Finite element modeling of electrode-skin contact impedance in electrical impedance tomography

Non-Invasive Detection of Early-Stage Fatty Liver Disease via an On-Skin Impedance Sensor and Attention-Based Deep Learning

Early-stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going undiagnosed, potentially progressing to liver cirrhosis and cancer. A non-invasive and cost-effective detection method for early-stage NAFLD detection is a public health priority but challenging. In this study, an adhesive, soft on-skin sensor with low electrode-skin contact impedance for early-stage NAFLD detection is fabricated. A method is developed to synthesize platinum nanoparticles and reduced graphene quantum dots onto the on-skin sensor to reduce electrode-skin contact impedance by increasing double-layer capacitance, thereby enhancing detection accuracy. Furthermore, an attention-based deep learning algorithm is introduced to differentiate impedance signals associated with early-stage NAFLD in high-fat-diet-fed low-density lipoprotein receptor knockout (Ldlr-/-) mice compared to healthy controls. The integration of an adhesive, soft on-skin sensor with low electrode-skin contact impedance and the attention-based deep learning algorithm significantly enhances the detection accuracy for early-stage NAFLD, achieving a rate above 97.5% with an area under the receiver operating characteristic curve (AUC) of 1.0. The findings present a non-invasive approach for early-stage NAFLD detection and display a strategy for improved early detection through on-skin electronics and deep learning.

Performance evaluation of electrode design and material for a large animal electrical impedance tomography belt

BACKGROUND

Electrical impedance tomography (EIT) produces lung ventilation images via a thoracic electrode belt. Robust electrode design and material, providing low electrode skin contact impedance (SCI), is needed in veterinary medicine. The aim of this study was to compare three EIT electrode designs and materials.

METHODS

Simulations of cylindrical, rectangular and spiked electrode designs were used to evaluate electrode SCI as a function of electrode size, where skin contact was uneven. Gold-plated washers (E_GW ), zinc-plated rivets (E_ZR ) and zinc-galvanised spikes (E_ZS ) were assigned randomly on two interconnected EIT belts. Gel was applied to the cranial or caudal belt and placed on 17 standing cattle. SCI was recorded at baseline and 3, 5, 7, 9 and 11 minutes later.

RESULTS

Simulations that involved electrodes with a greater skin contact area had lower and more uniform SCI. In cattle, SCI decreased with all electrodes over time (p < 0.01). Without gel, no difference was found between E_GW and E_ZS , while SCI was higher for E_ZR (p < 0.03). With gel, SCI was lower in E_GW and E_ZR (p < 0.026), with the SCI in E_GW being the lowest (p < 0.01).

LIMITATIONS

Low numbers of animals and static electrode position may affect SCI.

CONCLUSIONS

Electrode design is important for EIT measurement, with larger electrode designs able to compensate for the use of less conductive materials. Gel is not necessary to achieve acceptable SCI in large animals.

Improved resolution of D-bar images of ventilation using a Schur complement property and an anatomical atlas

BACKGROUND

Electrical impedance tomography (EIT) is a nonionizing imaging technique for real-time imaging of ventilation of patients with respiratory distress. Cross-sectional dynamic images are formed by reconstructing the conductivity distribution from measured voltage data arising from applied alternating currents on electrodes placed circumferentially around the chest. Since the conductivity of lung tissue depends on air content, blood flow, and the presence of pathology, the dynamic images provide regional information about ventilation, pulsatile perfusion, and abnormalities. However, due to the ill-posedness of the inverse conductivity problem, EIT images have a coarse spatial resolution. One method of improving the resolution is to include prior information in the reconstruction.

PURPOSE

In this work, we propose a technique in which a statistical prior built from an anatomical atlas is used to postprocess EIT reconstructions of human chest data. The effectiveness of the method is demonstrated on data from two patients with cystic fibrosis.

