Experimental dependences of measurement data on the volume of inhaled air in multi-frequency electrical impedance tomography
DOI:
https://doi.org/10.15587/1729-4061.2021.241769Keywords:
electric impedance tomography, multifrequency, measurement data, respiratory volumes, experimental studies, conductivityAbstract
This paper proposes an approach to modeling the process of artificial ventilation of human lungs by their controlled filling with a fixed volume of air, using an incentive spirometer Coach 2. This makes it possible to simulate the ventilation process for a healthy person and to link the assigned respiratory volume to measurement data. The results of experimental studies of the developed system of multifrequency electric impedance tomography are presented. The tests were performed for the frequency range from 50 kHz to 400 kHz (with a pitch of 50 kHz) at assigned respiratory volumes from 500 ml to 4,000 ml (with a pitch of 500 ml) for five inhalation/exhalation cycles. The scheme of research: active inhalation ‒ passive exhalation, the number of tested volunteers ‒ 3 people from the developers of the system. As a result, the dependences of the measured values of changes in potentials on the frequency of injected current for different respiratory volumes in three test participants without pathologies of the respiratory function and the external respiration function were obtained. The obtained results of the experimental studies show that there is a dependence of the value of the measurement data both on the volume of inhaled air and on the frequency of the injected current. This feature can be used to develop a number of medical devices for personalized monitoring of human lung function. It was also revealed that there are frequencies at which the maximum spread of measurement data according to the results of a series of repeated experiments is observed. At the same time, the nature of the change in the measurement data of the EIT at an increase in the volume of inhaled air is the same for all test participants. It is assumed that this feature can also be used to increase the EIT personalization degree
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