Improved Cole parameter extraction based on the least absolute deviation method

Opto-electromechanical quantification of epithelial barrier function in injured and healthy airway tissues

The airway epithelium lining the luminal surface of the respiratory tract creates a protective barrier that ensures maintenance of tissue homeostasis and prevention of respiratory diseases. The airway epithelium, unfortunately, is frequently injured by inhaled toxic materials, trauma, or medical procedures. Substantial or repeated airway epithelial injury can lead to dysregulated intrinsic repair pathways and aberrant tissue remodeling that can lead to dysfunctional airway epithelium. While disruption in the epithelial integrity is directly linked to degraded epithelial barrier function, the correlation between the structure and function of the airway epithelium remains elusive. In this study, we quantified the impact of acutely induced airway epithelium injury on disruption of the epithelial barrier functions. By monitoring alternation of the flow motions and tissue bioimpedance at local injury site, degradation of the epithelial functions, including mucociliary clearance and tight/adherens junction formation, were accurately determined with a high spatiotemporal resolution. Computational models that can simulate and predict the disruption of the mucociliary flow and airway tissue bioimpedance have been generated to assist interpretation of the experimental results. Collectively, findings of this study advance our knowledge of the structure-function relationships of the airway epithelium that can promote development of efficient and accurate diagnosis of airway tissue injury.

Bioimpedance-based Authentication of Defrosted Versus Fresh Pork at the End of Refrigerated Shelf Life

Correct food labeling is a legal requirement and helps consumers to make informed purchasing choices. Mislabeling defrosted meat as fresh is illegal in the EU. However, there are no standardized technologies to authenticate fresh versus defrosted meat. We address this by testing if bioimpedance-based measurements can separate defrosted meat from refrigerated-only meat at the end of shelf life, i.e., when also fresh meat shows deterioration. Pork sirloin samples from 20 pigs were first tested at 12 days postmortem ('fresh group'). This time point was chosen to represent a typical use-by date for refrigerated storage of fresh pork. Then, all samples were transferred to a -24°C freezer for 3 days and thawed for 2 days before final testing ('frozen-thawed group'). Bioimpedance analyses (BIA) were done in a frequency range of [10²-10⁶ Hz]. Weight, pH and electrode positioning were assessed to test for potential confounding effects. Statistics for treatment dependent differences were based on the established P_y parameter and phase angle, which were extracted from the BI spectra. We found that using bioimpedance testing with tetrapolar electrodes, P_y and phase angle allowed almost complete separation of fresh and previously frozen samples. However, within the whole sample population, there was some overlap between the spectra of fresh and frozen samples. Yet, based on P_y, only one fresh sample (5% of N_total=20) fell in the lowest P_y class with all the frozen samples. We used a multifactorial design that allowed to test the effects of potential confounding factors, such as electrode positioning and meat quality parameters. We found a relatively low explained variance for the P_y parameter, indicating that confounding effects from other factors or quality defects in fresh pork may affect the detection capacity of bioimpedance-based authentication of fresh pork. Our data, therefore, suggest that reliable fresh-label authentication with bioimpedance testing should be based on testing a small number of samples to represent a specific lot of pork that is to be inspected.

Iterative method to obtain semi-circle variables from bioimpedance measurements for Cole's Modeling

Bioimpedance Spectroscopy measurements and Cole-Cole models are commonly used to characterize biological systems. Cole-Cole model parameters may be obtained by fitting the measured bioimpedance data into a semicircle. This work proposes an iterative method to approximate a bioimpedance dataset to a Cole-Cole model analysis using only three points. The performance of the proposed method was compared against similar methods reported in a recent publication; our proposal presents greater efficiency (87.5%) and lower mean error (0.022) than the compared methods. The main contribution of the proposed method is that its performance does not rely on the user's technical knowledge, neither does it on the instrument used to perform the measurements, while the compared methods do.Clinical Relevance- Our proposal is an efficient unsupervised iterative method to acquire the clinically-relevant parameters from a Cole-Cole analysis from a given bioimpedance spectroscopy dataset, eliminating the need for the user to have prior technical knowledge on bioimpedance, thus, furthering the use of bioimpedance technology in the clinical point-of-care.

Optimal charging of fractional-order circuits with Cuckoo search

INTRODUCTION

Optimal charging of RC circuits is a well-studied problem in the integer-order domain due to its importance from economic and system temperature hazards perspectives. However, the fractional-order counterpart of this problem requires investigation.

OBJECTIVES

This study aims to find approximate solutions of the most energy-efficient input charging function in fractional-order RC circuits.

