Evaluation of EIT system performance

Sensitivity volume as figure-of-merit for maximizing data importance in electrical impedance tomography

Objective.Electrical impedance tomography (EIT) is a noninvasive imaging method whereby electrical measurements on the periphery of a heterogeneous conductor are inverted to map its internal conductivity. The EIT method proposed here aims to improve computational speed and noise tolerance by introducing sensitivity volume as a figure-of-merit for comparing EIT measurement protocols.Approach.Each measurement is shown to correspond to a sensitivity vector in model space, such that the set of measurements, in turn, corresponds to a set of vectors that subtend a sensitivity volume in model space. A maximal sensitivity volume identifies the measurement protocol with the greatest sensitivity and greatest mutual orthogonality. A distinguishability criterion is generalized to quantify the increased noise tolerance of high sensitivity measurements.Main result.The sensitivity volume method allows the model space dimension to be minimized to match that of the data space, and the data importance to be increased within an expanded space of measurements defined by an increased number of contacts.Significance.The reduction in model space dimension is shown to increasecomputational efficiency, accelerating tomographic inversion by several orders of magnitude, while the enhanced sensitivitytolerates higher noiselevels up to several orders of magnitude larger than standard methods.

Machine learning-enhanced gesture recognition through impedance signal analysis

Gesture recognition is a crucial aspect in the advancement of virtual reality, healthcare, and human-computer interaction, and requires innovative methodologies to meet the increasing demands for precision. This paper presents a novel approach that combines Impedance Signal Spectrum Analysis (ISSA) with machine learning to improve gesture recognition precision. A diverse dataset that included participants from various demographic backgrounds (five individuals) who were each executing a range of predefined gestures. The predefined gestures were designed to encompass a broad spectrum of hand movements, including intricate and subtle variations, to challenge the robustness of the proposed methodology. The machine learning model using the K-Nearest Neighbors (KNN), Gradient Boosting Machine (GBM), Naive Bayes (NB), Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM) algorithms demonstrated notable precision in performance evaluations. The individual accuracy values for each algorithm are as follows: KNN, 86%; GBM, 86%; NB, 84%; LR, 89%; RF, 87%; and SVM, 87%. These results emphasize the importance of impedance features in the refinement of gesture recognition. The adaptability of the model was confirmed under different conditions, highlighting its broad applicability.

Towards continuous EIT monitoring for hemorrhagic stroke patients

The practical implementation of continuous monitoring of stroke patients by Electrical Impedance Tomography (EIT) is addressed. In a previous paper, we have demonstrated EIT sensitivity to cerebral hemodynamics, using scalp-mounted electrodes, very low-noise measurements, and a novel image reconstruction method. In the present paper, we investigate the potential to adapt that system for clinical application, by using 50% fewer electrodes and by incorporating into the measurement protocol an additional high-frequency measurement to provide an effective reference. Previously published image reconstruction methods for multi-frequency EIT are substantially improved by exploiting the forward calculations enabled by the detailed head model, particularly to make the referencing method more robust and to attempt to remove the effects of modelling error. Images are presented from simulation of a typical hemorrhagic stroke and its growth. These results are encouraging for exploration of the potential clinical benefit of the methodology in long-term monitoring of hemorrhagic stroke.

Signal-to-noise ratio variance impact on the image reconstruction of electrical resistance tomography in solutions with high background conductivity

Electrical Resistance Tomography (ERT) has the potentialities of non-intrusive techniques and high temporal resolution which are essential characteristics for multiphase flow measurements. However, high background conductivities, such as saline water in oil extraction, impose a limitation in ERT image reconstruction. Focusing on the operational limits of an ERT tomography system operating in different conductivity backgrounds from 0.010 to 4.584 S/m, the impact on the image reconstruction was assessed via signal-to-noise variance. The signal-to-noise ratio (SNR) variance had a strong correlation (p-value = 5.40 × 10^-15) with the image reconstruction quality at the threshold of 30 dB, reaching a correlation value of r = -0.92 in the range of 0.010-0.246 S/m. Regarding the position error of the phantom, p-value = 1.30 × 10^-5 and r = -0.66 were attained. The global results revealed that the correlation of the mean of the SNR (p-value = 5 × 10^-4 and r = 0.55) was kept unaltered through the whole conductivity range, showing that such a statistical index can induce bias in establishing the operational limits of the hardware.

