Microscale 3-D Capacitance Tomography with a CMOS Sensor Array

Electrical capacitance tomography (ECT) is a non-optical imaging technique in which a map of the interior permittivity of a volume is estimated by making capacitance measurements at its boundary and solving an inverse problem. While previous ECT demonstrations have often been at centimeter scales, ECT is not limited to macroscopic systems. In this paper, we demonstrate ECT imaging of polymer microspheres and bacterial biofilms using a CMOS microelectrode array, achieving spatial resolution of 10 microns. Additionally, we propose a deep learning architecture and an improved multi-objective training scheme for reconstructing out-of-plane permittivity maps from the sensor measurements. Experimental results show that the proposed approach is able to resolve microscopic 3-D structures, achieving 91.5% prediction accuracy on the microsphere dataset and 82.7% on the biofilm dataset, including an average of 4.6% improvement over baseline computational methods.

Dynamic Classification of Imageless Bioelectrical Impedance Tomography Features with Attention-Driven Spatial Transformer Neural Network

Point-of-Care monitoring devices have proven to be pivotal in the timely screening and intervention of critical care patients. The urgent demands for their deployment in the COVID-19 pandemic era has translated into the escalation of rapid, reliable, and low-cost monitoring systems research and development. Electrical Impedance Tomography (EIT) is a highly promising modality in providing deep tissue imaging that aids in patient bedside diagnosis and treatment. Motivated to bring forth an accurate and intelligent EIT screening system, we bypassed the complexity and challenges typically associated with its image reconstruction and feature identification processes by solely focusing on the raw data output to extract the embedded knowledge. We developed a novel machine learning architecture based on an attention-driven spatial transformer neural network to specifically accommodate for the patterns and dependencies within EIT raw data. Through elaborate precision-mapped phantom experiments, we validated the reproduction and recognition of features with systemically controlled changes. We demonstrated over 95% accuracy via state-of-the-art machine learning models, and an enhanced performance using our adapted transformer pipeline with shorter training time and greater computational efficiency. Our approach of using imageless EIT driven by a novel attention-focused feature learning algorithm is highly promising in revolutionizing conventional EIT operations and augmenting its practical usage in medicine and beyond.

Performance Prediction, Sensitivity Analysis and Parametric Optimization of Electrical Impedance Tomography Using A Bioelectrical Tissue Simulation Platform

There is an urgent need to bring forth portable, low-cost, point-of-care diagnostic instruments to monitor patient health and wellbeing. This is elevated by the COVID-19 global pandemic in which the availability of proper lung imaging equipment has proven to be pivotal in the timely treatment of patients. Electrical impedance tomography (EIT) has long been studied and utilized as such a critical imaging device in hospitals especially for lung ventilation. Despite decades of research and development, many challenges remain with EIT in terms of 1) optimal image reconstruction algorithms, 2) simulation and measurement protocols, 3) hardware imperfections, and 4) uncompensated tissue bioelectrical physiology. Due to the inter-connectivity of these challenges, singular solutions to improve EIT performance continue to fall short of the desired sensitivity and accuracy. Motivated to gain a better understanding and optimization of the EIT system, we report the development of a bioelectric facsimile simulator demonstrating the dynamic operations, sensitivity analysis, and reconstruction outcome prediction of the EIT sensor with stepwise visualization. By building a sandbox platform to incorporate full anatomical and bioelectrical properties of the tissue under study into the simulation, we created a tissue-mimicking phantom with adjustable EIT parameters to interpret bioelectrical interactions and to optimize image reconstruction accuracy through improved hardware setup and sensing protocol selections.

Hardware for cell culture electrical impedance tomography: A critical review

Human cell cultures are powerful laboratory tools for biological models of diseases, drug development, and tissue engineering. However, the success of biological experiments often depends on real-time monitoring of the culture state. Conventional culture evaluation methods consist of end-point laborious techniques, not capable of real-time operation and not suitable for three-dimensional cultures. Electrical Impedance Tomography (EIT) is a non-invasive imaging technique with high potential to be used in cell culture monitoring due to its biocompatibility, non-invasiveness, high temporal resolution, compact hardware, automatic operation, and high throughput. This review approaches the different hardware strategies for cell culture EIT that are presented in the literature, discussing the main components of the measurement system: excitation circuit, voltage/current sensing, switching stage, signal specifications, electrode configurations, measurement protocols, and calibration strategies. The different approaches are qualitatively discussed and compared, and design guidelines are proposed.

