Development of switching and measurement circuits for problems of electric impedance tomography
DOI:
https://doi.org/10.15587/1729-4061.2020.210776Keywords:
electric impedance tomography, image reconstruction, medical visualization, conductivity distribution, measurement, switcherAbstract
This study solves the relevant problem of selecting an optimal switching and measurement circuit for the problems of reconstruction of the field of change in the conductivity in a biological object.
Based on an analysis of publications in the area of construction of the hardware part of the EIT devices, the main types of the systems were identified: sequential, parallel, and mixed. Because of the low cost, sequential architecture became most common.
Due to the low level of a useful signal in the study of lung ventilation, the differential measurement circuit, which enables amplification of a difference signal, is considered optimal. A difference signal changes significantly as it moves away from injecting electrodes, so the optimal use of the analog-to-digital converter scale requires a change in the amplification coefficient during the collection of measurement information. A measurement circuit with an adaptive amplification coefficient was proposed. The optimal amplification coefficient is determined by the results of test measurements. A block diagram for the implementation of the proposed algorithm was developed.
A circuit for switching the injecting and measuring electrodes, allowing the injection and measurement between any pair of electrodes, was proposed. Theoretical analysis of the impact of switch parameters was carried out. The analysis revealed that the main parameters influencing the metrological characteristics are the resistance of the open channel and its spread.
As a result of mathematical modeling of the circuit of substitution of injection and measurement channels, it was determined that channel resistance and its spread for typical switches results in a relative error in measurements of potentials of no more than 0.2 %
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Copyright (c) 2020 Artem Kucher, Nuri Narakidze, Polina Tjaglicova, Maryana Filonova
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