An open-source and easily replicable hardware for Electrical Impedance Tomography

Electrical Impedance Tomography (EIT) is a powerful imaging tool for investigating electrical properties of tissues such as that of human bodies. The cheap, harmless and portable nature of this tool has made EIT a popular choice in many biomedical applications. However, performing EIT requires strong development at both hardware and software levels. In particular, performing in-lab experiences remains a challenge due to the cost of commercially available devices or the complexity of systems proposed in scientific literature. In this paper, an efficient and easily replicable EIT hardware is presented. This hardware was developed with the objective of making EIT accessible to as many people as possible. It has been designed for operating frequencies between 1 kHz and 50 kHz, and can be used for in-lab validation of proof of concept. Special care has been paid to the choice of components in order to optimize the performance versus cost ratio. Also, the overall footprint has been reduced by using recent and up-to-date integrated circuits. In particular, the use of a lock-in amplifier is a compact solution that allows both narrow-band filtering of the signal and provides an easily quantifiable DC signal at the output. Circuit schematics as well as manufacturing files are shared so that understanding, replication and improvement of circuits are facilitated. Fabrication and usage procedures are given as well. At last, the proposed hardware is experimentally tested and validated first by comparing experimental data to simulations, then by reconstructing an inclusion in biological tissues.

Scalp-Mounted Electrical Impedance Tomography of Cerebral Hemodynamics

An Electrical Impedance Tomography (EIT) system has been developed for dynamic three-dimensional imaging of changes in conductivity distribution in the human head, using scalp-mounted electrodes. We attribute these images to changes in cerebral perfusion. At 100 frames per second (fps), voltage measurement is achieved with full-scale signal-to-noise ratio of 105 dB and common-mode rejection ratio > 90 dB. A novel nonlinear method is presented for 3-D imaging of the difference in conductivity distribution in the head, relative to a reference time. The method achieves much reduced modelling error. It successfully localizes conductivity inclusions in experimental and simulation tests, where previous methods fail. For > 50 human volunteers, the rheoencephalography (REG) waveform is observed in EIT voltage measurements for every volunteer, with peak-to-peak amplitudes up to approx. 50 μV_rms. Images are presented of the change in conductivity distribution during the REG/cardiac cycle, at 50 fps, showing maximum local conductivity change of approx. 1% in grey/white matter. A total of 17 tests were performed during short (typically 5s) carotid artery occlusions on 5 volunteers, monitored by Transcranial Doppler ultrasound. From EIT measurements averaged over complete REG/cardiac cycles, 13 occlusion tests showed consistently decreased conductivity of cerebral regions on the occluded side, and increased conductivity on the opposite side. The maximum local conductivity change during occlusion was approx. 20%. The simplicity of the carotid artery intervention provides a striking validation of the scalp-mounted measurement system in imaging cerebral hemodynamics, and the REG images indicate its unique combination of sensitivity and temporal resolution.

An Imaged Based Method for Universal Performance Evaluation of Electrical Impedance Tomography Systems

This paper describes a simple and reproducible method for universal evaluation of the performance of electrical impedance tomography (EIT) systems using reconstructed images. To address the issues where common electrical parameters are not directly related to the quality of EIT images, based on objective full reference (FR) image quality assessment, the method provides a visually distinguishable hot colormap and two new FR metrics, the global and the more specific 'region of interest'. A passive 16 electrode EIT system using an application specific integrated circuit front-end was used to evaluate the proposed method. The measured results show, both visually and in terms of the proposed FR metrics, the impact on recorded EIT images with different design parameters and non-idealities. The paper also compares the image results of a passive electrode system with a matched 'single variable' active electrode system and demonstrates the merit of an active electrode system for noise interference. A figure of merit based on the FR metrics is proposed.

Signal conditioning using logarithmic amplifier for biomedical applications of electrical impedance tomography

OBJECTIVE

The aim of this study was to explore the use of a logarithmic amplifier to improve the spatial resolution (RES) of a low-cost electrical impedance tomography (EIT) system. In an EIT system, the measured signal has a large dynamic range from µV to mV, which requires high-RES (analog to digital conversion) cards. The logarithmic amplifier reduces the dynamic range by expanding lower values and compressing higher values, thereby improving the sensitivity and at the same time preventing the signal from saturation. In addition, a low-RES analog to digital conversion (ADC) cards can be used, making the system cost effective. This work evaluates the performance of a logarithmic amplifier and a linear amplifier used for signal conditioning in a low-cost EIT system.

APPROACH

Two EIT systems based on a linear amplifier and logarithmic amplifier were designed. Phantom experiments were carried out with very small amounts of current injection. The signal-to-noise ratio (SNR), image quality, minimum detectable size and minimum detectable conductivity change were obtained.

