Volume 10 (2019): Issue 1 (January 2019)

The first issue of the Journal of Electrical Bioimpedance saw the light in 2010 by the personal initiative of two men from the University of Oslo, Prof. Sverre Grimnes and Prof. Ørjan G. Martinsen, who has been the editor-in-chief of our Journal during all these ten years. With the sense of gratitude, we hope that he continues his persistent work also during the approaching next decade in the new conditions with a growing number of bioimpedance publications worldwide. However, every success creates new problems, some of which are discussed below.

Image reconstruction in EIT is an inverse problem, which is ill posed and hence needs regularization. Regularization brings stability to reconstructed EIT image with respect to noise in the measured data. But this is at the cost of smoothening of sharp edges and high curvature details of shapes in the image, affecting the quality. We propose a novel iterative regularization method based on detection of probable location of the inclusion, for locally relaxing the regularization by appropriate amount, to overcome this problem. Local relaxation around inclusion allows reconstruction of its high curvature shape details or sharp features at the same time giving benefits of higher regularization in remaining areas of the image. The proposed method called DeTER is implemented using a small plug-in to EIDORS (Electrical Impedance and Diffused Optical Reconstruction Software) in a MATLAB environment. Parameters like CNR, correlation coefficients of shape descriptor functions and relative size of reconstructed targets have been computed to evaluate the effectiveness of the technique. The performance of DeTER is tested and verified on simulated data added with Gaussian noise for inclusions of different shapes. Both conducting and nonconducting inclusions are considered. The method is validated using open EIT data shared by ‘Finnish inverse problem society’ and also by reconstructing image of internal void of a papaya fruit from the data acquired by an EIT system developed in our laboratory. The reconstructed images corresponding to the open EIT data clearly show the shapes similar to original objects, with sharp edges and curvature details. The shapes obtained in the papaya image are shown to correspond to the actual void using shape descriptor function. The results demonstrate that the proposed method enhances the sharp features in the reconstructed image with few iterations without causing geometric distortions like smoothening or rounding of the edges.

We determine the in-vivo dielectric properties—resistivity and relative permittivity—of living epidermis and dermis of human skin soaked with a physiological saline solution for one minute between 1 kHz and 1 MHz. This is done by fitting approximate analytical solutions of a mechanistic model for the transport of charges in these layers to a training set comprising impedance measurements at two depth settings on stripped skin on the volar forearm of 24 young subjects. Here, the depth settings are obtained by varying the voltage at a second inject on the electrical-impedance-spectroscopy probe. The model and the dielectric properties are validated with a test set for a third depth setting with overall good agreement. In addition, the means and standard deviations of the thicknesses of living epidermis and dermis are estimated from a literature review as 61±7 μm and 1.0±0.2 mm respectively. Furthermore, extensions to resolve the skin layers in more detail are suggested.

The relation between a biological process and the changes in passive electrical properties of the tissue is often non-linear, in which developing prediction models based on bioimpedance spectra is not trivial. Relevant information on tissue status may also lie in characteristic developments in the bioimpedance spectra over time, often neglected by conventional methods. The aim of this study was to explore possibilities in machine learning methods for time series of bioimpedance spectra, where we used organ ischemia as an example. Based on published data on the development of the bioimpedance spectrum during liver ischemia, a simulation model was made and used to generate sets of synthetic data with different levels of organ-to-organ variation, measurement noise and drift. Three types of artificial neural networks were employed in learning to predict the ischemic duration, based on the simulated datasets. The simulated prediction performance was very dependent on the amount of training examples, the organ-to-organ variation and the selection of input variables from the bioimpedance spectrum. The performance was also affected by noise and drift in the measurement, but a recurrent neural network with long short-term memory units could obtain good predictions even on noisy and drifting measurements. This approach may be relevant for further exploration on several applications of bioimpedance having the purpose of predicting a biological state based on spectra measured over time.

The purpose of this paper is to identify differences between abnormal and normal lung signals gathered by an EIT device, which is a new, non-invasive system that seeks the electrical conductivity and permittivity inside a body. Lung performances in patients are investigated using Phase Space Mapping technique on Electrical EIT signals. The database used in this paper contains 82 registered records of 52 individuals with proper lung volume. The results of this paper show that as the delay parameter (τ) increases, the SD1 parameter of phase space mapping indicates a significant difference between normal and abnormal lung volumes. The value of the SD1 parameter with τ = 6 in the case that the lung volume is in a normal condition is 342.57 ± 32.75 while it is 156.71 ± 26.01 in non-optimal mode. This method can be used to identify the patients’ lung volumes with chronic respiratory illnesses and is an accurate assessment of the diverse methods to treat respiratory system illnesses in addition to saving various therapeutic costs and dangerous consequences that are likely to occur by using improper treatment methods. It can also reduce the required treatment durations.