METHODS

A direct reconstruction algorithm known as the D-bar method was used to compute a two-dimensional reconstruction of the conductivity distribution in the plane of the electrodes. Reconstructions using one step in an iterative (regularized) Newton's method were also computed for comparison. An anatomical atlas consisting of 1589 synthetic EIT images computed from X-ray computed tomography (CT) scans of 74 adult male subjects was computed for use as a statistical prior. The resolution of the D-bar images was then improved by maximizing the conditional probability density function of an image that is consistent with the a priori information and the statistical model. A new method to evaluate the accuracy of the EIT images using CT scans of the imaged patient as ground truth is presented. The novel approach is tested on data from two patients with cystic fibrosis.

RESULTS AND CONCLUSIONS

The D-bar images resulted in better structural similarity index measures (SSIM) and multiscale (MS) SSIM measures for both subjects using the mask or amplitude evaluation approach than the one-step (regularized) Newton's method. Further improvement was achieved using the Schur complement (SC) approach, with MS-SSIM values of 0.718 and 0.682 using SC evaluated with the mask and amplitude approach, respectively, for Patient 1, and MS-SSIM values of 0.726 and 0.692 using SC evaluated with the mask and amplitude approach, respectively, for Patient 2. The results from applying an anatomical atlas and statistical prior to EIT data from two patients with cystic fibrosis suggest that the spatial resolution of the EIT image can be improved to reveal pathology that may be difficult to discern in the original EIT image. The novel metric of evaluation is consistent with the appearance of improved spatial resolution and provides a new way to evaluate the accuracy of EIT reconstructions when a CT scan is available.

Adjunctive Diagnostic Methods for Skin Cancer Detection: A Review of Electrical Impedance-Based Techniques

Skin cancer is among the fastest-growing cancers with an excellent prognosis, if detected early. However, the current method of diagnosis by visual inspection has several disadvantages such as overlapping tumor characteristics, subjectivity, low sensitivity, and specificity. Hence, several adjunctive diagnostic techniques such as thermal imaging, optical imaging, ultrasonography, tape stripping methods, and electrical impedance imaging are employed along with visual inspection to improve the diagnosis. Electrical impedance-based skin cancer detection depends upon the variations in electrical impedance characteristics of the transformed cells. The information provided by this technique is fundamentally different from other adjunctive techniques and thus has good prospects. Depending on the stage, type, and location of skin cancer, various impedance-based devices have been developed. These devices when used as an adjunct to visual methods have increased the sensitivity and specificity of skin cancer detection up to 100% and 87%, respectively, thus demonstrating their potential to minimize unnecessary biopsies. In this review, the authors track the advancements and progress made in this technique for the detection of skin cancer, focusing mainly on the advantages and limitations in the clinical setting. © 2022 Bioelectromagnetics Society.

Trends and recent development of the microelectrode arrays (MEAs)

In this paper, we reviewed the history of microelectrode arrays (MEAs), compared different microfabrication techniques applied to modern MEAs in terms of their material characters, device properties and application scenarios. Then we discussed the biocompatibility of different MEAs as well as corresponding strategy of improvement. At last, we analyzed the growing trend of MEAs' technical route, expected application of MEAs in the field of Electrical impedance tomography (EIT).

Modelling and analysis of electrical impedance myography of the lateral tongue

OBJECTIVE

Electrical impedance myography (EIM) performed on the centre of the tongue shows promise in detecting amyotrophic lateral sclerosis (ALS). Lateral recordings may improve diagnostic performance and provide pathophysiological insights through the assessment of asymmetry. However, it is not known if electrode proximity to the muscle edge, or electrode rotation, distort spectra. We evaluated this using finite element-based modelling.

APPROACH

Nine thousand EIM from patients and healthy volunteers were used to develop a finite element model for phase and magnitude. Simulations varied electrode proximity to the muscle edge and electrode rotation. LT-Spice simulations assessed disease effects. Patient data were assessed for reliability, agreement and classification performance.

