rss_2.0Journal of Electrical Bioimpedance FeedSciendo RSS Feed for Journal of Electrical Bioimpedancehttps://sciendo.com/journal/JOEBhttps://www.sciendo.comJournal of Electrical Bioimpedance Feedhttps://sciendo-parsed.s3.eu-central-1.amazonaws.com/65b92df1b81b0e1a1e5d179a/cover-image.jpghttps://sciendo.com/journal/JOEB140216Evaluation of the effect of several moisturizing creams using the low frequency electrical susceptance approachhttps://sciendo.com/article/10.2478/joeb-2024-0002<abstract> <title style='display:none'>Abstract</title> <p>Moisturizers are cosmetic compounds designed to increase the moisture content of the skin. There are many types of these products in the market making it difficult for consumers to select the most effective moisturizer according to their age and gender. Hence, the aim of this study was to evaluate the effects of different moisturizers on skin hydration as well as to figure out any dependencies of the effects of these products on age or gender-related differences. We investigated the short-term moisturizing effects of five different skin moisturizers on 60 participants by using a low frequency electrical instrument. Skin surface susceptance was recorded and compared before and after the application of moisturizers. Statistically significant differences were observed in the moisturizing effect among different types of products. However, with respect to gender and age differences, there were insignificant differences in the effects of the moisturizers. Results of this study suggest that some types of moisturizers that exist in the markets are not as effective as required, which calls for a further evaluation of the moisturizers before entering markets and offering them for sale. In addition, findings suggest that gender or age differences are perhaps not important to consider in the application of moisturizers.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2024-00022024-02-26T00:00:00.000+00:00Electrical bioimpedance in the era of artificial intelligencehttps://sciendo.com/article/10.2478/joeb-2024-0001ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2024-00012024-01-26T00:00:00.000+00:00Smart needle electrical bioimpedance to provide information on needle tip relationship to target nerve prior to local anesthetic deposition in peripheral nerve block (USgPNB) procedureshttps://sciendo.com/article/10.2478/joeb-2023-0007<abstract> <title style='display:none'>Abstract</title> <p>Ultrasound guided peripheral nerve block (USgPNB) refers to anaesthetic techniques to deposit local anesthetic next to nerves, permitting painful surgery without necessitating general anesthesia. Needle tip position prior to local anesthetic deposition is a key determinant of block success and safety. Nerve puncture and intra-neural injection of local anesthetic can cause permanent nerve injury. Currently ultrasound guidance is not sufficiently sensitive to reliably detect needle to nerve proximity. Feedback with bioimpedance data from the smart needle tip might provide the anesthetist with information as to the relationship between the needle tip and the target nerve prior to local anesthetic deposition.</p> <p>Bioimpedance using a smart needle integrated with a two-electrode impedance sensor has been developed to determine needle to nerve proximity during USgPNB. Having obtained all necessary ethical and regulatory approvals, <italic>in vivo</italic> data on brachial plexus, vagus, femoral and sciatic nerves were obtained from seven pig models using the smart needle bioimpedance system. The excision and histological analysis of above peripheral nerves and observation of the architecture and structure of nerves by means of histology allow the calculation of the ratios of connective tissue to neural tissue to determine the influence of this variable on absolute impedance. The ratio results give extra clinical data and explain the hetrogeneity of impedance data in the pig models and the hypothesis that connective tissue with intra-neural fat has higher impedance than neural tissue.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2023-00072023-12-31T00:00:00.000+00:00Detection of physiological concentrations of GABA using dielectric spectroscopy - A pilot studyhttps://sciendo.com/article/10.2478/joeb-2023-0006<abstract> <title style='display:none'>Abstract</title> <p>Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter that is present at a relatively low level throughout the normal adult human brain. Abnormal GABA levels are found in people with neurodegenerative disorders such as Parkinson’s disease, epilepsy, schizophrenia, depression, and others. Being able to measure the GABA concentration would be beneficial for patient groups with fluctuating GABA levels for better diagnosis and treatment. In this study, we explore the feasibility of using dielectric relaxation spectroscopy for the detection of GABA concentrations within a physiological range, with the perspective of miniaturization and use during implantation. Utilizing machine learning techniques, we were able to differentiate GABA concentrations down to 5 μm. This work investigates a novel use of dielectric relaxation spectroscopy, to assess if physiological GABA concentrations can be detected through permittivity measurements.