Studying the resistivity imaging of chicken tissue phantoms with different current patterns in Electrical Impedance Tomography (EIT)

A current injection pattern in Electrical Impedance Tomography (EIT) has its own current distribution profile within the domain under test. Hence, different current patterns have different sensitivity, spatial resolution and distinguishability. Image reconstruction studies with practical phantoms are essential to assess the performance of EIT systems for their validation, calibration and comparison purposes. Impedance imaging of real tissue phantoms with different current injection methods is also essential for better assessment of the biomedical EIT systems. Chicken tissue paste phantoms and chicken tissue block phantoms are developed and the resistivity image reconstruction is studied with different current injection methods. A 16-electrode array is placed inside the phantom tank and the tank is filled with chicken muscle tissue paste or chicken tissue blocks as the background mediums. Chicken fat tissue, chicken bone, air hole and nylon cylinders are used as the inhomogeneity to obtained different phantom configurations. A low magnitude low frequency constant sinusoidal current is injected at the phantom boundary with opposite and neighboring current patterns and the boundary potentials are measured. Resistivity images are reconstructed from the boundary data using EIDORS and the reconstructed images are analyzed with the contrast parameters calculated from their elemental resistivity profiles. Results show that the resistivity profiles of all the phantom domains are successfully reconstructed with a proper background resistivity and high inhomogeneity resistivity for both the current injection methods. Reconstructed images show that, for all the chicken tissue phantoms, the inhomogeneities are suitably reconstructed with both the current injection protocols though the chicken tissue block phantom and opposite method are found more suitable. It is observed that the boundary potentials of the chicken tissue block phantoms are higher than the chicken tissue paste phantom. SNR of the chicken tissue block phantoms are found comparatively more and hence the chicken tissue block phantom is found more suitable for its lower noise performance. The background noise is found less in opposite method for all the phantom configurations which yields the better resistivity images with high PCR and COC and proper IRMean and IRMax neighboring method showed higher noise level for both the chicken tissue paste phantoms and chicken tissue block phantoms with all the inhomogeneities. Opposite method is found more suitable for both the chicken tissue phantoms, and also, chicken tissue block phantoms are found more suitable compared to the chicken tissue paste phantom. (C) 2012 Elsevier Ltd. All rights reserved.

A MatLAB Based Virtual Phantom for 2D Electrical Impedance Tomography (MatVP2DEIT): Studying the Medical Electrical Impedance Tomography Reconstruction in Computer