This paper describes a new combined impedance plethysmographic (IPG) and electrical bioimpedance spectroscopic (BIS) instrument and software that will allow noninvasive real-time measurement of segmental blood flow, intracellular, interstitial, and intravascular volume changes during various fluid management procedures. The impedance device can be operated either as a fixed frequency IPG for the quantification of segmental blood flow and hemodynamics or as a multi-frequency BIS for the recording of intracellular and extracellular resistances at 40 discrete input frequencies. The extracellular volume is then deconvoluted to obtain its intravascular and interstitial component volumes as functions of elapsed time. The purpose of this paper is to describe this instrumentation and to demonstrate the information that can be obtained by using it to monitor segmental compartment volume responses of a pig model during simulated hemorrhage and resuscitation. Such information may prove valuable in the diagnosis and management of rapid changes in the body fluid balance and various clinical treatments.

Primary recognition of heart diseases by exploiting computer aided diagnosis (CAD) machines, decreases the vast rate of fatality among cardiac patients. Recognition of heart abnormalities is a staggering task because the low changes in ECG signals may not be exactly specified with eyesight. In this paper, an efficient approach for ECG arrhythmia diagnosis is proposed based on a combination of discrete wavelet transform and higher order statistics feature extraction and entropy based feature selection methods. Using the neural network and support vector machine, five classes of heartbeat categories are classified. Applying the neural network and support vector machine method, our proposed system is able to classify the arrhythmia classes with high accuracy (99.83%) and (99.03%), respectively. The advantage of the presented procedure has been experimentally demonstrated compared to the other recently presented methods in terms of accuracy.

The feasibility of bioimpedance spectroscopy (BIS) techniques for monitoring intradialytic changes in body fluids is advancing. The aim of this study was to compare the knee-to-knee (kkBIS) with the traditional whole-body (whBIS) with respect to continuous assessment of fluid volume status in hemodialysis patients. Twenty patients divided into two groups, hemodynamically stable and unstable, were recruited. Bioimpedance data from two different electrodes configurations (hand-to-foot and knee-to-knee) were collected and retrospectively analysed. A good correlation between the two methods with respect to changes in extracellular resistance (R_e) and R_e normalized for ultrafiltration volume (ΔR_e/UFV) with p < 0.001 was observed. The relationship between relative change (%) in ΔR_e and that in patient weight was most notable with kkBIS (4.82 ± 3.31 %/kg) in comparison to whBIS (3.69 ± 2.90 %/kg) in unstable patients. Furthermore, results based on kkBIS showed a reduced ability of the thigh compartments to keep up with the volume changes in the trunk for unstable patients. kkBIS provided a comparable sensitivity to whBIS even in patients at risk of intradialytic hypotension while avoiding the need for the complex implementation imposed by whBIS or other configurations.

In December of 2018 I published my consolidated findings of a closed-form description of propagated signaling phenomena in the membrane of an axon [1]. Those results demonstrate how intracellular conductance, the thermodynamics of magnetization, and current modulation, function together in generating an action potential in a unified differential equation. At present, I report on a subsequent finding within this model. Namely, evidence of quantized magnetic flux Φ₀ in an axon.

Spontaneous fluctuations in electrodermal responses are known as nonspecific electrodermal responses (NS.EDRs). The use of NS.EDRs as a tool in applied psychophysiological research has resulted in a variety of publications. NS.EDRs are examined separately as associated with the (as a biomarker of) levels of anxiety. The aim of this study was to compare changes (in terms of amplitude, frequency and time components) in NS.EDRs at two different (pre and post of an external stimulus) resting phases. NS.EDRs (nonspecific skin conductance responses (NS.SCRs), nonspecific skin potential responses (NS.SPRs), and nonspecific skin susceptance responses (NS.SSRs)) were recorded from 50 apparently healthy volunteers simultaneously at the same skin area. They were scored as NS.SCRs and NS.SSRs for changes greater than 0.02 μS and NS.SPRs greater than 0.02 mV. It was found that NS.EDRs, in particular NS.SCRs and NS.SPRs, were significantly changed in the second resting period, following the specific stimulus. More specifically, the amplitude of NS.EDRs were significantly decreased for NS.SCRs (p<0.001) and for NS.SPRs (p<0.005), but NS.SSRs remained stable. Moreover, the rise time of NS.SCRs was decreased in the second resting time. Furthermore, the frequency of responses was also changed. The computed NS.EDRs, in particular NS.SCRs and NS.SPRs could be of psychological interest and be used to study the electrodermal responses in detail. NS.SSRs were found to be robust with respect to nonspecific stimuli at various relaxation periods and their role was found to be less important in analysis of NS.EDRs in comparison to NS.SCRs and NS.SPRs at low frequency (20 Hz AC current). This should be considered in analysis of NS.EDRs. The computed NS.EDRs, especially NS.SCRs and NS.SPRs may be used as a useful measure of arousal due to their fast response and sensitivity to nonspecific stimuli and may also be used in assessment of individual differences.

