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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 Py 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 Py values first increased and reached a plateau which lasted for 1 - 2 hours, before it decreased irreversibly. The time interval where Py value reached the maximum is consistent with reported viable/non-viable limits from histological analysis.

Electrical impedance spectroscopy (EIS) has been used as an adjunct to colposcopy for cervical cancer diagnosis for many years, Currently, the template match method is employed for EIS measurements analysis, where the measured EIS spectra are compared with the templates generated from three-dimensional finite element (FE) models of cancerous and non-cancerous cervical tissue, and the matches between the measured EIS spectra and the templates are then used to derive a score that indicates the association strength of the measured EIS to the High-Grade Cervical Intraepithelial Neoplasia (HG CIN). These FE models can be viewed as the computational versions of the associated physical tissue models. In this paper, the problem is revisited with an objective to develop a new method for EIS data analysis that might reveal the relationship between the change in the tissue structure due to disease and the change in the measured spectrum. This could provide us with important information to understand the histopathological mechanism that underpins the EIS-based HG CIN diagnostic decision making and the prognostic value of EIS for cervical cancer diagnosis. A further objective is to develop an alternative EIS data processing method for HG CIN detection that does not rely on physical models of tissues so as to facilitate extending the EIS technique to new medical diagnostic applications where the template spectra are not available. An EIS data-driven method was developed in this paper to achieve the above objectives, where the EIS data analysis for cervical cancer diagnosis and prognosis were formulated as the classification problems and a Cole model-based spectrum curve fitting approach was proposed to extract features from EIS readings for classification. Machine learning techniques were then used to build classification models with the selected features for cervical cancer diagnosis and evaluation of the prognostic value of the measured EIS. The interpretable classification models were developed with real EIS data sets, which enable us to associate the changes in the observed EIS and the risk of being HG CIN or developing HG CIN with the changes in tissue structure due to disease. The developed classification models were used for HG CIN detection and evaluation of the prognostic value of EIS and the results demonstrated the effectiveness of the developed method. The method developed is of long-term benefit for EIS–based cervical cancer diagnosis and, in conjunction with standard colposcopy, there is the potential for the developed method to provide a more effective and efficient patient management strategy for clinic practice.

A non-invasive method of measuring bioimpedance is presented to study the effect of moisturizing cream on human skin. A novel two-electrode system is developed to get electrical access at the area of interest on human skin. Controlled experiments are conducted for a duration of 47 days. Bioimpedance is measured by LCR meter in the frequency range of 1 Hz to 5 kHz. The measured impedance is then fitted with the Cole model and the relevant Cole parameters are extracted. Analysis of variance is performed on the Cole parameters to gain statistical relevance. It is found that one of the Cole parameters, namely the relaxation-time changes significantly due to the treatment of the skin with a moisturizing cream at more than 95% confidence level. The relaxation-time increases sharply during the treatment period and drops sharply in the post-treatment period. The effectiveness of the two types of cream is studied. The gender distinguishability during the application of a moisturizing cream is also studied. A very generic bioimpedance measurement method to assess the physiological condition of local skin is demonstrated here and the method has potential application in human skin related diseases and treatments.

This article belongs to the Special Issue Body Sensors Networks for E-Health Applications., 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., This research was funded in part by the “Fondo de Investigaciones Sanitarias” (Instituto de Salud Carlos III, Spain) under Grants PI15/00306, in part by the “Fundación Progreso y Salud” (Government of Andalucía, Spain) under Grant PIN-0394-2017, in part by “Fundación Mutua Madrileña” under grant VÍA-RENAL, and in part by the “Eurostars Programme”, European Commission, under Grant “FRAIL”.

The objective of this work is to develop a technique for filtering parasitic effects from the impedance spectra (IS) measured in biological material phantoms. IS data are contaminated with unexpected capacitive and inductive effects from cable, input/output amplifiers capacitances, electrode polarization, temperature and contact pressure when collecting data. It is proposed a model which contains an RLC-network in series with the Cole model (RSC), then called RLC-Cole. It was built four circuits composed by resistors, capacitors and inductors. An impedance analyzer (HF2IS) was used to perform the measurements in the frequency range of 1 to 3000 kHz. Data were fitted into the model and comparisons to the nominal values were made. In order to validate the proposed model, a gelatin phantom and a chicken breast muscle impedance spectra were also collected and analyzed. After filtering, Cole fitting was performed. Results showed a maximum root-mean-square error of 1% for the circuits, 2.63% for the gelatin phantom, whereas 2.01% for the chicken breast. The RLC-Cole model could significantly remove parasitic effects out of a tissue impedance spectrum measured by a 4-point electrode probe. This may be highly important in EIS systems whose objective is to discriminate a normal tissue from a cancerous one.

Equivalence of information from single versus multiple frequency bioimpedance vector analysis in hemodialysis. Background In suspended cells, low-frequency current only passes through extracellular fluids, while current at higher frequencies passes through extra- and intracellular fluids. Cells in soft tissues are in contact with each other, which causes tissue anisotropy, meaning that impedance changes along different cell directions, with part of low-frequency current also passing through cells. Hence, equivalent information on body impedance change is expected at all frequencies, which we proved in a dynamic condition of fluid removal with hemodialysis. Methods We performed whole-body impedance spectroscopy (496 frequencies from 4 to 1024kHz, SEAC SFB3 analyzer; Brisbane, Australia) before and during fluid removal (0, 60, 120, 180min, 2.5kg) in 67 hemodialysis patients. With increasing current frequency, resistance (R) decreases and reactance (Xc) moves along the Cole's semicircle on the R-Xc plane. Results The Cole's semicircles progressively enlarged and moved to the right on the R-Xc plane following fluid removal (increase in both R and Xc values at any given frequency). Xc values at 5kHz (expected values close to 0 Ohm) were 70% of the maximun Xc, indicating an intracellular current flows at low frequencies. The correlation coefficient between R at 50kHz (standard frequency) and R at other frequencies ranged from 0.96 to 0.99, and the correlation coefficient between Xc at 50kHz and Xc at other frequencies at any time point ranged from 0.65 to 0.99. Conclusion From high Xc values at low frequency, tissue anisotropy is inferred. Intra- and extracellular current flow causes equivalence of information based on functions of R and Xc measurements made at 50kHz versus other frequencies.