Electrical Impedance Tomography (EIT) is a computerized medical imaging technique which reconstructs the electrical impedance images of a domain under test from the boundary voltage-current data measured by an EIT electronic instrumentation using an image reconstruction algorithm. Being a computed tomography technique, EIT injects a constant current to the patient's body through the surface electrodes surrounding the domain to be imaged (Omega) and tries to calculate the spatial distribution of electrical conductivity or resistivity of the closed conducting domain using the potentials developed at the domain boundary (partial derivative Omega). Practical phantoms are essentially required to study, test and calibrate a medical EIT system for certifying the system before applying it on patients for diagnostic imaging. Therefore, the EIT phantoms are essentially required to generate boundary data for studying and assessing the instrumentation and inverse solvers a in EIT. For proper assessment of an inverse solver of a 2D EIT system, a perfect 2D practical phantom is required. As the practical phantoms are the assemblies of the objects with 3D geometries, the developing of a practical 2D-phantom is a great challenge and therefore, the boundary data generated from the practical phantoms with 3D geometry are found inappropriate for assessing a 2D inverse solver. Furthermore, the boundary data errors contributed by the instrumentation are also difficult to separate from the errors developed by the 3D phantoms. Hence, the errorless boundary data are found essential to assess the inverse solver in 2D EIT. In this direction, a MatLAB-based Virtual Phantom for 2D EIT (MatVP2DEIT) is developed to generate accurate boundary data for assessing the 2D-EIT inverse solvers and the image reconstruction accuracy. MatVP2DEIT is a MatLAB-based computer program which simulates a phantom in computer and generates the boundary potential data as the outputs by using the combinations of different phantom parameters as the inputs to the program. Phantom diameter, inhomogeneity geometry (shape, size and position), number of inhomogeneities, applied current magnitude, background resistivity, inhomogeneity resistivity all are set as the phantom variables which are provided as the input parameters to the MatVP2DEIT for simulating different phantom configurations. A constant current injection is simulated at the phantom boundary with different current injection protocols and boundary potential data are calculated. Boundary data sets are generated with different phantom configurations obtained with the different combinations of the phantom variables and the resistivity images are reconstructed using EIDORS. Boundary data of the virtual phantoms, containing inhomogeneities with complex geometries, are also generated for different current injection patterns using MatVP2DEIT and the resistivity imaging is studied. The effect of regularization method on the image reconstruction is also studied with the data generated by MatVP2DEIT. Resistivity images are evaluated by studying the resistivity parameters and contrast parameters estimated from the elemental resistivity profiles of the reconstructed phantom domain. Results show that the MatVP2DEIT generates accurate boundary data for different types of single or multiple objects which are efficient and accurate enough to reconstruct the resistivity images in EIDORS. The spatial resolution studies show that, the resistivity imaging conducted with the boundary data generated by MatVP2DEIT with 2048 elements, can reconstruct two circular inhomogeneities placed with a minimum distance (boundary to boundary) of 2 mm. It is also observed that, in MatVP2DEIT with 2048 elements, the boundary data generated for a phantom with a circular inhomogeneity of a diameter less than 7% of that of the phantom domain can produce resistivity images in EIDORS with a 1968 element mesh. Results also show that the MatVP2DEIT accurately generates the boundary data for neighbouring, opposite reference and trigonometric current patterns which are very suitable for resistivity reconstruction studies. MatVP2DEIT generated data are also found suitable for studying the effect of the different regularization methods on reconstruction process. Comparing the reconstructed image with an original geometry made in MatVP2DEIT, it would be easier to study the resistivity imaging procedures as well as the inverse solver performance. Using the proposed MatVP2DEIT software with modified domains, the cross sectional anatomy of a number of body parts can be simulated in PC and the impedance image reconstruction of human anatomy can be studied.

A FEM-Based Forward Solver for Studying the Forward Problem of Electrical Impedance Tomography (EIT) with A Practical Biological Phantom

A Finite Element Method based forward solver is developed for solving the forward problem of a 2D-Electrical Impedance Tomography. The Method of Weighted Residual technique with a Galerkin approach is used for the FEM formulation of EIT forward problem. The algorithm is written in MatLAB7.0 and the forward problem is studied with a practical biological phantom developed. EIT governing equation is numerically solved to calculate the surface potentials at the phantom boundary for a uniform conductivity. An EIT-phantom is developed with an array of 16 electrodes placed on the inner surface of the phantom tank filled with KCl solution. A sinusoidal current is injected through the current electrodes and the differential potentials across the voltage electrodes are measured. Measured data is compared with the differential potential calculated for known current and solution conductivity. Comparing measured voltage with the calculated data it is attempted to find the sources of errors to improve data quality for better image reconstruction.

A Simple Instrumentation Calibration Technique for Electrical Impedance Tomography (EIT) Using A 16-Electrode Phantom

A simple analog instrumentation for Electrical Impedance Tomography is developed and calibrated using the practical phantoms. A constant current injector consisting of a modified Howland voltage controlled current source fed by a voltage controlled oscillator is developed to inject a constant current to the phantom boundary. An instrumentation amplifier, 50 Hz notch filter and a narrow band pass filter are developed and used for signal conditioning. Practical biological phantoms are developed and the forward problem is studied to calibrate the EIT-instrumentation. An array of sixteen stainless steel electrodes is developed and placed inside the phantom tank filled with KCl solution. 1 mA, 50 kHz sinusoidal current is injected at the phantom boundary using adjacent current injection protocol. The differential potentials developed at the voltage electrodes are measured for sixteen current injections. Differential voltage signal is passed through an instrumentation amplifier and a filtering block and measured by a digital multimeter. A forward solver is developed using Finite Element Method in MATLAB7.0 for solving the EIT governing equation. Differential potentials are numerically calculated using the forward solver with a simulated current and bathing solution conductivity. Measured potential data is compared with the differential potentials calculated for calibrating the instrumentation to acquire the voltage data suitable for better image reconstruction.