MAIN RESULTS

The logarithmic amplifier-based EIT system increased the average SNR by 4 dB. It also showed improvement in the RES and contrast-to-noise ratio of the images. The minimum size detectable by the logarithmic amplifier-based system was of radius 0.25 cm in a tank of radius 11 cm and the minimum change in conductivity detectable was 11%.

SIGNIFICANCE

Logarithmic amplifier-based signal conditioning is a promising technique for improving the spatial RES of a low-cost EIT system that has a low-RES ADC.

Electrical impedance tomography in perioperative medicine: careful respiratory monitoring for tailored interventions

BACKGROUND

Electrical impedance tomography (EIT) is a non-invasive radiation-free monitoring technique that provides images based on tissue electrical conductivity of the chest. Several investigations applied EIT in the context of perioperative medicine, which is not confined to the intraoperative period but begins with the preoperative assessment and extends to postoperative follow-up.

MAIN BODY

EIT could provide careful respiratory monitoring in the preoperative assessment to improve preparation for surgery, during anaesthesia to guide optimal ventilation strategies and to monitor the hemodynamic status and in the postoperative period for early detection of respiratory complications. Moreover, EIT could further enhance care of patients undergoing perioperative diagnostic procedures. This narrative review summarizes the latest evidence on the application of this technique to the surgical patient, focusing also on possible future perspectives.

CONCLUSIONS

EIT is a promising technique for the perioperative assessment of surgical patients, providing tailored adaptive respiratory and haemodynamic monitoring. Further studies are needed to address the current technological limitations, confirm the findings and evaluate which patients can benefit more from this technology.

Characteristic pattern of pleural effusion in electrical impedance tomography images of critically ill patients

BACKGROUND

Electrical impedance tomography (EIT) is increasingly used for continuous monitoring of ventilation in intensive care patients. Clinical observations in patients with pleural effusion show an increase in out-of-phase impedance changes. We hypothesised that out-of-phase impedance changes are a typical EIT finding in patients with pleural effusion and could be useful in its detection.

METHODS

We conducted a prospective observational study in intensive care unit patients with and without pleural effusion. In patients with pleural effusion, EIT data were recorded before, during, and after unilateral drainage of pleural effusion. In patients with no pleural effusion, EIT data were recorded without any intervention. EIT images were separated into four quadrants of equal size. We analysed the sum of out-of-phase impedance changes in the affected quadrant in patients with pleural effusion before, during, and after drainage and compared it with the sum of out-of-phase impedance changes in the dorsal quadrants of patients without pleural effusion.

RESULTS

We included 20 patients with pleural effusion and 10 patients without pleural effusion. The median sum of out-of-phase impedance changes was 70 (interquartile range 49-119) arbitrary units (a.u.) in patients with pleural effusion before drainage, 25 (12-46) a.u. after drainage (P<0.0001) and 11 (6-17) a.u. in patients without pleural effusion (P<0.0001 vs pleural effusion before drainage). The area under the receiver operating characteristics curve was 0.96 (95% limits of agreement 0.91-1.01) between patients with pleural effusion before drainage and those without pleural effusion.

CONCLUSIONS

In patients monitored with EIT, the presence of out-of-phase impedance changes is highly suspicious of pleural effusion and should trigger further examination.

Detection of thoracic vascular structures by electrical impedance tomography: a systematic assessment of prominence peak analysis of impedance changes

OBJECTIVE

Electrical impedance tomography (EIT) is a non-invasive and radiation-free bedside monitoring technology, primarily used to monitor lung function. First experimental data shows that the descending aorta can be detected at different thoracic heights and might allow the assessment of central hemodynamics, i.e. stroke volume and pulse transit time.

APPROACH

First, the feasibility of localizing small non-conductive objects within a saline phantom model was evaluated. Second, this result was utilized for the detection of the aorta by EIT in ten anesthetized pigs with comparison to thoracic computer tomography (CT). Two EIT belts were placed at different thoracic positions and a bolus of hypertonic saline (10 ml, 20%) was administered into the ascending aorta while EIT data were recorded. EIT images were reconstructed using the GREIT model, based on the individual's thoracic contours. The resulting EIT images were analyzed pixel by pixel to identify the aortic pixel, in which the bolus caused the highest transient impedance peak in time.

