Volume 2 (2011): Issue 1 (January 2011)

A Projection Error Propagation-based Regularization (PEPR) method is proposed and the reconstructed image quality is improved in Electrical Impedance Tomography (EIT). A projection error is produced due to the misfit of the calculated and measured data in the reconstruction process. The variation of the projection error is integrated with response matrix in each iteration and the reconstruction is carried out in EIDORS. The PEPR method is studied with the simulated boundary data for different inhomogeneity geometries. Simulated results demonstrate that the PEPR technique improves image reconstruction precision in EIDORS and hence it can be successfully implemented to increase the reconstruction accuracy in EIT.

A Block Matrix based Multiple Regularization (BMMR) technique is proposed for improving conductivity image quality in Electrical Impedance Tomography (EIT). The response matrix (J^TJ) has been partitioned into several sub-block matrices and the largest element of each sub-block matrix has been chosen as regularization parameter for the nodes contained by that sub-block. Simulated boundary data are generated for circular domains with circular inhomogeneities of different geometry and the conductivity images are reconstructed in a Model Based Iterative Image Reconstruction (MoBIIR) algorithm. Conductivity images are reconstructed with BMMR technique and the results are compared with the Single-step Tikhonov Regularization (STR) and modified Levenberg-Marquardt Regularization (LMR) methods. Results show that the BMMR technique improves the impedance image and its spatial resolution for single and multiple inhomogeneity phantoms of different geometries. It is observed that the BMMR technique reduces the projection error as well as the solution error and improves the conductivity reconstruction in EIT. Results also show that the BMMR method improves the image contrast and inhomogeneity conductivity profile by reducing background noise for all the phantom configurations.

Phantoms are essential for assessing the system performance in Electrical Impedance Tomography (EIT). Saline phantoms with insulator inhomogeneity fail to mimic the physiological structure of real body tissue in several aspects. Saline or any other salt solution is purely resistive and hence studying multifrequency EIT systems cannot be assessed with saline phantoms because the response of the purely resistive materials do not change over frequency. Animal tissues show a variable response over a wide band of signal frequency due to their complex physiological and physiochemical structures and hence they can be suitably used as bathing medium and inhomogeneity in the phantoms of multifrequency EIT systems. An efficient assessment of a multifrequency EIT system with a real tissue phantom needs a prior knowledge of the impedance profile of the bathing medium as well as the inhomogeneity. In this direction Electrical Impedance Spectroscopy (EIS) studies on broiler chicken muscle tissue paste, muscle tissue blocks and fat tissue blocks are conducted over a wide range of signal frequency using impedance analyzers, and their impedance profiles are analyzed. Results show that the chicken muscle tissue paste is less resistive than the fat tissue and hence it can be used successfully as the bathing medium of the phantoms for impedance imaging in multifrequency EIT. Fat tissue is found more resistive than the muscle tissue which makes it more suitable for the inhomogeneity in phantoms of impedance imaging study. Moreover, as there is a large difference between the resistivities of muscle tissue and fat tissue they can be used as either inhomogeneity or background medium. EIS studies also show that the variations in the impedance parameters of a muscle tissue block are greater than in the tissue paste as the cell membrane structures are destroyed in tissue paste. Results also show that the α and β dispersions are visible in all the parameters of both the tissue samples, but both the dispersions are larger in the muscle tissue block. The Nyquist plot obtained for the muscle tissue block demonstrates that the equivalent electric model of the tissue sample contains Warburg impedance and a constant phase element.

Dielectrophoresis (DEP) is a label-free technique for the characterization and manipulation of biological particles - such as cells, bacteria and viruses. Many studies have focused on the DEP cross-over frequency f_xo1, where cells in a non-uniform electric field undergo a transition from negative to positive DEP. Determination of f_xo1 provides a value for the membrane capacitance from the cell diameter, the means to monitor changes in cell morphology and viability, and the information required when devising DEP cell separation protocols. In this paper we describe the first systematic measurements of the second DEP cross-over frequency f_xo2 that occurs at much higher frequencies. Theory indicates that f_xo2 is sensitive to the internal dielectric properties of a cell, and our experiments on murine myeloma cells reveal that these properties exhibit temporal changes that are sensitive to both the osmolality and temperature of the cell suspending medium.

Activities around applications of Electrical Bioimpedance Spectroscopy (EBIS) have proliferated in the past decade significantly. Most of these activities have been focused in the analysis of the EBIS measurements, which eventually might enable novel applications. In Body Composition Assessment (BCA), the most common analysis approach currently used in EBIS is based on the Cole function, which most often requires curve fitting. One of the most implemented approaches for obtaining the Cole parameters is performed in the impedance plane through the geometrical properties that the Cole function exhibit in such domain as depressed semi-circle. To fit the measured impedance data to a semi-circle in the impedance plane, obtaining the Cole parameters in an indirect and sequential manner has several drawbacks. Applying a Non-Linear Least Square (NLLS) iterative fitting on the spectroscopy measurement, obtains the Cole parameters considering the frequency information contained in the measurement. In this work, from experimental total right side EBIS measurements, the BCA parameters have been obtained to assess the amount and distribution of whole body fluids. The values for the BCA parameters have been obtained using values for the Cole parameters estimated with both approaches: circular fitting on the impedance plane and NLLS impedance-only fitting. The comparison of the values obtained for the BCA parameters with both methods confirms that the NLLS impedance-only is an effective alternative as Cole parameter estimation method in BCA from EBIS measurements. Using the modulus of the Cole function as the model for the fitting would eliminate the need for performing phase detection in the acquisition process, simplifying the hardware specifications of the measurement instrumentation when implementing a bioimpedance spectrometer.

