Combined Optimization of Both Sensitivity Matrix and Residual Error for Improving EIT Imaging Quality

Jidong Guo, Qiao Xin and Shihong Yue ()
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Jidong Guo: School of Mathematics, Yili Normal University, Yili 835001, China
Qiao Xin: School of Mathematics, Yili Normal University, Yili 835001, China
Shihong Yue: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China

Mathematics, 2025, vol. 13, issue 16, 1-13

Abstract: As a visual detection technique, Electrical Impedance Tomography (EIT) can reconstruct the distribution of electrical parameters within a detection field. EIT reconstruction greatly depends on a physical equation that includes a sensitivity matrix and measurements, but the sensitivity matrix fails to be optimized for various reconstruction tasks. This issue decreases the applicable range of the physical equation and EIT reconstruction quality. To address this issue, this paper optimizes both the residual error for measurements and the sensitivity matrix in the equation, which leads to higher EIT reconstruction quality. The optimization solution is theoretically and experimentally verified. Results indicate that the proposed methods can reduce the relative error of EIT reconstruction quality by about 12.0%.

Keywords: electrical impedance tomography; sensitivity matrix; residual error; optimization; objective function (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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