For probing deep organs of the body using electrical impedance, the conventional method is to use Electrical Impedance Tomography (EIT). However, this would be a sophisticated machine and will be very expensive when a full 3D EIT is developed in the future. Furthermore, for most low income countries such expensive devices may not deliver the benefits to a large number of people. Therefore, this paper suggests the use of simpler techniques like Tetrapolar Impedance Measurement (TPIM) or Focused Impedance Method (FIM) in probing deeper organs. Following a method suggested earlier by one of the authors, this paper studies the possibility of using TPIM and FIM for the stomach. Using a simplified model of the human trunk with an embedded stomach, a finite element simulation package, COMSOL, was used to obtain transfer impedance values and percentage contribution of the stomach region in the total impedance. For this work, judicious placement of electrodes through qualitative visualizations based on point sensitivity equations and equipotential concepts were made, which showed that reasonable contribution of the stomach region is possible through the use of TPIM and FIM. The contributions were a little over 20% which is of similar order of the cross-sectional area percentage of the stomach with respect to that of the trunk. For the case where the conductivity of the stomach region was assumed about 4 times higher, the contributions increased to about 38%. Through further studies this proposed methods may contribute greatly in the study of deeper organs of the body.

Non-linear electrical properties of a (biological) tissue can be revealed by non-linear electrical measurements, which means that the applied stimulus itself affects the measurement. If resulting voltage–current plots exhibit pinched hysteresis loops, the underlying tissue may be classified as a memristor, a state dependent resistor. The aloe vera plant and apples have been found to be memristors. However, polarization processes on the electrodes are also non-linear and may affect the measurement. Apples and aloe vera conduct electrical current very well and it is likely that the recordings are actually dominated by the polarization impedance of the electrodes. Here, we study the non-linear properties of aloe vera and apples with two different measurement electrode types. Furthermore, we measured also on the extracted liquids from one aloe vera leaf and one apple, leading to similar results. We concluded, unlike previous studies on these subjects, that the memristive properties originate from electrochemical reactions on the electrodes rather than the apples or aloe vera themselves.

Overall survival of oncologic patients is strongly influenced by the incidence of malnutrition, with subsequent loss of muscle mass until sarcopenia. In this respect, the assessment of body composition has a pivotal role in order to manage the clinical consequences of muscle loss.

Electrical impedance tomography (EIT) has a large potential as a two dimensional imaging technique and is gaining attention among researchers across various fields of engineering. Beamforming techniques stem from the array signal processing field and is used for spatial filtering of array data to evaluate the location of objects. In this work the circular electrodes are treated as an array of sensors and beamforming technique is used to localize the object(s) in an electrical field. The conductivity distributions within a test tank is obtained by an EIT system in terms of electrode voltages. These voltages are then interpolated using elliptic partial differential equations. Finally, a narrowband beamformer detects the peak in the output response signal to localize the test object(s). Test results show that the beamforming technique can be used as a secondary method that may provide complementary information about accurate position of the test object(s) using an eight electrode EIT system. This method could possibly open new avenues for spatial EIT data filtering techniques with an understanding that the inverse problem is more likely considered here as a source localization algorithm instead as an image reconstruction algorithm.

