• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.36-39
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• 2004

Electrical impedance tomography (EIT) has been suffered from the severe ill-posedness which is caused by the inherent low sensitivity of boundary measurements to any changes of internal resistivity values. So, small noise occur unexpected reconstruction image. Generally in EIT system, if measured voltage includes noise, we can't find object location and resistivity values. In this paper, we propose digital filter for measured voltage in EIT. Newton-Raphson is the most..popular algorithm in EIT, but noise cause to blur image. We use Fourier transform (FT) in order to minimize the noise and design the filter. After filtering, result of reconstruction image is improved better than before filtering.

• Journal of IKEEE
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• v.23 no.1
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• pp.164-172
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• 2019

Current clinical methods for diagnosing urination disorder are invasive, expensive, and very inconvenient to perform continuous monitoring. EIT is a non-invasive technique that injects electrical current through an external electrodes and measures the induced voltage to visualize the internal electrical (impedance) characteristics, which makes it possible to monitor bladder conditions with low cost. The signal characteristics of the measured voltage data changes according to the current pattern injected through the electrode and affects reconstruction performance. In this paper, image reconstruction performance is compared and analyzed according to the injected current patterns to maximize the sensitivity to the variation of bladder size.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.118-121
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• 2003

In the conventional boundary estimation in EIT (Electrical Impedance Tomography), the interface between anomalies and background is expressed in usual as Fourier series and the boundary is reconstructed by obtaining the Fourier coefficients. This paper proposes a method for the boundary estimation, where the boundary of anomaly is approximated as the interpolation of front points located discretely along the boundary and is imaged by tracking the points in the region of interest. In the solution to the inverse problem to estimate the front points, the multi-layer neural network is introduced. For the verification of the proposed method, numerical experiments are conducted and the results indicate a good performance.

• Journal of IKEEE
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• v.19 no.1
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• pp.33-40
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• 2015

Inverse problem in electrical impedance tomography (EIT) is highly ill-posed therefore prior information is used to mitigate the ill-posedness. Regularization methods are often adopted in solving EIT inverse problem to have satisfactory reconstruction performance. In solving the EIT inverse problem, iterative Gauss-Newton method is generally used due to its accuracy and fast convergence. However, its performance is still suboptimal and mainly depends on the selection of regularization parameter. Although, there are few methods available to determine the regularization parameter such as L-curve method they are sometimes not applicable for all cases. Moreover, regularization parameter is a scalar and it is fixed during iteration process. Therefore, in this paper, a novel method is used to determine the regularization parameter to improve reconstruction performance. Conductivity norm is calculated at each iteration step and it used to obtain the regularization parameter which is a diagonal matrix in this case. The proposed method is applied to human thorax imaging and the reconstruction performance is compared with traditional methods. From numerical results, improved performance of proposed method is seen as compared to conventional methods.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.2
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• pp.167-180
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• 2014

In this paper we consider a novel reconstruction method in electrical impedance tomography (EIT) and its application for monitoring and detecting a hydrargyrum (mercury) polluted soil near to the surface of underground. We use electrodes placed on the surface of land to collect the data which provides the relations of voltage and current map and to produce a projected image of interior conductivity distribution onto the surface of land. Here the projected image reconstruction method is used to monitor the pollution in soil underneath the ground without any destruction and any digging into a land.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.39.1-39
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• 2001

Impedance tomography (EIT) is a relatively new imaging modality in which the internal impedivity distribution is reconstructed based on the known sets of injected currents through the electrodes and induced voltages on the surface of the object. We describe a dynamic EIT imaging technique for the case where the resistivity distribution inside the object changes rapidly within the time taken to acquire a full set of independent measurement data, In doing so, the inverse problem is treated as the nonlinear state estimation problem and the unknown state (resistivity) is estimated with the aid of extended Kalman filter in a minimum mean square error sense. In particular, additional electrodes are attached to the known internal structure of the object ...

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.457-462
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• 1998

유동장에서의 기포거동 정보의 중요성 때문에 이를 정확히 측정하기 위한 실험방법이 여러 가지로 발전해 왔지만 아직까지도 기포분포에 대한 정확한 정보 추출에는 도달하지 못하고 있다. 본 연구에서는 원래 의공학분야에서 새로운 tomography 기술로 연구되고 있는 EIT(Electrical Impedance Tomography) 기술을 2상유동에서의 기포분포 측정방법 개발에 적용하기 위한 기초연구와 기포분포 가시화를 위한 전산실험을 수행하였다. 기포분포 가시화를 위해서는 EIT inverse problem solver로 많이 사용되는 iNR(improved Newton-Raphson) 계열의 EIT 염상복원 프로그램을 본 연구진이 유전알고리즘(Genetic Algorithm)과 fuzzy-based mesh grouping 방법을 추가하여 개선한 영상복원프로그램을 사용하였다. 전산실험 결과 본 영상복원프로그램으로는 12$\times$12의 분해능으로 모사되는 기포분포를 저항률 오차한도 $\pm$1%의 신뢰도로 PC상에서 복원이 가능함을 확인하였다.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.66-74
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• 2007

We have developed a multi-channel, multi-frequency EIT system with operating frequency of 10Hz to 500KHz. The number of digital voltmeters using phase-sensitive demodulation can be varied from 8 to 64 and we found that 16 and 32-channels are most practical. This paper describes the design, implementation, and construction of 16 and 32-channel systems. The performance of the system was thoroughly tested and we found that CMRR of the developed voltmeter is about 85dB with $100{\Omega}$ unbalancing series resistor. The SNR is greater than 99.6dB and the output impedance of the constant current source is $1{\Omega}W$ at least for all frequencies. Imaging experiments using a banana with frequency-dependent conductivity and permittivity show that frequency-difference imaging is possible using the developed system. Future works of animal and human experiments are discussed.

• Communications of the Korean Mathematical Society
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• v.16 no.3
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• pp.459-485
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• 2001

The aim of EIT (electrical impedance tomography) system is to image cross-section conductivity distribution of a human body by means of both generating and sensing electrodes attached on to the surface of the body, where currents are injected and voltages are measured. EIT has been suffered from the severe ill-posedness which is caused by the inherent low sensitivity of boundary measurements to any changes of internal tissue conductivity values. With a limited set of current-to-voltage data, figuring out full structure of the conductivity distribution could be extremely difficult at present time, so it could be worthwhile to extract some necessary partial information of the internal conductivity. We try to extract some key patterns of current-to-voltage data that furnish some core information on the conductivity distribution such s location and size. This overview provides our recent observation on the location search and the size estimation.