Design of Bio-Impedance Electrode Topologies for Specific Depth Sensing in Skin Layer

Bio-impedance analysis provides non-invasive estimation of body composition. Recently, applications based on bio-impedance measurement in skin tissue such as skin cancer diagnosis and skin composition monitoring have been studied. For scanning the electrical properties along the skin depth, the relationship between the electrode topologies and the depth sensitivity should be clarified. This work reports a systematic analysis on designing line electrode topologies to measure the bio-impedance of the skin layer at specific depth using a finite element method (FEM). Four electrodes consisting of two outer current electrodes and two inner voltage electrodes in the form of Wenner-Schlumberger array were employed on the top of a collagen layer as a skin model. The numerical results demonstrate a change in the effective depth of measurement depending on the electrode topologies, which also have a good agreement with an analytic solution. This study suggests a decision guideline for designing the electrode topologies to achieve target depth sensitivity in bio-impedance measurement of skin tissue.Clinical Relevance-This establishes the effect of electrode topologies on depth sensitivity in bio-impedance measurements in skin layer.

Electrical Resistivity Tomography as a Support Tool for Physicochemical Properties Assessment of Near-Surface Waste Materials in a Mining Tailing Pond (El Gorguel, SE Spain)

The legacy of the mining industry has left a large number of tailing ponds in the Cartagena–La Unión mining district exposed to water and wind erosion, which causes serious environmental and health problems and requires remediation. Before applying any remediation technique, an intensive sampling of the materials infilling the pond is required to determine the geochemistry of the pond, which will condition the remediation process. However, sampling the large number of tailing ponds that compose the district could be expensive. Thus, the main objective of this study is to evaluate the usefulness of electrical resistivity tomography (ERT) as a non-invasive tool to provide an image of spatial subsurface resistivity distribution and its relation to the physicochemical composition of near-surface mine wastes. To achieve this objective, three short ERT profiles were conducted, and 12 samples in each profile were collected at different depths for its geochemical characterization. Several non-linear regression models were fitted to predict physicochemical properties and metal concentrations from electrical resistivity measures. As a result, a high resistivity area was depicted in the ERT profiles G2 and G3, while the low resistivity ERT profile G1 was also obtained in accordance with the site’s surficial characteristics. Relationships among low resistivity values and high salinity, clay content, high metal concentrations, and mobility were established. Specifically, calibrated models were obtained for electrical conductivity, particle sizes of 0.02–50 µm and 50–2000 µm, total Zn and Cd concentration, and bioavailable Ni, Cd, and Fe. The ERT technique was shown to be a useful tool for the approximation of the location and distribution of the highest ranges of fine particle sizes, moisture, and, to a lesser extent, metal accumulation in the near-surface waste materials.

Spatially resolved electrical impedance methods for cell and particle characterization

Electrical impedance is an established technique used for cell and particle characterization. The temporal and spectral resolution of electrical impedance have been used to resolve basic cell characteristics like size and type, as well as to determine cell viability and activity. Such electrical impedance measurements are typically performed across the entire sample volume and can only provide an overall indication concerning the properties and state of that sample. For the study of heterogeneous structures such as cell layers, biological tissue, or polydisperse particle mixtures, an overall measured impedance value can only provide limited information and can lead to data misinterpretation. For the investigation of localized sample properties in complex heterogeneous structures/mixtures, the addition of spatial resolution to impedance measurements is necessary. Several spatially resolved impedance measurement techniques have been developed and applied to cell and particle research, including electrical impedance tomography, scanning electrochemical microscopy, and microelectrode arrays. This review provides an overview of spatially resolved impedance measurement methods and assesses their applicability for cell and particle characterization.

Simulation of effects of the electrode structure and material in the density measuring system of the peripheral nerve based on micro-electrical impedance tomography

The electrode structure in micro-electrical impedance tomography (MEIT) highly influences the measurement sensitivity and therefore the reconstructed image quality. Hence, optimizing the electrode structure leads to the improvement of image quality in the reconstruction procedure. Although there have been many investigations on electrical impedance tomography (EIT) electrodes, there is no comprehensive study on their influence on images of the peripheral nerve. In this paper, we present a simulation method to study the effects of the electrode structure in the density measurement system of the peripheral nerve based on MEIT. The influence of the electrode structure such as dimensions, material and the number of electrodes and also the recognition feature of different radii of fascicle and different locations of fascicles has been studied. Data were reconstructed from the real and imaginary parts of complex conductivity data, respectively. It has been shown that the material of the electrodes had no effect on the reconstructed images, while the dimensions of the electrodes significantly affected the image sensitivity and thus the image quality. An increase in the number of electrodes increased the amount of data and information content. However, as the number of electrodes increased due to the given perimeter of the peripheral nerve, the area of the electrodes was reduced. This reduction affects the reconstructed image quality. The real and imaginary parts of the data were separately reconstructed for each case. Although, in real EIT systems, the reconstructed images using the real part of the signal have a better signal-to-noise ratio (SNR), this study proved that for a density measuring system of the peripheral nerve, the reconstructed images using the imaginary part of the signal had better quality. This simulation study proposes the effects of the electrode size and material and obtained spatial resolution that was high enough to reconstruct fascicles in a peripheral nerve.