METHODS

This paper uses a meta-heuristic optimization technique called Cuckoo search optimizer to attain the maximum charging efficiency of three common fractional-order RC circuits. An analytical expression of the fractional capacitor voltage is suggested such that it satisfies the boundary conditions of the optimal charging problem. The problem is formulated as a fractional-order calculus of variations problem with compositional functional. The numerical solutions are obtained with the meta-heuristic optimization algorithm's help to avoid the complexities of the analytical approach.

RESULTS

he efficiency surfaces and input voltage charging curves are discussed for fractional-order in the range 0.5 < α ≤ 1 .

CONCLUSION

The optimized charging function can approximate the optimal charging curve using at most 4 terms. The charging time and the resistive parameters have the most dominant effect on charging efficiency at constant fractional-order α .

Programmable constant phase element realization with crossbar arrays

INTRODUCTION

Constant Phase Elements (CPEs) have been widely used in many applications due to the extra degree of freedom, which offers new responses and behaviors.

OBJECTIVES

This paper proposes a new programmable CPE realization using resistive crossbar arrays. By programming the resistive devices, different CPEs can be obtained.

METHODS

The proposed realization can be approximated as a weighted sum of low and high pass filters having the same cut-off frequency (i.e., Lapicque model). The closed-form approximation expression is derived, and then the Flower Pollination Algorithm (FPA) is used to find the optimal values of the network components.

RESULTS

Different design examples are given over the frequency range of 106-109 rad/sec to prove the ability of this realization achieving any fractional order with less than 5% relative error in both phase and pseudo-capacitance. Monte-Carlo simulations are performed to evaluate the sensitivity of the proposed realization against device variability. In addition, multiple CPEs can be designed at the same time by utilizing the multiple ports of the crossbar array. The proposed realization is compared with two other state-of-art realizations showing comparable results as standalone realization and within fractional-order relaxation oscillator application.

CONCLUSION

The proposed crossbar realization has proven its ability to realize any CPE with acceptable error. In addition, this multiple-port design offers high flexibility and on-the-fly switching of the CPE.

A novel method for estimating the fractional Cole impedance model using single-frequency DC-biased sinusoidal excitation

OBJECTIVE

The Cole model is a widely used fractional circuit model in electrical bioimpedance applications for evaluating the content and status of biological tissues and fluids. Existing methods for estimating the Cole impedance parameters are often based on multi-frequency data obtained from stepped-sine measurements fitted using a complex non-linear least square (CNLS) algorithm. Newly emerged numerical methods from the magnitude of electrical bio-impedance data-only do not need CNLS fitting, but they still require multi-frequency stepped-sine data. This study proposes a novel approach to estimating the Cole impedance parameters that combines a numerical and time-domain fitting method based on a single-frequency DC-biased sinusoidal current excitation.

APPROACH

First, the transient and steady-state voltage response along with the current excitation are acquired in electrical bio-impedance measurement. From the sampled data, a numerical method is applied to provide the initial estimation of the Cole impedance parameters, which are then used in a time-domain iterative fitting algorithm.

RESULTS

The accuracy of the algorithm proposed is tested with noisy electrical bio-impedance simulations. The maximum relative error of the estimated Cole impedance parameters is 1% considering 2% (34 dB) additive Gaussian noise. Experimental measurements performed on a 2R-1C circuit and some fruit samples show a mean difference less than 1% and 5% respectively compared to the Cole impedance parameters estimated from a commercial electrical bio-impedance analyzer performing stepped-sine measurements and CNLS fitting.

SIGNIFICANCE

This is the first method that allows estimating the Cole impedance parameters from single-frequency electrical bio-impedance data. The approach presented could find broad use in many applications, including single-frequency body impedance analysis.

Assessing Ischemic Injury in Human Intestine Ex Vivo with Electrical Impedance Spectroscopy

Electrical impedance spectroscopy is a well-established tool for monitoring changes in the electrical properties of tissue. Most tissue and organ types have been investigated in various studies. As for the small intestine, there are several published studies conducted on pig and rat models. This study investigates the changes in passive electrical properties of the complete wall of the human intestine non-invasively during ischemia. We aim to use the passive electrical properties to assess intestinal viability. The bioimpedance measurements were performed using a two-electrode set-up with a Solartron 1260 Impedance/gain-phase analyser. The small intestinal samples were resected from patients who underwent pancreaticoduodenectomy. Impedance measurements were conducted following resection by placing the electrodes on the surface of the intestine. A voltage was applied across the intestinal sample and the measured electrical impedance was obtained in the ZPlot software. Impedance data were further fitted into a Cole model to obtain the Cole parameters. The P_y value was calculated from the extracted Cole parameters and used to assess the cell membrane integrity, thus evaluate the intestinal viability. Eight small intestinal segments from different patients were used in this study and impedance measurements were performed once an hour for a ten-hour period. One hour after resection, the impedance decreased, then increased the next two hours, before decreasing until the end of the experiment. For all the intestinal segments, the P_y values first increased and reached a plateau which lasted for 1 - 2 hours, before it decreased irreversibly. The time interval where P_y value reached the maximum is consistent with reported viable/non-viable limits from histological analysis.