Athletes need a balanced body composition in order to achieve maximum performance. Especially dehydration reduces power and endurance during physical exercise. Monitoring the body composition, with a focus on body fluid, may help to avoid reduction in performance and other health problems. For this, a potential measurement method is bioimpedance spectroscopy (BIS). BIS is a simple, non-invasive measurement method that allows to determine different body compartments (body fluid, fat, fat-free mass). However, because many physiological changes occur during physical exercise that can influence impedance measurements and distort results, it cannot be assumed that the BIS data are related to body fluid loss alone. To confirm that BIS can detect body fluid loss due to physical exercise, finite element (FE) simulations were done. Besides impedance, also the current density contribution during a BIS measurement was modeled to evaluate the influence of certain tissues on BIS measurements. Simulations were done using CST EM Studio (Computer Simulation Technology, Germany) and the Visible Human Data Set (National Library of Medicine, USA). In addition to the simulations, BIS measurements were also made on athletes. Comparison between the measured bioimpedance data and simulation data, as well as body weight loss during sport, indicates that BIS measurements are sensitive enough to monitor body fluid loss during physical exercise.

This paper presents a new system for measuring water conductivity as a function of electrophysical property (admittance). The system is cheap and its manufacturing is easy. In addition, it does not require any sort of electrolysis and calibration. The system consists of four electrodes made of silver (Ag 92.5 g to Cu 7.5 g) fixed in a plastic tube filled by water which allows the use of two and four electrode setups. The admittance (reciprocal of impedance) was measured for different water sources (distilled, rainfall, mineral, river and tap water) using different frequencies between 50 Hz and 100 kHz. These measurements were taken twice, first with four electrodes and then with two electrodes of two modes (inner and outer electrodes). The results showed good correlation between the measured admittance and the conductivity of all the water sources and the best correlation was found at low frequencies between 50 Hz and 20 kHz. The highest efficiency can be achieved by using the four electrode system which allows circumventing the effect of the electrode impedance. This result makes the system efficient compared to traditional conductivity meters which usually require high frequencies for good operation.

Non-invasive, label-free assessment of membrane potential of living cells is still a challenging task. The theory linking membrane potential to the low frequency α dispersion exhibited by suspensions of spherical shelled particles (presenting a net charge distribution on the inner side of the shell) has been pioneered in our previous studies with emphasis on the permittivity spectra. Whereas α dispersion is related to a rather large variation exhibited by the permittivity spectrum, we report that the related decrement presented by the impedance magnitude spectrum is either extremely small, or occurs (for large cells) at very small frequencies (~mHz) explaining the lack of experimental bioimpedance data on the matter.

We stress that appropriate choice of the parameters (as revealed by the microscopic model) may enable access to membrane potential as well as to other relevant parameters when investigating living cells and charged lipid vesicles. We analyse the effect on the low frequency of the permittivity and impedance spectra of: I. Parameters pertaining to cell membrane i.e. (i) membrane potential (through the amount of the net charge on the inner side of the membrane), (ii) size of the cells/vesicles, (iii) conductivity of the membrane; II. Parameters of the extra cellular medium (viscosity and conductivity).

The applicability of the study has far reaching implications for basic (life) sciences (providing non-invasive access to the dynamics of relevant cell parameters) as well as for biosensing applications, e.g. assessment of cytotoxicity of a wide range of stimuli.

The Initial Systolic Time Interval (ISTI) has been defined as the time difference between the peak electrical and peak mechanical activity of the heart. ISTI is obtained from the electro-cardiogram and the impedance cardiogram. The response of ISTI while breathing at rest and to a deep breathing stimulus was studied in a group of patients suffering from Parkinson’s disease (PD) and a group of healthy control subjects. ISTI showed substantial variability during these manoeuvres. The tests showed that the variability of RR and ISTI was substantially different between PD patients and controls. It is hypothesized that in PD patients the sympathetic nervous system compensates for the loss of regulatory control function of the blood-pressure by the parasympathetic system. It is concluded that ISTI is a practical, additional and independent parameter that can be used to assist other tests in evaluating autonomic nervous control of the heart in PD patients.

Tools such as Simpleware ScanIP+FE and COMSOL Multiphysics allow us to gain a better understanding of bioimpedance measurements without actually doing the measurements. This tutorial will cover the steps needed to go from a 3D voxel data set to a model that can be used to simulate a transfer impedance measurement. Geometrical input data used in this tutorial are from MRI scan of a human thigh, which are converted to a mesh using Simpleware ScanIP+FE. The mesh is merged with electrical properties for the relevant tissues, and a simulation is done in COMSOL Multiphysics. Available numerical output data are transfer impedance, contribution from different tissues to final transfer impedance, and voltages at electrodes. Available volume output data are normal and reciprocal current densities, potential, sensitivity, and volume impedance sensitivity. The output data are presented as both numbers and graphs. The tutorial will be useful even if data from other sources such as VOXEL-MAN or CT scans are used.