MAIN RESULTS

In the phantom, small objects could be located at each position with a maximal deviation of 0.71 cm. In vivo, no significant differences between the aorta position measured by EIT and the anatomical aorta location were obtained for both measurement planes if the search was restricted to the dorsal thoracic region of interest (ROIs).

SIGNIFICANCE

It is possible to detect the descending aorta at different thoracic levels by EIT using an intra-aortic bolus of hypertonic saline. No significant differences in the position of the descending aorta on EIT images compared to CT images were obtained for both EIT belts.

A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors

Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively.

A novel 3D-printed head phantom with anatomically realistic geometry and continuously varying skull resistivity distribution for electrical impedance tomography

Phantom experiments are an important step for testing during the development of new hardware or imaging algorithms for head electrical impedance tomography (EIT) studies. However, due to the sophisticated anatomical geometry and complex resistivity distribution of the human head, constructing an accurate phantom for EIT research remains challenging, especially for skull modelling. In this paper, we designed and fabricated a novel head phantom with anatomically realistic geometry and continuously varying skull resistivity distribution based on 3D printing techniques. The skull model was constructed by simultaneously printing the distinct layers inside the skull with resistivity-controllable printing materials. The entire phantom was composed of saline skin, a 3D-printed skull, saline cerebrospinal fluid (CSF) and 3D-printed brain parenchyma. The validation results demonstrated that the resistivity of the phantom was in good agreement with that of human tissue and was stable over time, and the new phantom performed well in EIT imaging. This paper provides a standardized, efficient and reproducible method for the construction of a head phantom for EIT that could be easily adapted to other conditions for manufacturing head phantoms for brain function research, such as transcranial direct current stimulation (TDCS) and electroencephalography (EEG).

Absolute Reconstructions Using Rotational Electrical Impedance Tomography for Breast Cancer Imaging

A rotational Electrical Impedance Tomography (rEIT) methodology is described and shown to produce spatially accurate absolute reconstructions with improved image contrast and an improved ability to distinguish closely spaced inclusions compared to traditional EIT on data recorded from cylindrical and breast-shaped tanks. Rotations of the tank without altering the interior conductivity distribution are used to produce the rEIT data. Quantitatively, rEIT was able to distinguish two inclusions that were 1.5 cm closer together than traditional EIT could achieve for inclusions placed 2 to 3 cm from the center for the cylindrical tank, and rEIT was able to distinguish two tumor-like inclusions where traditional EIT could not reliably do so. Mathematical analysis showed that rEIT improves the number of stable singular vectors by up to 4.2 and 4.7 times than that of traditional EIT for the cylindrical and breast-shaped tanks, respectively, which is an indication of improved resolution. Direct investigations into measurements revealed minimum rotation angles that should yield data uncorrupted by noise. Two inverse approaches (one that inverts then fuses the data (I/DF) and one that fuses the data then inverts (DF/I)) and two mesh modeling approaches were considered. It was found that DF/I produces far better results compared to I/DF and a rotated-mesh approach produces further improvements. The ability to obtain improved absolute reconstructions using rEIT on a practical clinical scenario (breast-shaped tank experiment) is an important step towards using rEIT to improve previous EIT results in medical applications.

Chest electrical impedance tomography examination, data analysis, terminology, clinical use and recommendations: consensus statement of the TRanslational EIT developmeNt stuDy group

Electrical impedance tomography (EIT) has undergone 30 years of development. Functional chest examinations with this technology are considered clinically relevant, especially for monitoring regional lung ventilation in mechanically ventilated patients and for regional pulmonary function testing in patients with chronic lung diseases. As EIT becomes an established medical technology, it requires consensus examination, nomenclature, data analysis and interpretation schemes. Such consensus is needed to compare, understand and reproduce study findings from and among different research groups, to enable large clinical trials and, ultimately, routine clinical use. Recommendations of how EIT findings can be applied to generate diagnoses and impact clinical decision-making and therapy planning are required. This consensus paper was prepared by an international working group, collaborating on the clinical promotion of EIT called TRanslational EIT developmeNt stuDy group. It addresses the stated needs by providing (1) a new classification of core processes involved in chest EIT examinations and data analysis, (2) focus on clinical applications with structured reviews and outlooks (separately for adult and neonatal/paediatric patients), (3) a structured framework to categorise and understand the relationships among analysis approaches and their clinical roles, (4) consensus, unified terminology with clinical user-friendly definitions and explanations, (5) a review of all major work in thoracic EIT and (6) recommendations for future development (193 pages of online supplements systematically linked with the chief sections of the main document). We expect this information to be useful for clinicians and researchers working with EIT, as well as for industry producers of this technology.