MAIN RESULTS

No effect on phase spectra was seen if all electrodes remained in contact with the tissue. Small effects on magnitude were observed. Cole-Cole circuit simulations indicated capacitance reduced with disease severity. Lateral tongue muscle recordings in both patients and healthy volunteers were reproducible and symmetrical. Combined lateral/central tongue EIM improved disease classification compared to either placement alone.

SIGNIFICANCE

Lateral EIM tongue measurements using phase angle are feasible. Such measurements are reliable, find no evidence of tongue muscle asymmetry in ALS and improve disease classification. Lateral measurements enhance tongue EIM in ALS.

Role of skin tissue layers and ultra-structure in transcutaneous electrical stimulation including tDCS

BACKGROUND

During transcranial electrical stimulation (tES), including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), current density concentration around the electrode edges that is predicted by simplistic skin models does not match experimental observations of erythema, heating, or other adverse events. We hypothesized that enhancing models to include skin anatomical details, would alter predicted current patterns to align with experimental observations.

METHOD

We develop a high-resolution multi-layer skin model (epidermis, dermis, and fat), with or without additional ultra-structures (hair follicles, sweat glands, and blood vessels). Current flow patterns across each layer and within ultra-structures were predicted using finite element methods considering a broad range of modeled tissue parameters including 78 combinations of skin layer conductivities (S m^-1): epidermis (standard: 1.05 × 10^-5; range: 1.05 × 10^-6 to 0.465); dermis (standard: 0.23; range: 0.0023 to 23), fat (standard: 2 × 10^-4; range: 0.02 to 2 × 10^-5). The impact of each ultra-structures in isolation and combination was evaluated with varied basic geometries. An integrated final model is then developed.

RESULTS

Consistent with prior models, current flow through homogenous skin was annular (concentrated at the electrode edges). In multi-layer skin, reducing epidermis conductivity and/or increasing dermis conductivity decreased current near electrode edges, however no realistic tissue layer parameters produced non-annular current flow at both epidermis and dermis. Addition of just hair follicles, sweat glands, or blood vessels resulted in current peaks around each ultrastructure, irrespective of proximity to electrode edges. Addition of only sweat glands was the most effective approach in reducing overall current concentration near electrode edges. Representation of blood vessels resulted in a uniform current flow across the vascular network. Finally, we ran the first realistic model of current flow across the skin.

CONCLUSION

We confirm prior models exhibiting current concentration near hair follicles or sweat glands, but also exhibit that an overall annular pattern of current flow remains for realistic tissue parameters. We model skin blood vessels for the first time and show that this robustly distributes current across the vascular network, consistent with experimental erythema patterns. Only a state-of-the-art precise model of skin current flow predicts lack of current concentration near electrode edges across all skin layers.

Capacitively Coupled Electrical Impedance Tomography for Brain Imaging

Electrical impedance tomography (EIT) is considered as a potential candidate for brain stroke imaging due to its compactness and potential use in bedside and emergency settings. The electrode-skin contact impedance and low conductivity of skull pose some practical challenges to the EIT head imaging. This paper studies the application of capacitively coupled electrical impedance tomography (CCEIT) in brain imaging for the first time. CCEIT is a new contactless EIT technique which uses voltage excitation without direct contact with the skin, as oppose to directly injecting the current to the skin in EIT. Because the safety issue of a new technique should be strictly treated, simulation work based on a simplified head model was carried out to investigate the safety aspects of CCEIT. By comparing with the standard EIT excited by a typical safe current level used in brain imaging, the safe excitation reference of CCEIT is obtained. This is done by comparing the maximum level of internal electrical field (internal current density) of EIT and that of CCEIT. Simulation results provide useful knowledge of excitation signal level of CCEIT and also show a critical comparison with traditional EIT. Practical experiments were carried out with a 12-electrode CCEIT phantom, saline, and carrot samples. Experimental results show the feasibility and potential of CCEIT for stroke imaging. In this paper, the anomaly diameter resolution is 10 mm (1/18 of the phantom diameter), which indicates that small-volume stroke could be detected. This is achieved by a low excitation voltage of 1 V, showing the possibility of even better performance when higher but yet safe level of excitation voltages is used.

