Electricalimpedancetomography (EIT) shares the same concepts as ERT. Although the imaged property remains the same (resistivity, or its inverse conductivity), EIT injects an alternating current rather than a direct current. his provides extra versatility as it can exploit diferent modalities (time diference, frequency difer- ence, multi-frequency) and expands the opportunities to characterise plant-soil interactions. he conduction of current in RSAs depends highly on the characteristics of the AC injected with the potential to better discriminate between soil and root tissues. Recent advances in this area [28, 36], show that the use of spectral EIT in com- bination with induced polarisation techniques are capa- ble of discerning the presence of high-density roots and some physiological processes. Moreover, studies such as , show the capability of EIT to identify the pres- ence of pathogenic agents in trees. his ield is still under continuous development, and new approaches are being established. For instance, Rao et al.  suggest a com- bined use of ERT and plant-water-low models to further understand their pedophysical interactions with soil.
ElectricalImpedanceTomography (EIT) is a non-invasive, portable and low-cost medical imaging technique. Different current patterns are injected to the surface of a conductive body and the corresponding voltages are measured also on the boundary. These mea- surements are the data used to infer the interior conductivity distribution of the object. However, it is well known that the reconstruction process is extremely ill-posed due to the low sensitivity of the boundary voltages to changes in the interior conductivity distribution. The reconstructed images also suffer from poor spatial resolution. In tomographic systems, the spatial resolution is related to the number of applied current patterns and to the number and positions of electrodes which are placed at the surface of the object under examination. Two mammographic sensors were recently developed at the University of Mainz in collaboration with Oxford Brookes University. These prototypes consist of a planar sensing head of circular geometry with twelve large outer (active) electrodes arranged on a ring of radius 4.4cm where the external currents are injected and a set of, respectively thirty six and fifty four point-like high-impedance inner (passive) electrodes arranged in a hexagonal pattern where the induced voltages are measured. Two 2D reconstruction methods were proposed for these devices, one based on resistor network models and another one which uses an integral equation formulation. The novelty of the device and hence of these imaging techniques consists exactly in the distinct use of active and passive electrodes.
In this work, EIT was undertaken using epicortical electrode arrays, placed over S1 in the anesthetized rat during evoked activity. The activ- ity was induced using a piezoelectric stimulator, by 1 Hz mechanical dis- placement of diagonally adjacent groups of whiskers tied together: 1) δ , γ , E1, and D1, or 2) D2, C2, D3 and C3 (Diamond et al., 2008). Both groups were stimulated separately, twice in 4 rats, which yielded 16 image sets. EIT arrays comprised 30 platinized, stainless-steel electrodes embedded in silicone, with contacts 0.6 mm in diameter and centers off- set in a triangular pattern 1.2 mm apart. The array was placed on the left cerebral hemisphere and centered upon the posteriomedial barrel sub ﬁ eld (PMBSF); the location of the PMBSF was determined prior to electrode placement using intrinsic signal optical imaging (ISOI). A 16-contact single shank LFP electrode array was placed in the center of the EIT electrode array. For EIT recordings, a sine-wave current (1.7 kHz and 50 μ A) was injected through a single electrode pair at a time and the resultant voltages were recorded (Fig. 1A). The signal was ﬁ ltered and demodulated with a bandwidth of ± 500 Hz, which gave a temporal resolution of 2 ms, to yield the evoked potentials (EPs) and the impedance change ( δ Z; Fig. 1B). The current injection pair was switched, using a multiplexer, every 15 s. This was repeated over 30 different electrode pairs in an expanding spiral pattern around the center of the array (Fig. 1C). Each complete image data set took c. 15 min. Data within each 15 s trial were averaged. The resulting c. 900 voltages were processed and used to produce images (Fig. 1D – E). LFP and EIT data were recorded simultaneously.