A Study of Practical Biological Phantoms with Simple Instrumentation for Electrical Impedance Tomography (EIT)

16-electrode phantoms are developed and studied with a simple instrumentation developed for Electrical Impedance Tomography. An analog instrumentation is developed with a sinusoidal current generator and signal conditioner circuit. Current generator is developed withmodified Howland constant current source fed by a voltage controlled oscillator and the signal conditioner circuit consisting of an instrumentation amplifier and a narrow band pass filter. Electronic hardware is connected to the electrodes through a DIP switch based multiplexer module. Phantoms with different electrode size and position are developed and the EIT forward problem is studied using the forward solver. A low frequency low magnitude sinusoidal current is injected to the surface electrodes surrounding the phantom boundary and the differential potential is measured by a digital multimeter. Comparing measured potential with the simulated data it is intended to reduce the measurement error and an optimum phantom geometry is suggested. Result shows that the common mode electrode reduces the common mode error of the EIT electronics and reduces the error potential in the measured data. Differential potential is reduced up to 67 mV at the voltage electrode pair opposite to the current electrodes. Offset potential is measured and subtracted from the measured data for further correction. It is noticed that the potential data pattern depends on the electrode width and the optimum electrode width is suggested. It is also observed that measured potential becomes acceptable with a 20 mm solution column above and below the electrode array level.

Resistivity imaging of a reconfigurable phantom with circular inhomogeneities in 2D-electrical impedance tomography

Resistivity imaging of a reconfigurable phantom with circular inhomogeneities is studied with a simple instrumentation and data acquisition system for Electrical Impedance Tomography. The reconfigurable phantom is developed with stainless steel electrodes and a sinusoidal current of constant amplitude is injected to the phantom boundary using opposite current injection protocol. Nylon and polypropylene cylinders with different cross sectional areas are kept inside the phantom and the boundary potential data are collected. The instrumentation and the data acquisition system with a DIP switch-based multiplexer board are used to inject a constant current of desired amplitude and frequency. Voltage data for the first eight current patterns (128 voltage data) are found to be sufficient to reconstruct the inhomogeneities and hence the acquisition time is reduced. Resistivity images are reconstructed from the boundary data for different inhomogeneity positions using EIDORS-2D. The results show that the shape and resistivity of the inhomogeneity as well as the background resistivity are successfully reconstructed from the potential data for single or double inhomogeneity phantoms. The resistivity images obtained from the single and double inhomogeneity phantom clearly indicate the inhomogeneity as the high resistive material. Contrast to noise ratio (CNR) and contrast recovery (CR) of the reconstructed images are found high for the inhomogeneities near all the electrodes arbitrarily chosen for the entire study. (C) 2010 Elsevier Ltd. All rights reserved.

Common Ground Method of Current Injection in Electrical Impedance Tomography

Surface electrodes are essentially required to be switched for boundary data collection in electrical impedance tomography (Ell). Parallel digital data bits are required to operate the multiplexers used, generally, for electrode switching in ELT. More the electrodes in an EIT system more the digital data bits are needed. For a sixteen electrode system. 16 parallel digital data bits are required to operate the multiplexers in opposite or neighbouring current injection method. In this paper a common ground current injection is proposed for EIT and the resistivity imaging is studied. Common ground method needs only two analog multiplexers each of which need only 4 digital data bits and hence only 8 digital bits are required to switch the 16 surface electrodes. Results show that the USB based data acquisition system sequentially generate digital data required for multiplexers operating in common ground current injection method. The profile of the boundary data collected from practical phantom show that the multiplexers are operating in the required sequence in common ground current injection protocol. The voltage peaks obtained for all the inhomogeneity configurations are found at the accurate positions in the boundary data matrix which proved the sequential operation of multiplexers. Resistivity images reconstructed from the boundary data collected from the practical phantom with different configurations also show that the entire digital data generation module is functioning properly. Reconstructed images and their image parameters proved that the boundary data are successfully acquired by the DAQ system which in turn indicates a sequential and proper operation of multiplexers.