Effect of electrode geometry on the electrolyte resistance measurement over the surface of a skin phantom in a noninvasive manner

We analyzed the electrode geometry to obtain the potential (E) and current density (J) distributions at the surface of a skin phantom (SP), in this case a planar surface. Two electrode geometries were tested: a circular electrode (CiE) and a rectangular electrode (ReE). First, by a finite element simulation, we calculated the E and J distributions at the surface of the SP. Second, we determined the resistivity properties as a function of the electrochemical impedance. Three- and four-electrode configurations were used to measure the E versus distance between the reference electrodes (d). For the ReE, the electrolyte resistance (R_e) measurements show a linear behavior with respect to "d" if the zone of the linear distribution of E and the homogeneous current density (J_H) is considered. In contrast, the CiE shows nonlinear behavior due to the absence of that zone of the linear distribution of E and J_H in the entire range. For ReE, we deduced that the behavior of R_e versus "d" is related to the material resistivity. Consequently, the ReE geometry improves the R_e measurements on the surface and shows us a way to control the behavior of this element in planar samples such as skin.

A Review of Electrical Impedance Tomography in Lung Applications: Theory and Algorithms for Absolute Images

Electrical Impedance Tomography (EIT) is under fast development, the present paper is a review of some procedures that are contributing to improve spatial resolution and material properties accuracy, admitivitty or impeditivity accuracy. A review of EIT medical applications is presented and they were classified into three broad categories: ARDS patients, obstructive lung diseases and perioperative patients. The use of absolute EIT image may enable the assessment of absolute lung volume, which may significantly improve the clinical acceptance of EIT. The Control Theory, the State Observers more specifically, have a developed theory that can be used for the design and operation of EIT devices. Electrode placement, current injection strategy and electrode electric potential measurements strategy should maximize the number of observable and controllable directions of the state vector space. A non-linear stochastic state observer, the Unscented Kalman Filter, is used directly for the reconstruction of absolute EIT images. Historically, difference images were explored first since they are more stable in the presence of modelling errors. Absolute images require more detailed models of contact impedance, stray capacitance and properly refined finite element mesh where the electric potential gradient is high. Parallelization of the forward program computation is necessary since the solution of the inverse problem often requires frequent solutions of the forward problem. Several reconstruction algorithms benefit by the Bayesian inverse problem approach and the concept of prior information. Anatomic and physiologic information are used to form the prior information. An already tested methodology is presented to build the prior probability density function using an ensemble of CT scans and in vivo impedance measurements. Eight absolute EIT image algorithms are presented.

The Frequency Spectral Properties of Electrode-Skin Contact Impedance on Human Head and Its Frequency-Dependent Effects on Frequency-Difference EIT in Stroke Detection from 10Hz to 1MHz

Frequency-difference electrical impedance tomography (fdEIT) reconstructs frequency-dependent changes of a complex impedance distribution. It has a potential application in acute stroke detection because there are significant differences in impedance spectra between stroke lesions and normal brain tissues. However, fdEIT suffers from the influences of electrode-skin contact impedance since contact impedance varies greatly with frequency. When using fdEIT to detect stroke, it is critical to know the degree of measurement errors or image artifacts caused by contact impedance. To our knowledge, no study has systematically investigated the frequency spectral properties of electrode-skin contact impedance on human head and its frequency-dependent effects on fdEIT used in stroke detection within a wide frequency band (10 Hz-1 MHz). In this study, we first measured and analyzed the frequency spectral properties of electrode-skin contact impedance on 47 human subjects’ heads within 10 Hz-1 MHz. Then, we quantified the frequency-dependent effects of contact impedance on fdEIT in stroke detection in terms of the current distribution beneath the electrodes and the contact impedance imbalance between two measuring electrodes. The results showed that the contact impedance at high frequencies (>100 kHz) significantly changed the current distribution beneath the electrode, leading to nonnegligible errors in boundary voltages and artifacts in reconstructed images. The contact impedance imbalance at low frequencies (<1 kHz) also caused significant measurement errors. We conclude that the contact impedance has critical frequency-dependent influences on fdEIT and further studies on reducing such influences are necessary to improve the application of fdEIT in stroke detection.

