 616-71
DOI: 10.26102/2310-6018/2025.48.1.011
The article presents the results of the development and experimental study of two simplified physical models of the neonatal mediastinum for electrical impedance tomography. The created models are based on spiral computed tomography data and take into account the anatomical features of the infant chest organs. The designs were implemented using 3D printing technologies, which made it possible to achieve high accuracy of geometric parameters. The models are equipped with a controlled air filling system for the lungs and three rows of electrodes, which makes it possible to conduct experiments on modeling global and regional ventilation. Experimental studies have demonstrated that the developed models make it possible to record respiratory volumes in the range from 2 to 120 ml, which corresponds to the physiological parameters of newborn breathing. The data obtained confirmed the operability of the models, their sensitivity to changes in air volumes, as well as their suitability for research and testing of new algorithms and methods in the field of electrical impedance tomography. It was found that the proposed models provide adequate reproduction of ventilation processes and can be used to develop diagnostic solutions in the field of neonatology. The results of the work are of practical value for scientific research aimed at improving methods for diagnosing respiratory disorders in newborns, and can be used in educational practice.
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Keywords: simplified physical model of mediastinum, electrical impedance tomography, newborns, process of global and regional ventilation, lungs
For citation: Konko M.A., Aleksanyan G.K., Gorbatenko N.I., Elkin N.S., Temnyakov N.S. Simplified physical models of the mediastinum of newborns for electrical impedance tomography. Modeling, Optimization and Information Technology. 2025;13(1). URL: https://moitvivt.ru/ru/journal/pdf?id=1791 DOI: 10.26102/2310-6018/2025.48.1.011 (In Russ).
Received 28.12.2024
Revised 22.01.2025
Accepted 27.01.2025