A Coupled Double-Layer Electrical Impedance Tomography-Based Sensing Skin for Pressure and Leak Detection.

There is an extensive need for surface sensors for applications such as tactile sensing for robotics, damage and strain detection for structural health monitoring and leak detection for buried structures. One type of surface sensor is electrical impedance tomography (EIT)-based sensing skins, which use electrically conductive coatings applied on the object's surface to monitor physical or chemical phenomena on the surface. In this article, we propose a sensing skin with two electrically coupled layers separated by an insulator. Based on electrical measurements, the spatial distribution of the electrical coupling between the layers is estimated. This coupling is sensitive to both the pressure distribution on the surface and water entering between the layers through a leak. We present simulations and experimental studies to evaluate the feasibility of the proposed method for pressure sensing and leak detection. The results support the feasibility of the proposed method for both of these applications.

Improvements in Maturity and Stability of 3D iPSC-Derived Hepatocyte-like Cell Cultures.

Induced pluripotent stem cell (iPSC) technology enables differentiation of human hepatocytes or hepatocyte-like cells (iPSC-HLCs). Advances in 3D culturing platforms enable the development of more in vivo-like liver models that recapitulate the complex liver architecture and functionality better than traditional 2D monocultures. Moreover, within the liver, non-parenchymal cells (NPCs) are critically involved in the regulation and maintenance of hepatocyte metabolic function. Thus, models combining 3D culture and co-culturing of various cell types potentially create more functional in vitro liver models than 2D monocultures. Here, we report the establishment of 3D cultures of iPSC-HLCs alone and in co-culture with human umbilical vein endothelial cells (HUVECs) and adipose tissue-derived mesenchymal stem/stromal cells (hASCs). The 3D cultures were performed as spheroids or on microfluidic chips utilizing various biomaterials. Our results show that both 3D spheroid and on-chip culture enhance the expression of mature liver marker genes and proteins compared to 2D. Among the spheroid models, we saw the best functionality in iPSC-HLC monoculture spheroids. On the contrary, in the chip system, the multilineage model outperformed the monoculture chip model. Additionally, the optical projection tomography (OPT) and electrical impedance tomography (EIT) system revealed changes in spheroid size and electrical conductivity during spheroid culture, suggesting changes in cell-cell connections. Altogether, the present study demonstrates that iPSC-HLCs can successfully be cultured in 3D as spheroids and on microfluidic chips, and co-culturing iPSC-HLCs with NPCs enhances their functionality. These 3D in vitro liver systems are promising human-derived platforms usable in various liver-related studies, specifically when using patient-specific iPSCs.

Dual-Modal Electrical Imaging of Two-Phase Flow-Experimental Evaluation of the State Estimation Approach.

Accurate measurement of two-phase flow quantities is essential for managing production in many industries. However, the inherent complexity of two-phase flow often makes estimating these quantities difficult, necessitating the development of reliable techniques for quantifying two-phase flow. In this paper, we investigated the feasibility of using state estimation for dynamic image reconstruction in dual-modal tomography of two-phase oil-water flow. We utilized electromagnetic flow tomography (EMFT) to estimate velocity fields and electrical tomography (ET) to determine phase fraction distributions. In state estimation, the contribution of the velocity field to the temporal evolution of the phase fraction distribution was accounted for by approximating the process with a convection-diffusion model. The extended Kalman filter (EKF) and fixed-interval Kalman smoother (FIKS) were used to reconstruct the temporally evolving velocity and phase fraction distributions, which were further used to estimate the volumetric flow rates of the phases. Experimental results on a laboratory setup showed that the FIKS approach outperformed the conventional stationary reconstructions, with the average relative errors of the volumetric flow rates of oil and water being less than 4%. The FIKS approach also provided feasible uncertainty estimates for the velocity, phase fraction, and volumetric flow rate of the phases, enhancing the reliability of the state estimation approach.

Nonlinear Difference Imaging Approach to Three-Dimensional Electrical Impedance Tomography in the Presence of Geometric Modeling Errors.

OBJECTIVE: To evaluate the recently proposed nonlinear difference imaging approach to electrical impedance tomography (EIT) in realistic 3-D geometries. METHODS: In this paper, the feasibility of nonlinear difference approach-based EIT is tested using simulation studies in 3-D geometries of thorax and larynx, and with an experimental study of a thorax-shaped water tank. All test cases exhibit severe modeling errors due to uncertainty in the boundary shape of the body. RESULTS: In all test cases, the conductivity change reconstructed with nonlinear difference imaging outperforms the conventional reconstructions qualitatively and quantitatively. CONCLUSION: The results demonstrate that the nonlinear difference reconstructions tolerate geometrical modeling errors at least to the same extent as the conventional linear approach and produce quantitatively more accurate information on the conductivity change. SIGNIFICANCE: Physiological processes that produce changes in the electrical conductivity of the body can be monitored with difference imaging based on EIT. The wide popularity of linearized difference imaging in EIT is mainly based on its good tolerance for the ubiquitous modeling errors, which are predominantly caused by inexact knowledge of the body geometry. However, the linearized difference imaging produces only qualitative information on the conductivity change, and the feasibility of the estimates also depends on the selection of the linearization point which ideally should be equal to the conductivity of the initial state. Based on the findings of this paper, these problems can be avoided by nonlinear difference imaging, and potentially the approach can enable quantitative imaging of conductivity change in medical applications.

Nonlinear approach to difference imaging in diffuse optical tomography.

Difference imaging aims at recovery of the change in the optical properties of a body based on measurements before and after the change. Conventionally, the image reconstruction is based on using difference of the measurements and a linear approximation of the observation model. One of the main benefits of the linearized difference reconstruction is that the approach has a good tolerance to modeling errors, which cancel out partially in the subtraction of the measurements. However, a drawback of the approach is that the difference images are usually only qualitative in nature and their spatial resolution can be weak because they rely on the global linearization of the nonlinear observation model. To overcome the limitations of the linear approach, we investigate a nonlinear approach for difference imaging where the images of the optical parameters before and after the change are reconstructed simultaneously based on the two datasets. We tested the feasibility of the method with simulations and experimental data from a phantom and studied how the approach tolerates modeling errors like domain truncation, optode coupling errors, and domain shape errors.