Efficient Simultaneous Reconstruction of Time-Varying Images and Electrode Contact Impedances in Electrical Impedance Tomography

OBJECTIVE

In electrical impedance tomography (EIT), we apply patterns of currents on a set of electrodes at the external boundary of an object, measure the resulting potentials at the electrodes, and, given the aggregate dataset, reconstruct the complex conductivity and permittivity within the object. It is possible to maximize sensitivity to internal conductivity changes by simultaneously applying currents and measuring potentials on all electrodes but this approach also maximizes sensitivity to changes in impedance at the interface.

METHODS

We have, therefore, developed algorithms to assess contact impedance changes at the interface as well as to efficiently and simultaneously reconstruct internal conductivity/permittivity changes within the body. We use simple linear algebraic manipulations, the generalized singular value decomposition, and a dual-mesh finite-element-based framework to reconstruct images in real time. We are also able to efficiently compute the linearized reconstruction for a wide range of regularization parameters and to compute both the generalized cross-validation parameter as well as the L-curve, objective approaches to determining the optimal regularization parameter, in a similarly efficient manner.

RESULTS

Results are shown using data from a normal subject and from a clinical intensive care unit patient, both acquired with the GE GENESIS prototype EIT system, demonstrating significantly reduced boundary artifacts due to electrode drift and motion artifact.

Electro-resistive bands for non-invasive cardiac and respiration monitoring, a feasibility study

Continuous unobtrusive monitoring of tidal volume, particularly for critical care patients (i.e. neonates and patients in intensive care) during sleep studies and during daily activities, is still an unresolved monitoring need. Also a successful monitoring solution is yet to be proposed for continuous non-invasive cardiac stroke volume monitoring that is a novel clinical need.In this paper we present the feasibility study for a wearable, non-invasive, non-contact and unobtrusive sensor (embedded in a standard T-shirt) based on four electro-resistive bands that simultaneously monitors tidal volume and cardiac stroke volume changes. This low power sensor system (requires only 100 mW and accepts a wide power supply range up to ±18 V); thus the sensor can be easily embedded in existing wearable solutions (i.e. Holter monitors). Moreover, being contactless, it can be worn over bandages or electrodes, and as it does not rely over the integrity of the garment to work, it allows practitioners to perform procedures during monitoring. For this preliminary evaluation, one subject has worn the sensor over the period of 24 h (removing it only to shower); the accuracy of the tidal volume tested against a portable spirometer reported a precision of ±10% also during physical activity; accuracy tests for cardiac output (as it may require invasive procedure) have not been carried out in this preliminary trial.

A pipeline for the simulation of transcranial direct current stimulation for realistic human head models using SCIRun/BioMesh3D

The current work presents a computational pipeline to simulate transcranial direct current stimulation from image based models of the head with SCIRun [15]. The pipeline contains all the steps necessary to carry out the simulations and is supported by a complete suite of open source software tools: image visualization, segmentation, mesh generation, tDCS electrode generation and efficient tDCS forward simulation.

Peripheral nerve stimulation in regional anesthesia

Peripheral nerve stimulation has a long history in regional anesthesia. Despite the advent of ultrasound-guided peripheral nerve blockade, nerve stimulation remains a popular technique used alone or, now, in combination with ultrasound-guided techniques. In light of this evolving utility of nerve stimulation, this is an appropriate time to review the basic concepts and knowledge base of this historically important tool. Electrical nerve stimulation facilitates nerve localization, using threshold current as a surrogate for needle-to-nerve distance. Preferential activation of motor nerves is possible because motor nerve fibers are more readily activated with a shorter duration of current compared with sensory nerves. The association between current and needle-to-nerve distance predicts that less current is needed to evoke a motor response as the needle moves closer to the nerve. Thus, an elicited motor response at or below 0.5 mA is considered a common end point for successful neural blockade. However, current magnitude is neither 100% sensitive nor specific. Independent of technical ability, both the biological environment and the equipment used impact the current-distance relationship. Thus, successful electrical nerve stimulation is dependent on an anesthesiologist with a solid foundation in anatomy and a thorough understanding of electrophysiology.