ElectricalImpedanceTomography(EIT) is a non-invasive imaging technique which aims to provide the cross- sectional distribution of electricalimpedance inside the human body. In EIT, we attach surface electrodes (typically 8 to 256) on the boundary of the subject, inject linearly independent patterns of sinusoidal currents in the frequency range of 50Hz to 500kHz, and measure the induced complex voltages. Since the relationship between the applied current and the resulting voltage data provide the electrical propensity of the subject, we use all available distributed current patterns and the measured voltage data set to reconstruct cross-sectional images of the conductivity and/or permittivity distribution inside the subject. This EIT technique has received considerable attention over the past two decades. Several review papers describe numerous aspects of the EIT technique [5, 8, 24, 29, 37], and mathematical theory was developed to support EIT system [1, 10, 16, 23, 26, 27, 34–36].
This article is dedicated to the current state of electricalimpedancetomography in medicine. The basic directions of research in this area have been detected. Possible areas of application in clinical conditions have been considered. The main manufacturers of electricalimpedance equipment in Russia and abroad have been presented. A list of main dissertations in the Russian Federation on the subject of electricalimpedancetomography since 2009 has been presented. Main scientific publications have been presented that publish results of leading groups of researchers. Based on the review and analysis of the subject area, a new approach to the theory of electricalimpedancetomography has been proposed.
Breast imaging together with other more advanced complementary methods focuses on improving early detection of the cancer cells and reduces the occurrence of missed cancers (Houssami et al. 2009). One suggested method is electricalimpedancetomography (EIT). A potentially, new noninvasive diagnostic technique based on different electrical storage potential of normal and pathologically altered tissues allowing image differences in the tissue conductivity and permittivity inferred from the body surface electrical measurements. EIT consists of a hand-held scanning probe and a computer screen that displays two-dimensional images of the breast. The EIT examination is performed with the subject recumbent, with both arms raised above the head. The purpose of this position is to flatten the breast as much as possible, allowing optimal contact of the flat surface of
Fig 1 shows EIT Experimental set up. It includes signal generator, a voltage to current converter producing a current of 20 mA at 5 KHz, a closed phantom with 16 electrode set up and a multimeter to measure resulting differential voltages . This paper gives description of experiments performed on 16 gold plated silver electrodes, plastic container of 14cm diameter and 7cm height filled with saline solution of 0.9% of sodium chloride having electrical conductivity of 300 ms/m. The low magnitude and low frequency sinusoidal current is applied to the pair of electrodes. Current can be applied in neighboring pattern, opposite pattern, cross pattern and adaptive pattern [12, 13]. The neighboring pattern is also known as adjacent pattern. Brown and Segar (1987)  suggested a method where current is applied to a pair of electrodes and voltage is measured from other noncurrent pair of electrodes.
Electricalimpedancetomography (EIT) can provide images with well defined characteristics only when the full nonlinear reconstruction process is constrained by a property of the image such as its local smoothness, applied in parallel with the requirement to fit the data to within clearly defined statistical criteria (Blott et al 1998, 2000). The finite element forward solution is a significant part of the computational cost of such a reconstruction (Yorkey et al 1987, Johnson and MacLeod 1994). This cost grows quickly when the image is subdivided into smaller and smaller elements to obtain an image whose accuracy is governed by the quality of the input data alone and not by the choice of discretization.
Then, in 2006, through the path of relating (1) with a Vekua equation , K. Astala and L. Päivärinta  gave a positive answer for the two-dimensional ElectricalImpedanceTomography problem. And in 2007, V. Kravchenko and H. Oviedo  obtained what it could be considered the rst general solution of (1) in analytic form, employing elements of the Pseudoanalytic Function Theory  for a certain class of . Two years latter, adopting new results in Complex Analysis , it was possible to pose the general solution for the two- dimensional case of (1) in terms of Taylor series in formal powers, when is a separable-variables function .