The objective of this study was to determine the potential value of electrical impedance myography (EIM) for assessing lumbosacral paraspinal muscle (LPM) condition in lower back pain (LBP) patients. Standard methods for assessing the condition of LPMs, such as magnetic resonance imaging, are inconvenient and expensive. One tool that could be useful for this purpose is electrical impedance myography (EIM) a technique that can be performed rapidly at the bedside. After undergoing a screening history and examination, subjects were studied with the mView EIM device (Myolex, Inc, Boston). Bilateral LPMs were measured three times each and the two closest sets of measurements averaged on each side. Data analysis included non-parametric two-group comparisons between healthy subjects and back pain patients, receiver-operating curve analyses, and correlation analyses to age and body mass index. A total of 86 healthy individuals (median age (interquartile range) (IQR), 45.5 years (30.3–56.0 years), 42 men, 44 women) and 47 LBP (median age 51.0 year (39.5–57.5) years, 21 men, 26 women) were enrolled. Median EIM 100kHz phase was lower in the LBP patients (9.3°(IQR 8.4°–10.6°) versus 11.4°(IQR 9.4°–13.0°), p = 0.0007). Significantly increased normalized side-to-side differences were present for all three EIM variables (e.g., median 100 kHz phase 0.15 (IQR 0.07–0.31 in LBP patients versus 0.09 (IQR 0.04–0.17) in healthy individuals). A significant correlation between 100 kHz EIM phase and reactance was found with age (R_spearman=−0.46, P=0.0002 and R_spearman=−0.440, P=0.0003) but not for resistance. This study provides early evidence supporting that EIM has the potential to serve as a useful tool for evaluating the condition of LPMs.

A circuit is presented that enables measurement of skin electrical conductance, susceptance, and potential simultaneously beneath the same monopolar electrode. Example measurements are shown to confirm the function of the circuit. The measurements are also in accordance with earlier findings that changes in skin conductance and potential do not always correspond and hence contain unique information.

An electrical measurement is non-linear when it is affected by the applied stimulus, i.e. when the measured phenomenon changes with amplitude. If pinched hysteresis loops can be observed in the voltage current representation, the underlying tissue can be classified as a memristor. Several biological memristors have been published, like human skin and apples. However, changes in the polarization impedance of electrodes may also cause pinched hysteresis loops. The question whether the reported biological memristors are real or whether the results just reflect changes in the polarization impedance arises. If the impedance of the measured object is close to or smaller than the polarization impedance of the used electrodes, the latter may dominate the measurement.

In this study, we investigated the non-linear electrical properties of silver/silver chloride electrodes in a sodium chloride solution that has a similar concentration as human sweat and compared these to results from human skin. First of all, we found that silver/silver chloride electrodes in sodium chloride solution can be classified as memristors. However, the currents obtained from the sodium chloride solution are much higher than the currents recorded from human skin and there is a qualitative difference in the pinched hysteresis loops in both cases. We can conclude that the non-linear electrical measurements with silver/silver chloride on human skin are actually dominated by the skin and we can confirm that the human skin memristor really exists.

Electrical impedance spectroscopy (EIS) measurements on cells is a proven method to assess stem cell proliferation and differentiation. Cell regenerative medicine (CRM) is an emerging field where the need to develop and deploy stem cell assessment techniques is paramount as experimental treatments reach pre-clinical and clinical stages. However, EIS measurements on cells is a method requiring extensive post-processing and analysis. As a contribution to address this concern, we developed three machine learning models for three different stem cell lines able to classify the measured data as proliferation or differentiation laying the stone for future studies on using machine learning to profile EIS measurements on stem cells spectra.

Sixteen volunteers each drank 700 ml sugar-containing soft drink during two successive periods and the blood sugar was measured at 10 min intervals together with electrical impedance spectroscopy and near infrared spectroscopy (NIR). A maximum correlation of 0.46 was found for the electrical measurements but no clear separation between low and high blood glucose levels were found in the NIR measurements. The latter was attributed to the experimental design where the NIR probe was removed from the skin between each measurement.

Impedance cardiography (ICG) is a non-invasive method of hemodynamic measurement, mostly known for estimation of stroke volume and cardiac output based on characteristic features of the signal. Compared with electrocardiography, the knowledge on the morphology of the ICG signal is scarce, especially with respect to age-dependent changes in ICG waveforms. Based on recordings from ten younger (20–29 years) and ten older (60–79) healthy human subjects after three different levels of physical activity, the typical interbeat ICG waveforms were derived based on ensemble averages. Comparison of these waveforms between the age groups indicates the following differences: a later initial upward deflection for the younger group, an additional hump in the waveform from many older subjects not presented in the younger group, and a more pronounced second wave in the younger group. The explanation for these differences is not clear, but may be related to arterial stiffness. Further studies are suggested to determine whether these morphological differences have clinical value.