Image reconstruction using interval simulated annealing in electrical impedance tomography

Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.

A new method for non-invasive measurement of skin in the low frequency range

OBJECTIVES

The purpose of our study was to estimate skin structure and conductivity distribution in a cross section of local tissue using non-invasive measurement of impedance data. The present study was designed to evaluate the efficiency of skin depth information through computer simulations. The multilayer tissue model was composed of epidermis, dermis tissues, and subcutaneous.

METHODS

In this study, electrical characteristics of skin models were used for conductivity of 0.13 S/m, 0.26 S/m, 0.52 S/m, permittivity of 94,000 F/m, and a frequency of 200 Hz. The effect of the new method was assessed by computer simulations using three-electrode methods. A non-invasive electrical impedance method has been developed for analysis using computer simulation and a skin electrical model with low frequency range. Using the three-electrode method differences through the potentials between measurement electrodes and reference electrodes can be easily detected. The Cole electrical impedance model, which is better suited for skin was used in this study.

RESULTS

In this study, experiments using three-electrode methods were described by computer simulation based on a simple model. This electrical impedance model was fitted and developed in comparison with our model for measurement of skin impedance.

CONCLUSIONS

The proposed electrical model for skin is suitable for use in interpretation of changes in impedance characterization of the skin. Using the computer simulation method, information on skin impedance depth can be more accurately developed and predicted.

Adaptive mesh refinement techniques for 3-D skin electrode modeling

In this paper, we develop a 3-D adaptive mesh refinement technique. The algorithm is constructed with an electric impedance tomography forward problem and the finite-element method in mind, but is applicable to a much wider class of problems. We use the method to evaluate the distribution of currents injected into a model of a human body through skin contact electrodes. We demonstrate that the technique leads to a significantly improved solution, particularly near the electrodes. We discuss error estimation, efficiency, and quality of the refinement algorithm and methods that allow for preserving mesh attributes in the refinement process.

Dynamic imaging in electrical impedance tomography of the human chest with online transition matrix identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

Design of electrodes and current limits for low frequency electrical impedance tomography of the brain

For the novel application of recording of resistivity changes related to neuronal depolarization in the brain with electrical impedance tomography, optimal recording is with applied currents below 100 Hz, which might cause neural stimulation of skin or underlying brain. The purpose of this work was to develop a method for application of low frequency currents to the scalp, which delivered the maximum current without significant stimulation of skin or underlying brain. We propose a recessed electrode design which enabled current injection with an acceptable skin sensation to be increased from 100 muA using EEG electrodes, to 1 mA in 16 normal volunteers. The effect of current delivered to the brain was assessed with an anatomically realistic finite element model of the adult head. The modelled peak cerebral current density was 0.3 A/m(2), which was 5 to 25-fold less than the threshold for stimulation of the brain estimated from literature review.

Electrical impedance tomography using the extended Kalman filter

In this paper, we propose an algorithm that, using the extended Kalman filter, solves the inverse problem of estimating the conductivity/resistivity distribution in electrical impedance tomography (EIT). The algorithm estimates conductivity/resistivity in a wide range. The purpose of this investigation is to provide information for setting and controlling air volume and pressure delivered to patients under artificial ventilation. We show that, when the standard deviation of the measurement noise level raises up to 5% of the maximal measured voltage, the conductivity estimates converge to the expected vector within 7% accuracy of the maximal conductivity value, under numerical simulations, with spatial a priori information. A two-phase identification procedure is proposed. A cylindrical phantom with saline solution is used for experimental evaluation. An abrupt modification on the resistivity distribution of this solution is caused by the immersion of a glass object. Estimates of electrode contact impedances and images of the glass object are presented.

