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Electrical impedance tomography (EIT) is a promising technique for conductivity distribution reconstruction. Considering the fact that cerebral disease causes variation of conductivity distribution, EIT technique can be used to reflect the pathological change in the cerebral region. This would offer an alternative for the timely diagnosis and treatment of cerebral disease. In cerebral EIT, contact impedance between the electrode and the scalp changes with time, which largely affects the reconstruction quality. To conquer this problem, a compensation method is proposed for voltage data correction when contact impedance varies. By analysis of boundary measurement, the electrode with contact impedance variation and how much contact impedance changes are determined. Together with a prior matrix, voltage data in the case of contact impedance variation can be compensated. Reconstruction of conductivity distribution is implemented by the L1 regularization method. The performance of the proposed method is evaluated under contact impedance variation of a single electrode, a pair of electrodes, and 16 electrodes. In addition, the influence of noise with a signal-to-noise ratio of 40 dB is studied. The results show that the proposed method can effectively suppress the effect of contact impedance change on image quality. Even under the impact of noise, reconstructed images show great improvement. With this method, it is able to monitor cerebral disease in the clinical application of EIT where contact impedance variation is inevitable. [ABSTRACT FROM AUTHOR]

Electrical impedance tomography (EIT) has attracted research interests in imaging of brain function, detection of breast cancer, monitoring of lung function and other medical fields. For EIT, its image reconstruction is largely affected by variation of electrode placement arranged around the detected object. Note that electrode offset is unavoidable in some medical applications, leading to low-quality reconstructed images or even failure of reconstruction. In this paper, a novel method is proposed to improve reconstruction quality in case of electrode offset. By identifying which electrode moves, mismatched boundary voltage caused by movement of electrode is corrected. After mismatch correction, image reconstruction is conducted with total generalized variation regularization method. To demonstrate performance of the proposed method in suppressing impact of electrode offset on reconstruction, extensive work is carried out. Mismatch corrections for four models under a series of counterclockwise or clockwise movements of a certain electrode are studied. The reconstruction results show that the proposed method can effectively improve the image quality under electrode offset. Even in presence of larger electrode offset and noise, reconstructed images have been greatly improved. Quantitative evaluation is also conducted by calculating relative blur radius (RBR). It is shown that RBR values are much closer to 1 compared with results under mismatch conditions. Image reconstruction when two electrodes move is also investigated which further validate the performance of the proposed method. This method is potential for mismatch correction in some medical applications. [ABSTRACT FROM AUTHOR]

Image reconstruction of conductivity distribution is a highly nonlinear ill-posed inverse problem in electrical impedance tomography (EIT). To solve the problem, Tikhonov regularization and total variation (TV) regularization methods have been generally adopted. However, reconstructed images suffer from excessive smoothness or staircase effect. In this article, a novel approach is proposed for imaging conductivity distribution. Unlike traditional regularization methods, fidelity term based on $L_{1}$ -norm is introduced to stabilize the ill-posed problem and enforce sparsity in the solution. Moreover, a first-order and high-order TV combined hybrid penalty term is introduced to keep the sharp profile and restrain the staircase effect. During image reconstruction, regularization parameter and weighting factor are determined by the adaptive method. In addition, a soft-thresholding operator is introduced to remove artifact and enhance robustness to noise. Numerical simulations have been performed to validate the performance of the proposed approach against Landweber, Tikhonov, TV, high-order TV, and iterated soft-thresholding methods. The impacts of conductivity distribution, conductivity contrast, contact impedance, and boundary shape on reconstruction are studied. Besides, robustness to noise and computation time are evaluated. The performance of the proposed approach is also verified by phantom experiments. Simulation and experimental results demonstrate that the proposed approach performs well in image reconstruction of conductivity distribution. Clearer background is observed and inclusions with sharp or smooth edges can be better reconstructed. [ABSTRACT FROM AUTHOR]

Electrical impedance tomography (EIT) is a potential imaging technique for reconstructing the interior conductivity distribution within an object. The reconstruction is realized by processing the boundary voltage measured from the EIT. Mathematically, the reconstruction of conductivity distribution is a highly nonlinear ill-posed inverse problem as the solution is not unique and is sensitive to the noise, which largely hinders the practical application of the EIT technique. In this paper, a novel modified non-convex ${L}_{1}$ -norm penalty based total generalized variation (NCP-TGV) model is proposed to solve the inverse problem and reconstruct the conductivity distribution. An iteratively reweighted ${L}_{1}$ algorithm is developed to convert the non-convex model to convex function and the Chambolle-Pock primal-dual algorithm is then applied to solve the minimization problem. To demonstrate the performance of the proposed NCP-TGV model in reconstructing the conductivity distribution, extensive numerical simulation and experimental work have been carried out. Additionally, the proposed approach has been validated by comparing its performance with the convex ${L}_{1}$ -norm penalty based total variation (TV) and TGV inverse models. The results indicate that the images reconstructed by the proposed NCP-TGV model show better quality with the advantages of simultaneous reduction of staircase effect and preservation of edge in comparison to the TV and TGV approaches. [ABSTRACT FROM AUTHOR]