Applications of Bioimpedance Measurement Techniques in Tissue Engineering

Rapid development in the field of tissue engineering necessitates implementation of monitoring methods for evaluation of the viability and characteristics of the cell cultures in a real-time, non-invasive and non-destructive manner. Current monitoring techniques are mainly histological and require labeling and involve destructive tests to characterize cell cultures. Bioimpedance measurement technique which benefits from measurement of electrical properties of the biological tissues, offers a non-invasive, label-free and real-time solution for monitoring tissue engineered constructs. This review outlines the fundamentals of bioimpedance, as well as electrical properties of the biological tissues, different types of cell culture constructs and possible electrode configuration set ups for performing bioimpedance measurements on these cell cultures. In addition, various bioimpedance measurement techniques and their applications in the field of tissue engineering are discussed.

Dosimetric Characteristics of an EMF Delivery System Based on a Real-Time Impedance Measurement Device

In this paper, the dosimetric characterization of an EMF exposure setup compatible with real-time impedance measurements of adherent biological cells is proposed. The EMF are directly delivered to the 16-well format plate used by the commercial xCELLigence apparatus. Experiments and numerical simulations were carried out for the dosimetric analysis. The reflection coefficient was less than -10 dB up to 180 MHz and this exposure system can be matched at higher frequencies up to 900 and 1800 MHz. The specific absorption rate (SAR) distribution within the wells containing the biological medium was calculated by numerical finite-difference time domain simulations and results were verified by temperature measurements at 13.56 MHz. Numerical SAR values were obtained at the microelectrode level where the biological cells were exposed to EMF including 13.56, 900, and 1800 MHz. At 13.56 MHz, the SAR values, within the cell layer and the 270-μL volume of medium, are 1.9e3 and 3.5 W/kg/incident mW, respectively.

Bioelectrical Impedance Methods for Noninvasive Health Monitoring: A Review

Under the alternating electrical excitation, biological tissues produce a complex electrical impedance which depends on tissue composition, structures, health status, and applied signal frequency, and hence the bioelectrical impedance methods can be utilized for noninvasive tissue characterization. As the impedance responses of these tissue parameters vary with frequencies of the applied signal, the impedance analysis conducted over a wide frequency band provides more information about the tissue interiors which help us to better understand the biological tissues anatomy, physiology, and pathology. Over past few decades, a number of impedance based noninvasive tissue characterization techniques such as bioelectrical impedance analysis (BIA), electrical impedance spectroscopy (EIS), electrical impedance plethysmography (IPG), impedance cardiography (ICG), and electrical impedance tomography (EIT) have been proposed and a lot of research works have been conducted on these methods for noninvasive tissue characterization and disease diagnosis. In this paper BIA, EIS, IPG, ICG, and EIT techniques and their applications in different fields have been reviewed and technical perspective of these impedance methods has been presented. The working principles, applications, merits, and demerits of these methods has been discussed in detail along with their other technical issues followed by present status and future trends.

Design of a microscopic electrical impedance tomography system using two current injections

We describe a novel design of a microscopic electrical impedance tomography (micro-EIT) system for long-term noninvasive monitoring of cell or tissue cultures. The core of the micro-EIT system is a sample container including two pairs of current-injection electrodes and 360 voltage-sensing electrodes. In designing the container, we took advantage of a hexagonal structure with fixed dimensions and electrode configuration. This eliminated technical difficulties related to the unknown irregular boundary geometry of an imaging object in conventional medical EIT. Attaching a pair of large current-injection electrodes fully covering the left and right sides of the hexagonal container, we generated uniform parallel current density inside the container filled with saline. The 360 voltage-sensing electrodes were placed on the front, bottom and back sides of the hexagonal container in three sets of 8 × 15 arrays with equal gaps between them. We measured voltage differences between all neighboring pairs along the direction of the parallel current pathway. For the homogeneous container, all measured voltages must be the same since the voltage changes linearly along that direction. Any anomaly in the container perturbed the current pathways and therefore equipotential lines to produce different differential voltage data. For conductivity image reconstructions, we adopted a lately developed image reconstruction algorithm for this electrode configuration to first produce projected conductivity images on the front, bottom and back sides. Using a backprojection method, we reconstructed three-dimensional conductivity images from those projection images. To improve the image quality and also to meet the mathematical requirement on the uniqueness of a reconstructed image, we used a second pair of thin and long current-injection electrodes located at the middle of the front and back sides. This paper describes the design and construction of such a micro-EIT system with experimental results. Proposing the novel micro-EIT system design, we suggest future studies of miniaturizing the sample container for true microscopic conductivity imaging of cell or tissue cultures.