Three-dimensional electrical impedance tomography based on the complete electrode model

In electrical impedance tomography an approximation for the internal resistivity distribution is computed based on the knowledge of the injected currents and measured voltages on the surface of the body. It is often assumed that the injected currents are confined to the two-dimensional (2-D) electrode plane and the reconstruction is based on 2-D assumptions. However, the currents spread out in three dimensions and, therefore, off-plane structures have significant effect on the reconstructed images. In this paper we propose a finite element-based method for the reconstruction of three-dimensional resistivity distributions. The proposed method is based on the so-called complete electrode model that takes into account the presence of the electrodes and the contact impedances. Both the forward and the inverse problems are discussed and results from static and dynamic (difference) reconstructions with real measurement data are given. It is shown that in phantom experiments with accurate finite element computations it is possible to obtain static images that are comparable with difference images that are reconstructed from the same object with the empty (saline filled) tank as a reference.

Tikhonov regularization and prior information in electrical impedance tomography

The solution of impedance distribution in electrical impedance tomography is a nonlinear inverse problem that requires the use of a regularization method. The generalized Tikhonov regularization methods have been popular in the solution of many inverse problems. The regularization matrices that are usually used with the Tikhonov method are more or less ad hoc and the implicit prior assumptions are, thus, in many cases inappropriate. In this paper, we propose an approach to the construction of the regularization matrix that conforms to the prior assumptions on the impedance distribution. The approach is based on the construction of an approximating subspace for the expected impedance distributions. It is shown by simulations that the reconstructions obtained with the proposed method are better than with two other schemes of the same type when the prior is compatible with the true object. On the other hand, when the prior is incompatible with the true object, the method will still give reasonable estimates.

Monitoring cellular edema at single-neuron level by electrical resistance measurements

Electrical resistance measurements have been used for investigating extracellular volume fraction (EVF) of brain tissue. Conventional techniques using multiple metal electrodes are limited in their spatial resolution, and thus not suitable for detecting local EVF changes at cellular level. We used a multibarrelled glass microelectrode to monitor cellular swelling locally at single-neuron level. The microelectrode was placed in CA1 region of the rat hippocampus, in situ. A constant current pulse was applied between one of the barrels and a reference electrode placed in the neck. The resultant voltage drop, which was directly proportional to the resistance of the immediate environment surrounding the tip of the microelectrode, was recorded through another barrel. A third barrel was used for iontophoretic injection of N-methyl-D-aspartate (NMDA) for inducing local cellular edema. The effect of diffuse edema induced by bilateral carotid artery ligation on EVF was also investigated. NMDA application increased the local tissue resistance by 2.0-, and ischemia, by 3.4-folds. We conclude that the method described can detect changes in EVF of minute volumes of brain tissue, and is suitable for monitoring very local effects of drugs or changes in the metabolism on cell volume.

Linearity of transthoracic conductance with respect to electrode force and area during high-voltage defibrillation shocks

Canine transthoracic conductance (GT) was measured during high-voltage defibrillation shocks to test the hypothesis that (GT) is a linear function of electrode force (F) and electrode area (A). Symmetric protocols were used to compensate for changes in (GT) with respect to shock number (n). Stainless steel electrodes were employed with a force-control system for precise selection and control of both F and A at each shock. For a constant A = 60 cm2, GT was linear (r = 0.996, 0.995, 0.971, 0.992, 0.995) over five dogs for 30 N < or = F < or = 70 N. For a constant F = 50 N, GT was linear (r = 0.992, 0.998, 0.994, 0.992) over four dogs for 20 cm2 < or = A < or = 60 cm2, and in one dog (r = 0.996) for 40 cm2 < or = A < or = 90 cm2. The quantitative relationship demonstrated for GT and F and A can be used in the design of experiments and interpretation of results used for validation of numerical defibrillation models.