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2023-00062023-12-31T00:00:00.000+00:00Whole-body phase angle correlates with pre-operative markers in total joint arthroplastyhttps://sciendo.com/article/10.2478/joeb-2023-0008<abstract> <title style='display:none'>Abstract</title> <sec> <title style='display:none'>Background</title> <p>Bioimpedance derived whole body phase angle (ϕ), a measure of cellular integrity, has been identified as an independent marker of morbidity and mortality in many medical and surgical specialties. While similar measures of water homeostasis like extracellular edema (EE) have been associated with pre-operative risk, ϕ has not been studied in orthopaedics, despite potential to serve as a pre-operative marker. This study aims to identify relationships between ϕ, EE, and body composition metrics, laboratory values, patient reported outcomes, and comorbidities.</p> </sec> <sec> <title style='display:none'>Methods</title> <p>Multi-frequency bioimpedance analysis (BIA) records, laboratory values, and patient reported outcomes of adult patients presenting to an academic arthroplasty clinic were retrospectively reviewed. Correlation coefficients between ϕ, EE, and reviewed information were conducted.</p> </sec> <sec> <title style='display:none'>Results</title> <p>ϕ was significantly correlated (p&lt;0.001) most positively with measures of lean tissue such as skeletal muscle mass (r=0.48), appendicular skeletal muscle index (r=0.39), lean body mass (r=0.43), and dry lean mass (r=0.47), while it held negative correlations (p&lt;0.001) with age (r= -0.55), and body fat mass (r= -0.11). ϕ was not correlated with body mass index (BMI, p = 0.204). In contrast, EE demonstrated its strongest positive correlations (p&lt;0.001) with body fat mass (r=0.32), age (r=0.50), and BMI (r=0.26), and its strongest negative correlations (p&lt;0.001) with serum albumin (r= -0.37) and total protein (r= -0.23).</p> </sec> <sec> <title style='display:none'>Conclusions</title> <p>Based on their associations with markers of health and fitness, BIA determined ϕ and EE demonstrate relationships to markers currently implemented in orthopaedic practice. This likely indicates that ϕ has potential as a comprehensive surrogate for several commonly used markers to quantify pre-operative risk. In the future, ϕ may aid in developing risk-stratifications for intervention and prevention of complications.</p> </sec> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2023-00082023-12-31T00:00:00.000+00:00Advancing biomedical engineering: Leveraging Hjorth features for electroencephalography signal analysishttps://sciendo.com/article/10.2478/joeb-2023-0009<abstract> <title style='display:none'>Abstract</title> <p>Biomedical engineering stands at the forefront of medical innovation, with electroencephalography (EEG) signal analysis providing critical insights into neural functions. This paper delves into the utilization of EEG signals within the MILimbEEG dataset to explore their potential for machine learning-based task recognition and diagnosis. Capturing the brain’s electrical activity through electrodes 1 to 16, the signals are recorded in the time-domain in microvolts. An advanced feature extraction methodology harnessing Hjorth Parameters—namely Activity, Mobility, and Complexity—is employed to analyze the acquired signals. Through correlation analysis and examination of clustering behaviors, the study presents a comprehensive discussion on the emergent patterns within the data. The findings underscore the potential of integrating these features into machine learning algorithms for enhanced diagnostic precision and task recognition in biomedical applications. This exploration paves the way for future research where such signal processing techniques could revolutionize the efficiency and accuracy of biomedical engineering diagnostics.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2023-00092023-12-31T00:00:00.000+00:00Expert knowledge-based peak current mode control of electrosurgical generators for improved output power regulationhttps://sciendo.com/article/10.2478/joeb-2023-0005<abstract> <title style='display:none'>Abstract</title> <p>Electrosurgical generators (ESG) are widely used in medical procedures to cut and coagulate tissue. Accurate control of the output power is crucial for surgical success, but can be challenging to achieve. In this paper, a novel expert knowledge-based peak current mode controller (EK-PCMC) is proposed to regulate the output power of an ESG. The EK-PCMC leverages expert knowledge to adapt to changes in tissue impedance during surgical procedures. We compared the performance of the EK-PCMC with the classical peak current mode controller (PCMC) and fuzzy PID controller. The results demonstrate that the EK-PCMC significantly outperformed the PCMC, reducing the integral square error (ISE) and integral absolute error (IAE) by a factor of 3.88 and 4.86, respectively. In addition, the EK-PCMC outperformed the fuzzy PID controller in terms of transient response and steady-state performance. Our study highlights the effectiveness of the proposed EK-PCMC in improving the regulation of the output power of an ESG and improving surgical outcomes.