Studies on thin film based flexible gold electrode arrays for resistivity imaging in electrical impedance tomography

Practical phantoms are essential to assess the electrical impedance tomography (EIT) systems for their validation, calibration and comparison purposes. Metal surface electrodes are generally used in practical phantoms which reduce the SNR of the boundary data due to their design and development errors. Novel flexible and biocompatible gold electrode arrays of high geometric precision are proposed to improve the boundary data quality in EIT. The flexible gold electrode arrays are developed on flexible FR4 sheets using thin film technology and practical gold electrode phantoms are developed with different configurations. Injecting a constant current to the phantom boundary the surface potentials are measured by a LabVIEW based data acquisition system and the resistivity images are reconstructed in EIDORS. Boundary data profile and the resistivity images obtained from the gold electrode phantoms are compared with identical phantoms developed with stainless steel electrodes. Surface profilometry, microscopy and the impedance spectroscopy show that the gold electrode arrays are smooth, geometrically precised and less resistive. Results show that the boundary data accuracy and image quality are improved with gold electrode arrays. Results show that the diametric resistivity plot (DRP), contrast to noise ratio (CNR), percentage of contrast recovery (PCR) and coefficient of contrast (COC) of reconstructed images are improved in gold electrode phantoms. (C) 2013 Elsevier Ltd. All rights reserved.

Projection Error Propagation-based Regularization (PEPR) method for resistivity reconstruction in Electrical Impedance Tomography (EIT)

A novel Projection Error Propagation-based Regularization (PEPR) method is proposed to improve the image quality in Electrical Impedance Tomography (EIT). PEPR method defines the regularization parameter as a function of the projection error developed by difference between experimental measurements and calculated data. The regularization parameter in the reconstruction algorithm gets modified automatically according to the noise level in measured data and ill-posedness of the Hessian matrix. Resistivity imaging of practical phantoms in a Model Based Iterative Image Reconstruction (MoBIIR) algorithm as well as with Electrical Impedance Diffuse Optical Reconstruction Software (EIDORS) with PEPR. The effect of PEPR method is also studied with phantoms with different configurations and with different current injection methods. All the resistivity images reconstructed with PEPR method are compared with the single step regularization (STR) and Modified Levenberg Regularization (LMR) techniques. The results show that, the PEPR technique reduces the projection error and solution error in each iterations both for simulated and experimental data in both the algorithms and improves the reconstructed images with better contrast to noise ratio (CNR), percentage of contrast recovery (PCR), coefficient of contrast (COC) and diametric resistivity profile (DRP). (C) 2013 Elsevier Ltd. All rights reserved.

A Gold Sensors Array for Imaging The Real Tissue Phantom in Electrical Impedance Tomography

Surface electrodes in Electrical Impedance Tomography (EIT) phantoms usually reduce the SNR of the boundary potential data due to their design and development errors. A novel gold sensors array with high geometric precision is developed for EIT phantoms to improve the resistivity image quality. Gold thin films are deposited on a flexible FR4 sheet using electro-deposition process to make a sixteen electrode array with electrodes of identical geometry. A real tissue gold electrode phantom is developed with chicken tissue paste and the fat cylinders as the inhomogeneity. Boundary data are collected using a USB based high speed data acquisition system in a LabVIEW platform for different inhomogeneity positions. Resistivity images are reconstructed using EIDORS and compared with identical stainless steel electrode systems. Image contrast parameters are calculated from the resistivity matrix and the reconstructed images are evaluated for both the phantoms. Image contrast and image resolution of resistivity images are improved with gold electrode array.

A Feature-Based Solution to Forward Problem in Electrical Capacitance Tomography of Conductive Materials

A new feature-based technique is introduced to solve the nonlinear forward problem (FP) of the electrical capacitance tomography with the target application of monitoring the metal fill profile in the lost foam casting process. The new technique is based on combining a linear solution to the FP and a correction factor (CF). The CF is estimated using an artificial neural network (ANN) trained using key features extracted from the metal distribution. The CF adjusts the linear solution of the FP to account for the nonlinear effects caused by the shielding effects of the metal. This approach shows promising results and avoids the curse of dimensionality through the use of features and not the actual metal distribution to train the ANN. The ANN is trained using nine features extracted from the metal distributions as input. The expected sensors readings are generated using ANSYS software. The performance of the ANN for the training and testing data was satisfactory, with an average root-mean-square error equal to 2.2%.