Fully Parallel Electrical Impedance Tomography Using Code Division Multiplexing

Electrical Impedance Tomography (EIT) has been dominated by the use of Time Division Multiplexing (TDM) and Frequency Division Multiplexing (FDM) as methods of achieving orthogonal injection of excitation signals. Code Division Multiplexing (CDM), presented in this paper is an alternative that eliminates temporal data inconsistencies of TDM for fast changing systems. Furthermore, this approach eliminates data inconsistencies that arise in FDM when frequency bands of current injecting electrodes are chosen over frequencies that have large changes in the imaged object's impedance. To the authors knowledge no fully functional wideband system or simulation platform using simultaneous injection of Gold codes currents has been reported. In this paper, we formulate, simulate and develop a fully functional pseudo-random (Gold) code driven EIT system with 15 excitation currents and 16 separate voltage measurement electrodes. In the work we verify the use of CDM as a multiplexing modality in simultaneous injection EIT, using a prototype system with an overall bandwidth of 15 kHz, and attainable speed of 462 frames/s using codes with a period of 31 chips. Simulations and experiments are performed using the Electrical Impedance and Diffuse Optics Reconstruction Software (EIDORS). We also propose the use of image processing on reconstructed images to establish their quality quantitatively without access to raw reconstruction data. The results of this study show that CDM can be successfully used in EIT, and gives results of similar visual quality to TDM and FDM. Achieved performance shows average position error of 3.5% and size error of 6.2%.

Feature-space assessment of electrical impedance tomography coregistered with computed tomography in detecting multiple contrast targets

PURPOSE

Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets.

METHODS

EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance and diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures.

RESULTS

In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed contrast discrimination of 47%, while the CT imaging system showed a discrimination of only 1.5%. The structural similarity index measure showed a drop of 24% with EIT imaging compared to CT imaging. The average detectability measure for CT imaging was found to be 2.375 ± 0.19 before fusion. After complementing with EIT information, the detectability measure increased to 11.06 ± 2.04. Based on the feature metrics, the functional imaging quality of CT and EIT were found to be 2.29% and 86%, respectively, before fusion. Structural imaging quality was found to be 66% for CT and 16% for EIT. After fusion, functional imaging quality improved in CT imaging from 2.29% to 42% and the structural imaging quality of EIT imaging changed from 16% to 66%. The improvement in image quality was also observed in detecting objects of different sizes.

CONCLUSIONS

The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.

Functional validation and comparison framework for EIT lung imaging

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.

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.

Iterative sinc-convolution method for solving planar D-bar equation with application to EIT

The numerical solution of D-bar integral equations is the key in inverse scattering solution of many complex problems in science and engineering including conductivity imaging. Recently, a couple of methodologies were considered for the numerical solution of D-bar integral equation, namely product integrals and multigrid. The first one involves high computational complexity and other one has low convergence rate disadvantages. In this paper, a new and efficient sinc-convolution algorithm is introduced to solve the two-dimensional D-bar integral equation to overcome both of these disadvantages and to resolve the singularity problem not tackled before effectively. The method of sinc-convolution is based on using collocation to replace multidimensional convolution-form integrals- including the two-dimensional D-bar integral equations - by a system of algebraic equations. Separation of variables in the proposed method allows elimination of the formulation of the huge full matrices and therefore reduces the computational complexity drastically. In addition, the sinc-convolution method converges exponentially with a convergence rate of O(e-cN). Simulation results on solving a test electrical impedance tomography problem confirm the efficiency of the proposed sinc-convolution-based algorithm.

Electrical impedance tomography system based on active electrodes

Electrical impedance tomography (EIT) can image the distribution of ventilated lung tissue, and is thus a promising technology to help monitor patient breathing to help selection of mechanical ventilation parameters. Two key difficulties in EIT instrumentation make such monitoring difficult: (1) EIT data quality depends on good electrode contact and is sensitive to changes in contact quality, and (2) EIT electrodes are difficult and time consuming to place on patients. This paper presents the design and initial tests of an active electrode-based system to address these difficulties. Our active electrode EIT system incorporates an active electrode belt, a central voltage-driven current source, central analog to digital converters and digital to analog converters, a central FPGA-based demodulator and controller. The electrode belt is designed incorporating 32 active electrodes, each of which contains the electronic amplifiers, switches and associated logic. Tests show stable device performance with a convenient ease of use and good imaging ability in volunteer tests.