The regularization method has been utilized to address the ill-posed inverse problem of electrical resistance tomography (ERT). As one of the regularization methods, the total variation (TV) regularization method has the advantage of edge-preserving. A majority of research has been focused on the study of the penalty term in the TV method. In this article, a novel TV regularization based on iteratively reweighted least squares (TV-IRLS) method is proposed, in which, $L_{1}$ -norm is applied to the fidelity term, and a weighting matrix is applied to convert the $L_{1}$ -norm to $L_{2}$ -norm when calculating the objective function, which reduces the difficulty of solving the $L_{1}$ -norm. An improved generalized cross-validation method is adopted to determine the optimal regularization parameter (RP) automatically, and an automatic method is presented for the selection of the threshold value in the weighting matrix to guarantee the accuracy and speed of the solution. Meanwhile, a scaling factor is introduced to constrain the solution and ensure the stability of the solution. For verifying the performance of the proposed TV-IRLS regularization method, both numerical simulation and static experiments are carried out in the image reconstruction of ERT through qualitative and quantitative analysis. The results demonstrate that the proposed TV-IRLS regularization method performs well in improving the quality and resolution of the reconstructed images in ERT. Besides, it is more robust to data noises compared with the Tikhonov regularization method and TV regularization method. [ABSTRACT FROM AUTHOR]

Image reconstruction in electrical impedance tomography is an ill-posed inverse problem. To address this problem, regularization methods such as Tikhonov regularization and total variation regularization have been adopted. However, the image is over-smoothed when reconstructing with the Tikhonov regularization and staircase effect appears in the image when using the total variation regularization. In this paper, the total generalized variation regularization method which combines the first-order and the second-order derivative terms to perform as the regularization term is proposed to cope with the above problems. The weight between the two derivative terms is adjusted by the weighting factors. Chambolle-Pock primal-dual algorithm, an efficient iterative algorithm to handle optimization problem and solve dual problem, is developed. Simulation and experiments are performed to verify the performance of the total generalized variation regularization method against other regularization methods. Besides, the relative error and correlation coefficient are also calculated to estimate the proposed regularization methods quantitatively. The results indicate that the staircase effect is effectively reduced and the sharp edge is well-preserved in the reconstructed image. [ABSTRACT FROM AUTHOR]

To improve the power transfer efficiency in wireless power transfer systems, a novel configuration of a magnetic resonant structure is proposed in this paper. According to the analytical expression of mutual inductance, the magnetic field can be improved by weakening the demagnetizing factor for coils with a ferrite core. In this paper, the demagnetizing factors of a cylindrical ferrite core and a novel ferrite core are investigated. Compared with the cylindrical ferrite core, the proposed ferrite core has a smaller demagnetizing factor and an increased mutual inductance. In addition, the magnetic field through the receiving coil is enhanced due to the thin ferrite axis where the magnetic field is concentrated. The proposed ferrite core is designed and analyzed. Moreover, the effects of pitch and lateral misalignment, as well as the number of turns of the receiving coil, the core loss, and the load, are studied. Experimental prototypes are established to validate the performance of the wireless power transfer system with different types of receiving structures. The results indicate that the proposed structure is superior to others and that it shows better performance in power transfer efficiency and transfer distance, which is in good agreement with the theoretical and simulation analysis. [ABSTRACT FROM AUTHOR]

A compact and broadband rectifying antenna (rectenna) which consists of a novel slotted antenna and an efficient rectifying circuit is presented for wireless power transfer at LTE-2300/2500 band. Three different broadband antennas have been investigated and compared. It is found that the newly designed antenna which combines the annular slot radiation patch and a slotted ground plane (GP) has the widest bandwidth and the best matching characteristic. A new broadband dual-stub matching network is proposed to maximize the transmission of wireless power and enhance the reliability of the rectifier when the input power and load varies. In addition, the ground of the rectifier is directly connected to the GP of the antenna for compactness and low energy loss. The proposed designs have been simulated, fabricated, and tested. The results indicate that the proposed receiving antenna performs well at LTE band with a wide bandwidth from 2 to 3.1 GHz. The maximum efficiency of the proposed rectenna reaches 70% at 2.5 GHz under the input power of 5 dBm. Furthermore, the rectenna remains at a relatively efficient power conversion when the load varies in a wide range from 2 to 20 $\text{k}\Omega $ under different low input power, which is of great significance when the ambient radio frequency(F) signal is weak. Therefore, the rectenna is potentially applicable to a wide range of low-power electronic devices by harvesting RF energy at LTE band. [ABSTRACT FROM AUTHOR]

We present a contact method for the complex permittivity measurement of materials based on a two-port microwave sensor over a frequency range of 3–4 GHz. The proposed sensor is composed of a 3-dB directional coupler with the direct and coupled ports each connecting an open-ended transmission line. Two simple un-calibrated scattering parameters are required to extract the complex permittivity of the materials under test (MUT). One is for the empty sensor, and the other is for the MUT loaded on the sensor. Additionally, the relation expression between complex permittivity and measured scattering parameters is presented. Some experiments were carried out over the whole frequency range. The results agree well with the resonant method. This transmission-reflection method can provide a highly accurate measurement for only requirement of amplitude information of the S-parameters. To low-loss materials, the relative errors of the calculated results are less than 4% for real part and 6% for imaginary part of permittivity in comparisons with the literature data. [ABSTRACT FROM AUTHOR]