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2023-00052023-11-17T00:00:00.000+00:00Skin layer classification by feedforward neural network in bioelectrical impedance spectroscopyhttps://sciendo.com/article/10.2478/joeb-2023-0004<abstract> <title style='display:none'>Abstract</title> <p>Conductivity change in skin layers has been classified by source indicator <italic>o<sup>k</sup></italic> (<italic>k</italic>=1: Stratum corneum, <italic>k</italic>=2: Epidermis, <italic>k</italic>=3: Dermis, <italic>k</italic>=4: Fat, and <italic>k</italic>=5: Stratum corneum + Epidermis) trained from feedforward neural network (FNN) in bioelectrical impedance spectroscopy (BIS). In BIS studies, treating the skin as a bulk, limits the differentiation of conductivity changes in individual skin layers, however skin layer classification using FNN shows promise in accurately categorizing skin layers, which is essential for predicting source indicators <italic>o<sup>k</sup></italic> and initiating skin dielectric characteristics diagnosis. The <italic>o<sup>k</sup></italic> is trained by three main conceptual points which are (i) implementing FNN for predicting <italic>k</italic> in conductivity change, (ii) profiling four impedance inputs <italic>α<sub>ξ</sub></italic> consisting of magnitude input <italic>α</italic>|<sub><italic>z</italic></sub>|, phase angle input <italic>α<sub>θ</sub></italic>, resistance input <italic>α<sub>R</sub></italic>, and reactance input <italic>α<sub>x</sub></italic> for filtering nonessential input, and (iii) selecting low and high frequency pair <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_joeb-2023-0004_ieq_001.png"/><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:msubsup><mml:mi>f</mml:mi><mml:mi>r</mml:mi><mml:mrow><mml:mi>l</mml:mi><mml:mi>h</mml:mi></mml:mrow></mml:msubsup></mml:mrow><mml:mo>)</mml:mo></mml:mrow></mml:mrow></mml:math><tex-math>$$(f_{r}^{lh})$$</tex-math></alternatives></inline-formula> by distribution of relaxation time (DRT) for eliminating parasitic noise effect. The training data set of FNN is generated to obtain the <italic>α<sub>ξ</sub></italic> ∈ <italic><bold>R</bold></italic><sup>10×17×10</sup> by 10,200 cases by simulation under configuration and measurement parameters. The trained skin layer classification is validated through experiments with porcine skin under various sodium chloride (NaCl) solutions <italic>C<sub>NaCl</sub></italic> = {15, 20, 25, 30, 35}[mM] in the dermis layer. FNN successfully classified conductivity change in the dermis layer from experiment with accuracy of 90.6% for the bipolar set-up at <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_joeb-2023-0004_ieq_002.png"/><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msubsup><mml:mi>f</mml:mi><mml:mn>6</mml:mn><mml:mrow><mml:mi>l</mml:mi><mml:mi>h</mml:mi></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mn>10</mml:mn><mml:mtext> </mml:mtext><mml:mo>&amp;</mml:mo><mml:mn>100</mml:mn><mml:mtext> </mml:mtext><mml:mo stretchy="false">[</mml:mo><mml:mtext>kHz]</mml:mtext></mml:mrow></mml:math><tex-math>$$f_{6}^{lh}=10\,\And 100\,{\rm{[kHz]}}$$</tex-math></alternatives></inline-formula> and with the same accuracy for the tetrapolar at <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_joeb-2023-0004_ieq_003.png"/><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msubsup><mml:mi>f</mml:mi><mml:mn>8</mml:mn><mml:mrow><mml:mi>l</mml:mi><mml:mi>h</mml:mi></mml:mrow></mml:msubsup><mml:mo>=</mml:mo><mml:mn>35</mml:mn><mml:mtext> </mml:mtext><mml:mo>&amp;</mml:mo><mml:mn>100</mml:mn><mml:mtext> </mml:mtext><mml:mo stretchy="false">[</mml:mo><mml:mtext>kHz]</mml:mtext></mml:mrow></mml:math><tex-math>$$f_{8}^{lh}=35\,\And 100\,{\rm{[kHz]}}$$</tex-math></alternatives></inline-formula>. The measurement noise and systematic error in the experimental results are minimized by the proposed method using the feature extraction based on <italic>α<sub>ξ</sub></italic> at <inline-formula><alternatives><inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_joeb-2023-0004_ieq_004.png"/><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msubsup><mml:mi>f</mml:mi><mml:mi>r</mml:mi><mml:mrow><mml:mi>l</mml:mi><mml:mi>h</mml:mi></mml:mrow></mml:msubsup></mml:mrow></mml:math><tex-math>$$f_{r}^{lh}$$</tex-math></alternatives></inline-formula>.