Studies on glass transition and starch re-crystallization in wheat bread during staling using electrical impedance spectroscopy

Bread staling is a very complex phenomenon that is not yet completely understood. The present work explains how the electrical impedance spectroscopy technique can be utilized to investigate the effect of staling on the physicochemical properties of wheat bread during storage. An instrument based on electrical impedance spectroscopy technique is developed to study the electrical properties of wheat bread both at its crumb and crust with the help of designed multi-channel ring electrodes. Electrical impedance behavior, mainly capacitance and resistance, of wheat bread at crust and crumb during storage (up to 120 h) is investigated. The variation in capacitance showed the glass transition phenomenon at room temperature in bread crust after 96 h of storage with 18% of moisture in it. The resistance changes at bread crumb showed the starch recrystallization during staling.

Non-Destructive Method to Estimate the Moisture Content in Bread using Multi-Channel Electrical Impedance Spectroscopy

Bread undergoes several physicochemical changes during storage that results in a rapid loss of freshness. These changes depend on moisture content present in bread product. An instrument based on electrical impedance spectroscopy technique is developed to estimate moisture content of bread at different zones using designed multi-channel ring electrodes. A dedicated AT89S52 microcontroller and associated peripherals are employed for hardware. A constant current is applied across bread loaf through central pair of electrodes and developed potential across different zones of bread loaf are measured using remaining four ring electrode pairs. These measured values of voltage and current are used to measure the impedance at each zone. Electrical impedance behavior of the bread loaf at crust and crumb is investigated during storage. A linear relationship is observed between the measured impedance and moisture content present in crust and crumb of bread loaf during storage of 120 hours.

Domain size correlated magnetic properties and electrical impedance of size dependent nickel ferrite nanoparticles

We report here the investigations on the size dependent variation of magnetic properties of nickel ferrite nanoparticles. Nickel ferrite nanoparticles of different sizes (14 to 22 nm) were prepared by the sol-gel route at different annealing temperatures. They are characterized by TGA-DTA, XRD, SEM, TEM and Raman spectroscopy techniques for the confirmation of the temperature of phase formation, thermal stability, crystallinity, morphology and structural status of the nickel ferrite nanoparticles. The magnetization studies revealed that the saturation magnetization (M-s), retentivity (M-r) increase, while coercivity (H-c) and anisotropy (K-eff) decrease as the particle size increases. The observed value of M-s is found to be relatively higher for a particle size of 22 nm. In addition, we have estimated the magnetic domain size using magnetic data and correlated to the average particle size. The calculated magnetic domain size is closely matching with the particle size estimated from XRD. Impedance spectroscopy was employed to study the samples in an equivalent circuit to understand their transport phenomena. It shows that nickel ferrite nanoparticles exhibit a non-Debye behavior with increasing particle size due to the influence of increasing disorders, surface effects, grain size and grain boundaries, etc. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Spectral analysis of noise in the neonatal intensive care unit

Objective To perform spectral analysis of noise generated by equipments and activities in a level III neonatal intensive care unit (NICU) and measure the real time sequential hourly noise levels over a 15 day period. Methods Noise generated in the NICU by individual equipments and activities were recorded with a digital spectral sound analyzer to perform spectral analysis over 0.5–8 KHz. Sequential hourly noise level measurements in all the rooms of the NICU were done for 15 days using a digital sound pressure level meter. Independent sample t test and one way ANOVA were used to examine the statistical significance of the results. The study has a 90% power to detect at least 4 dB differences from the recommended maximum of 50 dB with 95 % confidence. Results The mean noise levels in the ventilator room and stable room were 19.99 dB (A) sound pressure level (SPL) and 11.81 dB (A) SPL higher than the maximum recommended of 50 dB (A) respectively (p < 0.001). The equipments generated 19.11 dB SPL higher than the recommended norms in 1–8 KHz spectrum. The activities generated 21.49 dB SPL higher than the recommended norms in 1–8 KHz spectrum (p< 0.001). The ventilator and nebulisers produced excess noise of 8.5 dB SPL at the 0.5 KHz spectrum.Conclusion Noise level in the NICU is unacceptably high. Spectral analysis of equipment and activity noise have shown noise predominantly in the 1–8 KHz spectrum. These levels warrant immediate implementation of noise reduction protocols as a standard of care in the NICU.