Smart Bioimpedance Spectroscopy Device for Body Composition Estimation

The purpose of this work is to describe a first approach to a smart bioimpedance spectroscopy device for its application to the estimation of body composition. The proposed device is capable of carrying out bioimpedance measurements in multiple configurable frequencies, processing the data to obtain the modulus and the bioimpedance phase in each of the frequencies, and transmitting the processed information wirelessly. Another novelty of this work is a new algorithm for the identification of Cole model parameters, which is the basis of body composition estimation through bioimpedance spectroscopy analysis. Against other proposals, the main advantages of the proposed method are its robustness against parasitic effects by employing an extended version of Cole model with phase delay and three dispersions, its simplicity and low computational load. The results obtained in a validation study with respiratory patients show the accuracy and feasibility of the proposed technology for bioimpedance measurements. The precision and validity of the algorithm was also proven in a validation study with peritoneal dialysis patients. The proposed method was the most accurate compared with other existing algorithms. Moreover, in those cases affected by parasitic effects the proposed algorithm provided better approximations to the bioimpedance values than a reference device.

Evaluation on Phantoms of the Feasibility of a Smart Bra to Detect Breast Cancer in Young Adults

Breast cancer is the most common cancer observed in women. Although mammography is a recognized method, it remains ionizing and cannot be used routinely or in young adults, leaving up to two years between two diagnoses. Prior to validation on human subjects, this study aims to validate on phantoms the feasibility of quantifying breast density and detecting breast cancer tumors using a smart bra in young women. Six phantoms with various densities and seven phantoms with various volumes of modelized tumor were prepared and measured with a smart bra, including an electrophysiological module. There was a significant difference between the "healthy phantoms" and the "tumor phantoms" with P(Student) = 0.008 (Shapiro-Wilk p = 0.846, samples follow a normal distribution; Fisher variance test, p = 0.287). In addition, this study seems to indicate the possibility of discriminating various types of tumorous and healthy breast tissue using a smart bra, in high density breast. However, a new study on a large sample of human subjects will be required to generate new models, including resistive, capacitive, and other sensor parameters versus reference data collected from imaging.

Using bioimpedance spectroscopy parameters as real-time feedback during tDCS

An exploratory analysis is carried out to investigate the feasibility of using BioImpedance Spectroscopy (BIS) parameters, measured on scalp, as real-time feedback during Transcranial Direct Current Stimulation (tDCS). TDCS is shown to be a potential treatment for neurological disorders. However, this technique is not considered as a reliable clinical treatment, due to the lack of a measurable indicator of treatment efficacy. Although the voltage that is applied on the head is very simple to measure during a tDCS session, changes of voltage are difficult to interpret in terms of variables that affect clinical outcome. BIS parameters are considered as potential feedback parameters, because: 1) they are shown to be associated with the DC voltage applied on the head, 2) they are interpretable in terms of conductive and capacitive properties of head tissues, 3) physical interpretation of BIS measurements makes them prone to be adjusted by clinically controllable variables, 4) BIS parameters are measurable in a cost-effective and safe way and do not interfere with DC stimulation. This research indicates that a quadratic regression model can predict the DC voltage between anode and cathode based on parameters extracted from BIS measurements. These parameters are extracted by fitting the measured BIS spectra to an equivalent electrical circuit model. The effect of clinical tDCS variables on BIS parameters needs to be investigated in future works. This work suggests that BIS is a potential method to be used for monitoring a tDCS session in order to adjust, tailor, or personalize tDCS treatment protocols.

Bioimpedance spectroscopy method for investigating changes to intracranial dose during transcranial direct current stimulation

Tissue resistance changes upon application of DC current. We posit that in a similar fashion, that scalp and skull resistances during trancranial direct current stimulation (tDCS) are variable, resulting in changes to intracranial dose. Transcranial magnetic stimulation (TMS), electoencephelogram (EEG), functional magnetic resonance imaging (fMRI), proton magnetic resonance spectroscopy ((1)H MRS) and functional near infrared spectroscopy (fNIRS) are technologies used to measure individual neural response to tDCS. These technologies are complex and may not be directly correlated to intracranial dose. We therefore present a bioimpedance spectroscopy method of measuring changes to the intracranial dose in vivo. Scalp resistance changes are measured during tDCS. Current flow through the scalp is calculated as the ratio of voltage measured on the scalp and scalp resistance. Variation of intracranial current is indirectly calculated from changes in the current shunted through the scalp. We thus demonstrate a novel methodology of on-line monitoring of scalp resistance and current as an objective feedback of estimated individual tDCS dose.