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2023-00042023-08-10T00:00:00.000+00:00A fresh look at sports PSM-systemshttps://sciendo.com/article/10.2478/joeb-2023-0003<abstract> <title style='display:none'>Abstract</title> <p>The aim of the proposed study is to reveal the correlations between the dynamics of Respiratory Rate (RR) and Heart Rate (HR) during intermittent physical work at maximum power on a cycle ergometer. The stage of investigating the General functional athlete readiness (GFAR) was conducted using the sports standard “R-Engine” and the cycle ergometer in 16 volunteers (10 men, 6 women) whose average age was 21±1.17 years. To determine the athletic potential of the volunteers in this study, we used our own Coefficient of Anaerobic Capacity (CANAC Q, beats). Continuous registration of the heart rate and respiratory rate of volunteers in the maximum power sports test was performed by the “RheoCardioMonitor” system with a module of the athlete functional readiness based on the method of Transthoracic electrical impedance rheography (TEIRG). The degree of correlation of functional indicators (M, HRM, GFAR) with CANAC Q in all experimental series of the study group as a whole (n=80) was at a very high level, which confirmed the effectiveness of using the Coefficient of Anaerobic Capacity (CANAC Q) in assessing the general functional athlete readiness of the volunteers. CANAC Q is measured in “beats” of the heart and is recorded very accurately using the method of transthoracic electrical impedance rheography (TEIRG). For this reason, as a promising sports PSM-system, CANAC Q can replace the methods for determining the functional athlete readiness by blood lactate concentration and maximum oxygen consumption.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2023-00032023-05-26T00:00:00.000+00:00Dopamine detection using mercaptopropionic acid and cysteamine for electrodes surface modificationhttps://sciendo.com/article/10.2478/joeb-2018-0002<abstract><title style='display:none'>Abstract</title><p>Gold electrodes are often not suitable for dopamine measurements as dopamine creates a non-conducting polymer layer on the surface of the electrodes, which leads to increased amount of electrode passivity with the gradual increase in voltammograms measurement. This work presents the impedance spectroscopy and cyclic-voltammetry comparative study for dopamine detection with two modifications for the surface of Au electrodes; cysteamine and mercaptopropionic acid for thermally bonded and ultrasonically welded microfluidic chips, respectively. The effects of optimized tubing selection, bonding techniques, and cleaning methods of the devices with KOH solution played crucial role for improvements in dopamine detection, which are observed in the results. Furthermore, comparison for the modification with unmodified chips, and finding the unknown concentration of dopamine solution using flow injection techniques, is also illustrated.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00022018-08-16T00:00:00.000+00:00Electrodermal activity responses for quantitative assessment of felt painhttps://sciendo.com/article/10.2478/joeb-2018-0010<abstract><title style='display:none'>Abstract</title><p>Accurate assessment of experienced pain is a well-known problem in the clinical practices. Therefore, a proper method for pain detection is highly desirable. Electrodermal activity (EDA) is known as a measure of the sympathetic nervous system activity, which changes during various mental stresses. As pain causes mental stress, EDA measures may reflect the felt pain. This study aims to evaluate changes in skin conductance responses (SCRs), skin potential responses (SPRs), and skin susceptance responses (SSRs) simultaneously as a result of sequences of electrical (painful) stimuli with different intensities. EDA responses as results of painful stimuli were recorded from 40 healthy volunteers. The stimuli with three different intensities were produced by using an electrical stimulator. EDA responses significantly changed (increased) with respect to the intensity of the stimuli. Both SCRs and SSRs showed linear relationship with the painful stimuli. It was found that the EDA responses, particularly SCRs (<italic>p</italic> &lt; 0.001) and SSRs (<italic>p</italic> = 0.001) were linearly affected by the intensity of the painful stimuli. EDA responses, in particular SCRs, may be used as a useful indicator for assessment of experienced pain in clinical settings.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00102018-12-19T00:00:00.000+00:00Rectifying memristor bridge circuit realized with human skinhttps://sciendo.com/article/10.2478/joeb-2018-0023<abstract><title style='display:none'>Abstract</title><p>It has been demonstrated before that human skin can be modeled as a memristor (memory resistor). Here we realize a memristor bridge by applying two voltages of opposite signs at two different skin sites. By this setup it is possible to use human skin as a frequency doubler and half-wave rectifier which is an application of the non-linear electrical properties of human skin. The corresponding electrical measurements are non-linear since these are affected by the applied stimulus itself.