Acute respiratory distress syndrome (ARDS) is a clinical entity that acutely affects the lung parenchyma, and is characterized by diffuse alveolar damage and increased pulmonary vascular permeability. Currently, computed tomography (CT) is commonly used for classifying and prognosticating ARDS. However, performing this examination in critically ill patients is complex, due to the need to transfer these patients to the CT room. Fortunately, new technologies have been developed that allow the monitoring of patients at the bedside. Electricalimpedancetomography (EIT) is a monitoring tool that allows one to evaluate at the bedside the distribution of pulmonary ventilation continuously, in real time, and which has proven to be useful in optimizing mechanical ventilation parameters in critically ill patients. Several clinical applications of EIT have been developed during the last years and the technique has been generating increasing interest among researchers. However, among clinicians, there is still a lack of knowledge regarding the technical principles of EIT and potential applications in ARDS patients. The aim of this review is to present the characteristics, technical concepts, and clinical applications of EIT, which may allow better monitoring of lung function during ARDS.
In order to meet the requirements of stability, accuracy, dynamic range and signal-to-noise ratio of excitation source, direct digital synthesis technology (DDS) is used to achieve a programmable excitation source . DDS module is built by DDS compiler in IP core. The fre- quency and the phase of the excitation current are deter- mined by two different control words separately, PINC and POFF. Phase incremental control word PINC and phase offset control word POFF are both set in DDS compiler. The frequency is determined by
Electricalimpedancetomography (EIT) reconstructs the internal impedance distribution of the body from electrical measurements on body surface. The algorithm research is one of the main problems of the EIT. This paper presents the MPSO-MNR Algorithm, which is formed by combining the Modified Particle Swarm Optimization (MPSO) with Modified Newton-Raphson algorithm (MNR), gives the reconstruction results of certain configurations and analyzes the influence of the noise on the MPSO-MNR algorithm in the EIT. The numerical results show that the MPSO-MNR algo- rithm can reconstruct the resistivity distribution within the certain iterations. With the moving of the target to the centre of 2-D solution domain and the increase of noise, the border of the reconstruction objects becomes vague, and the fit- ness value and the total error increase gradually.
Electricalimpedancetomography EIT is an imaging technique, still in development, in which an image of the conductivity of a transverse section of an object is in- ferred from electrical measurements performed using a series of electrodes placed on its surface [1,2]. Despite its benefits, the method has a major drawback, as its low spatial resolution hinders the characterization of the ac- tivity of regions according to their physiological origin in a dynamic image. This difficulty in the interpretation of images can be translated as an uncertainty in the identi- fication of pixels in both anatomical and functional terms. Important EIT studies focus on the acquisition and inter- pretation of thoracic images. During the cardio-respira- tory cycle, air and blood share the same compartment
Data collection is performed within an ongoing observational clinical study as part of the CRADL project. Infants with a body weight less than 600 g, postmenstrual age less than 25 weeks at inclusion, electrically active implants or those suffering from thorax skin lesions were excluded from the study. Informed written consent was obtained from the parents of the neonatal study participants. The raw EIT data were acquired by the CRADL study EIT device (Swisstom, AG, Landquart) with 32 textile electrodes at the frame rate of 48 Hz. This system is specially designed for infants who had thorax diameters as small as 17.5 cm [27, 28]. Current injections with amplitude of 3 mA rms at a frequency of 200 kHz were applied using a skip 4 injection pattern. The resulting voltage differences were measured by the remaining electrode pairs after each current injection, then DC and system related voltage changes were removed. The GREIT reconstruction algorithm  was then used to reconstruct the images. EIT image data were filtered using a bandpass filter with cut-off frequencies of 0.15 Hz and 1.8 Hz in order to remove cardiac related impedance changes.
In the phantom experiment, fruit and vegetable objects with frequency-depend- ent conductivities were used to mimic the properties of live tissues. The background medium was a mixture of 0.1% NaCl solution and pomelo granules, and the perturbation was a cucumber segment of diameter 2.5 cm and height 7 cm. Conductivity measure- ments were acquired with a Solartron 1294 impedance analyzer for 25 frequencies in the range 1–200 kHz using Ag–AgCl electrodes. This frequency range is consistent with our imaging system, FMMU-EIT5 . The cucumber was cut into 3 mm × 3 mm cubes for placement in the measurement box, which had a diameter of 1 cm and a height of 1.2 cm and was connected to the analyzer via a conductor. Three different samples were selected for each tissue, and measurements were made five times for each sample at room tem- perature. The conductivity was calculated using the specific calculation formula for this measurement box, and the final conductivity spectra were obtained by averaging.
