FEM electrode refinement for electrical impedance tomography

Electrical Impedance Tomography (EIT) reconstructs images of electrical tissue properties within a body from electrical transfer impedance measurements at surface electrodes. Reconstruction of EIT images requires the solution of an inverse problem in soft field tomography, where a sensitivity matrix, J, of the relationship between internal changes and measurements is calculated, and then a pseudo-inverse of J is used to update the image estimate. It is therefore clear that a precise calculation of J is required for solution accuracy. Since it is generally not possible to use analytic solutions, the finite element method (FEM) is typically used. It has generally been recommended in the EIT literature that FEMs be refined near electrodes, since the electric field and sensitivity is largest there. In this paper we analyze the accuracy requirement for FEM refinement near electrodes in EIT and describe a technique to refine arbitrary FEMs

3D EIT image reconstruction with GREIT

Most applications of thoracic EIT use a single plane of electrodes on the chest from which a transverse image 'slice' is calculated. However, interpretation of EIT images is made difficult by the large region above and below the electrode plane to which EIT is sensitive. Volumetric EIT images using two (or more) electrode planes should help compensate, but are little used currently. The Graz consensus reconstruction algorithm for EIT (GREIT) has become popular in lung EIT. One shortcoming of the original formulation of GREIT is its restriction to reconstruction onto a 2D planar image. We present an extension of the GREIT algorithm to 3D and develop open-source tools to evaluate its performance as a function of the choice of stimulation and measurement pattern. Results show 3D GREIT using two electrode layers has significantly more uniform sensitivity profiles through the chest region. Overall, the advantages of 3D EIT are compelling

A virtual reality wheelchair driving simulator for use with a brain-computer interface

For patients with extensive paralysis, autonomous control of an electric powered wheelchair (EPW) is very difficult. Recent developments in brain-computer interfaces (BCI) suggest that BCI systems could provide an effective strategy for wheelchair control. Our goal is to build a BCI-controlled EPW to provide paralysed subjects with a means of autonomous mobility. This requires a safe testbed on which trials and user training are conducted. This paper presents an extendible virtual environment simulator of an EPW to fulfil that purpose. It combines the features of simulators used in robotics with those built for training and evaluation of prospective wheelchair users

Simultaneous Color Imaging and Fluorescence Detection using a Single Camera Sensor

We demonstrate an imaging system intended for medical applications that allows to display simultaneously and in real-time both the reflectance image as well as the signal from up to three fluorescent dyes

Catalistic Role of Legal Assistance between Formal Law and Social Norms : Hints from Japanese Assistance

Introduction: Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited. Methods: We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data. Results and Conclusions: Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT

A novel method for monitoring data quality in electrical impedance tomography

Electrical impedance tomography (EIT) has the promise to help improve care for patients undergoing ventilation therapy by providing real-time bed-side information on the distribution of ventilation in their lungs. To realise this potential, it is important for an EIT system to provide a reliable and meaningful signal at all times, or alert clinicians when this is not possible. Because the reconstructed images in EIT are sensitive to system instabilities (including electrode con

Evaluation and real-time monitoring of data quality in electrical impedance tomography

Electrical impedance tomography (EIT) is a noninvasive method to image conductivity distributions within a body. One promising application of EIT is to monitor ventilation in patients as a real-time bedside tool. Thus, it is essential that an EIT system reliably provide meaningful information, or alert clinicians when this is impossible. Because the reconstructed images are very sensitive to system instabilities (primarily from electrode connection variability and movement), EIT systems should continuously monitor and, if possible, correct for such errors. Motivated by this requirement, we describe a novel approach to quantitatively measure EIT data quality. Our goals are to define the requirements of a data quality metric, develop a metric q which meets these requirements, and an efficient way to calculate it. The developed metric q was validated using data from saline tank experiments and a retrospective clinical study. Additionally, we show that q may be used to compare the performance of EIT systems using phantom measurements. Results suggest that the calculated metric reflects well the quality of reconstructed EIT images for both phantom and clinical data. The proposed measure can thus be used for real-time assessment of EIT data quality and, hence, to indicate the reliability of any derived physiological information

Thoracic EIT in 3D: Experiences and recommendations

Objective: In EIT applications to the thorax, a single electrode plane has typically been used to reconstruct a transverse 2D 'slice'. However, such images can be misleading as EIT is sensitive to contrasts above and below the electrode plane, and ventilation and aeration inhomogeneities can be distributed in complex ways. Using two (or more) electrode planes, 3D EIT images may be reconstructed, but 3D reconstructions are currently little used in thoracic EIT. In this paper, we investigate an incremental pathway towards 3D EIT reconstructions, using two electrode planes to calculate improved transverse slices as an intermediate step. We recommend a specific placement of electrode planes, and further demonstrate the feasibility of multi-slice reconstruction in two species. Approach: Simulations of the forward and reconstructed sensitivities were analysed for two electrode planes using a 'square' pattern of electrode placement as a function of two variables: the stimulation and measurement 'skip', and the electrode plane separation. Next, single- versus two-plane measurements were compared in a horse and in human volunteers. We further show the feasibility of 3D reconstructions by reconstructing multiple transverse and, unusually, frontal slices during ventilation. Main results: Using two electrode planes leads to a reduced position error and improvement in off-plane contrast rejection. 2D reconstructions from two-plane measurements showed better separation of lungs, as compared to the single plane measurements which tend to push contrasts in the center of the image. 3D reconstructions of the same data show anatomically plausible images, inside as well as outside the volume between the two electrode planes. Significance: Based on the results, we recommend EIT electrode planes separated by less than half of the minimum thoracic dimension with a 'skip 4' pattern and 'square' placement to produce images with good slice selectivity