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00232018-12-31T00:00:00.000+00:00A single differential equation description of membrane properties underlying the action potential and the axon electric fieldhttps://sciendo.com/article/10.2478/joeb-2018-0015<abstract><title style='display:none'>Abstract</title><p>In a succession of articles published over 65 years ago, Sir Alan Lloyd Hodgkin and Sir Andrew Fielding Huxley established what now forms our physical understanding of excitation in nerve, and how the axon conducts the action potential. They uniquely quantified the movement of ions in the nerve cell during the action potential, and demonstrated that the action potential is the result of a depolarizing event across the cell membrane. They confirmed that a complete depolarization event is followed by an abrupt increase in voltage that propagates longitudinally along the axon, accompanied by considerable increases in membrane conductance. In an elegant theoretical framework, they rigorously described fundamental properties of the Na<sup>+</sup> and K<sup>+</sup> conductances intrinsic to the action potential.</p><p>Notwithstanding the elegance of Hodgkin and Huxley’s incisive and explicative series of discoveries, their model is mathematically complex, relies on no small number of stochastic factors, and has no analytical solution. Solving for the membrane action potential and the ionic currents requires integrations approximated using numerical methods. In this article I present an analytical formalism of the nerve action potential, <italic>V<sub>m</sub></italic> and that of the accompanying cell membrane electric field, <italic>E<sub>m</sub></italic>. To conclude, I present a novel description of <italic>V<sub>m</sub></italic> in terms of a single, nonlinear differential equation. This is an original stand-alone article: the major contribution is the latter, and how this description coincides with the cell membrane electric field. This work has necessitated unifying information from two preceding papers [1,2], each being concerned with the development of closed-form descriptions of the nerve action potential, <italic>V<sub>m</sub></italic>.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00152018-12-31T00:00:00.000+00:00Cutoff points of BMI for classification of nutritional status using bioelectrical impedance analysishttps://sciendo.com/article/10.2478/joeb-2018-0005<abstract><title style='display:none'>Abstract</title><p>The objective of this study was to improve the cutoff points of the traditional classification of nutritional status and overweight / obesity based on the BMI in a Brazilian sample. A cross-sectional study was conducted on 1301 individuals of both genders aged 18 to 60 years. The subjects underwent measurement of weight and height and bioelectrical impedance analysis. Simple linear regression was used for statistical analysis, with the level of significance set at p &lt; 0.05. The sample consisted of 29.7% men and 70.3% women aged on averaged 35.7 ± 17.6 years; mean weight was 67.6 ± 16.0 kg, mean height was 164.9 ± 9.5 cm, and mean BMI was 24.9 ± 5.5 kg/m<sup>2</sup>. As expected, lower cutoffs were found for BMI than the classic reference points traditionally adopted by the WHO for the classification of obesity, i.e., 27.15 and 27.02 kg/m<sup>2</sup> for obesity for men and women, respectively. Other authors also follow this tendency, Romero-Corral <italic>et al</italic>. (2008) suggested 25.8 to 25.5 kg/m<sup>2</sup> for American men and women as new values for BMI classification of obesity. Gupta and Kapoor (2012) proposed 22.9 and 28.8 kg/m<sup>2</sup> for men and women of North India. The present investigation supports other literature studies which converge in reducing the BMI cutoff points for the classification of obesity. Thus, we emphasize the need to conduct similar studies for the purpose of defining these new in populations of different ethnicities.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00052018-08-16T00:00:00.000+00:00Tetrapolar bioimpedance measurements compared to four-wire resistance measurementshttps://sciendo.com/article/10.2478/joeb-2018-0001ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00012018-08-16T00:00:00.000+00:00Significance of biological membranes for accurate computational dosimetry of low frequency electric fieldshttps://sciendo.com/article/10.2478/joeb-2018-0009<abstract><title style='display:none'>Abstract</title><p>Computational dosimetry has become the main tool for estimating induced electric fields within brain tissues in transcranial direct current stimulation (tDCS) which is recently attracting the attention of researches for motor function disturbances such as Parkinson’s disease. This paper investigates the effect of including or excluding the very thin meninges in computing tDCS electric fields using CST software. For this purpose, two models of the brain with and without meninges were used to induce electric field with two DC current electrodes (2 mA) in regions of the model referring to M1 and Prefrontal Cortex (FP2) similar to tDCS. Considering meninges, the results have shown differences in the induced field showing that there might be problems with conventional models in which meninges are not taken into account.