Abstract– ElectricalImpedanceTomography (EIT), is one of the safest medical imaging technologies and can be used in industrial process monitoring. In this method, image of electrical conductivity (or electricalimpedance) distribution of the inner part of a conductive subject can be reconstructed. The image reconstruction process is done by injecting an accurate current into the boundary of a volume conductor (Ω), measuring voltages around the boundary (∂Ω) and transmitting them to a computer, and processing on acquired data with software (e.g. MATLAB). The image would be reconstructed from the measured peripheral data by using an iterative algorithm. A precise instrumentation (EIT hardware) plays a very important and vital role in the quality of reconstructed images. In this paper, we have proposed a practical design of a low-cost precise EIT hardware including, a high output impedance VCCS (Voltage-Controlled Current Source) with pulse generation part, precise voltage demodulator and measuring parts, a high performance multiplexer module, and a control unit. All the parts have been practically and accurately tested with successful results, and finally the proposed design was assembled on PCB. The quality of experimental results at the end of this paper, (reconstructed images by using the implemented system), confirms the accuracy of the proposed EIT hardware.
Borsic et al.  moved the forward and the Jacobian cal- culations (not the assembly of the system matrix, though) to sparse parallel direct solver library PARDISO  to surpass these limitations. They were able to improve the speed for for- ward simulations about 5.3 fold compared to Horesh et al. . They used it on meshes with around half a million elements. On larger meshes, direct solvers require large amounts of memory that normally limits the mesh size that can be computed. Fur- thermore, we show in this paper, that the assembly of the direct solver is much slower than that of a good preconditioner, result- ing in faster execution times for iterative methods depending on the number of unique current injection patterns. In particular, the algebraic multigrid preconditioner has been shown to im- prove the solution time significantly . Graphics processing unit (GPU) based computations have already successfully been applied to the calculation of the Jacobian matrix , where fast access to the memory is paramount. A different approach to the forward modeling in EIT was done by using boundary elements , a technique that requires the head to be modeled as en- closed surfaces of the different tissues with fixed conductivity.
The present work is restricted by different limitations of the bioimpedance model (as lis- ted in Section 4.4) such as the lack of respiration-related displacements and deformations. Incorporating those into the model might allow to obtain more detailed insights. Besides, posture-induced heart displacement, lung liquid distribution, pneumothorax or edema should be studied as they could be additional confounding factors for EIT based SV monitoring. Moreover, it needs to be stressed out that the exact origins of the EIT heart signal remain unclear and that ventricular SV is not the only signal contributor. There are other effects such as heart motion , flow-induced reorientation of red blood cells , myocardial anisotropy, etc. . If the magnitudes of the other contributors are strong and they do not change proportional to SV, the heart signal will not be a reliable source to estimate SV from. Even though we have only investigated a part of all possible confounding factors on a model with certain limitations, we believe to have revealed some important challenges for SV via EIT mostly due to belt displacements and the heart-lung-conductivity contrast.
Abstract: Basically, Electricalimpedancetomography is a new technique in monitoring and imaging cross sectional images and physical state of objects by measuring the internal impedance distribution. This paper presents the design of a microscopic electricalimpedancetomography system, which is a non-destructive approach that has the capability to interpret and analyze the internal impedance distribution of a medium (the system) and reconstruct its image as a tomogram, where any object inside the system can be shown in a 2D (two-dimension) image. A current source circuit was constructed and studied by injecting 5 mA of current to an array of electrodes (3*3 array). Moreover, the conditional measurement circuit is going to receive voltage from measurement electrodes array of 8*16 in each plane. The data was obtained from both planes as a matrix of 8*16 electrodes using multiplexers which was transferred serially to the PC to be analyzed and to reconstruct the image/tomogram. The image reconstruction process and algorithms were engaged in the calculation to reconstruct the image based on the voltage collected. Finally, interpolation is conducted to improve the quality and increase the resolution of the image.