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00092018-12-19T00:00:00.000+00:00On sensitivity in transfer impedance measurementshttps://sciendo.com/article/10.2478/joeb-2018-0020<abstract><title style='display:none'>Abstract</title><p>The term sensitivity is sometimes misused when discussing volume impedance measurements. This is a critique of the name of the quantity sensitivity, as well as pointing out how the term easily can be misinterpreted. To resolve the issue, a shift of focus towards volume impedance density, which is a more useful quantity, is proposed. A new parameter, perceptivity, is introduced. Perceptivity is useful tool for characterization of measurement systems, to objectively compare systems, and to formulate instrument specifications.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00202018-12-31T00:00:00.000+00:00Applications of bioimpedance measurement techniques in tissue engineeringhttps://sciendo.com/article/10.2478/joeb-2018-0019<abstract><title style='display:none'>Abstract</title><p>Rapid development in the field of tissue engineering necessitates implementation of monitoring methods for evaluation of the viability and characteristics of the cell cultures in a real-time, non-invasive and non-destructive manner. Current monitoring techniques are mainly histological and require labeling and involve destructive tests to characterize cell cultures. Bioimpedance measurement technique which benefits from measurement of electrical properties of the biological tissues, offers a non-invasive, label-free and real-time solution for monitoring tissue engineered constructs. This review outlines the fundamentals of bioimpedance, as well as electrical properties of the biological tissues, different types of cell culture constructs and possible electrode configuration set ups for performing bioimpedance measurements on these cell cultures. In addition, various bioimpedance measurement techniques and their applications in the field of tissue engineering are discussed.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00192018-12-31T00:00:00.000+00:00On the selection of excitation signals for the fast spectroscopy of electrical bioimpedancehttps://sciendo.com/article/10.2478/joeb-2018-0018<abstract><title style='display:none'>Abstract</title><p>Different excitation signals are applicable in the wideband impedance spectroscopy in general. However, in electrical bioimpedance (EBI) measurements, there are limitations that set specific demands on the properties of the excitation signals. This paper compares the efficiency of different excitation signals in a graspable presentation and gives recommendations for their use. More exactly, the paper deals with finding the efficient excitation waveforms for the fast spectroscopy of electrical bioimpedance. Nevertheless, the described solutions could be useful also in other implementations of impedance spectroscopy intended for frequency domain characterization of different objects.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00182018-12-31T00:00:00.000+00:00Mechanistic multilayer model for non-invasive bioimpedance of intact skinhttps://sciendo.com/article/10.2478/joeb-2018-0006<abstract><title style='display:none'>Abstract</title><p>An approximate semi-analytical solution based on a Hankel transform of a mechanistic model for electrical impedance spectroscopy (EIS) is derived for a non-invasive axisymmetric concentric probe with <italic>m</italic> electrodes measuring the response of <italic>n</italic> layers of human skin. We validate the semi-analytical solution for the case when the skin is treated as a three-layer entity - (<italic>i</italic>) stratum corneum, (<italic>ii</italic>) viable skin comprising living epidermis and dermis and (<italic>iii</italic>) adipose tissue – on the volar forearm in the frequency range 1 kHz to 1 MHz with experimental EIS measurements of 120 young subjects. Overall, we find good agreement for both the mean magnitude and phase of the impedance as well as the natural variability between subjects. Finally, the semi-analytical solution is verified with the full set of equations solved numerically: Good agreement is found for the point-wise potential distribution in the three skin layers.</p></abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/joeb-2018-00062018-08-18T00:00:00.000+00:00en-us-1