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Electrical impedance biosensors are powerful and continuously being developed for various biological sensing applications. In this line, the sensitivity of impedance biosensors embedded with microfluidic technologies, such as sheath flow focusing, dielectrophoretic focusing, and interdigitated electrode arrays, can still be greatly improved. In particular, reagent consumption reduction and analysis time-shortening features can highly increase the analytical capabilities of such biosensors. Moreover, the reliability and efficiency of analyses are benefited by microfluidics-enabled automation. Through the use of mature microfluidic technology, complicated biological processes can be shrunk and integrated into a single microfluidic system (e.g., lab-on-a-chip or micro-total analysis systems). By incorporating electrical impedance biosensors, hand-held and bench-top microfluidic systems can be easily developed and operated by personnel without professional training. Furthermore, the impedance spectrum provides broad information regarding cell size, membrane capacitance, cytoplasmic conductivity, and cytoplasmic permittivity without the need for fluorescent labeling, magnetic modifications, or other cellular treatments. In this review article, a comprehensive summary of microfluidics-based impedance biosensors is presented. The structure of this article is based on the different substrate material categorizations. Moreover, the development trend of microfluidics-based impedance biosensors is discussed, along with difficulties and challenges that may be encountered in the future.

Therapies based on regenerative techniques have the potential to radically improve healthcare in the coming years. As a result, there is an emerging need for non-destructive and label-free technologies to assess the quality of engineered tissues and cell-based products prior to their use in the clinic. In parallel, the emerging regenerative medicine industry that aims to produce stem cells and their progeny on a large scale will benefit from moving away from existing destructive biochemical assays towards data-driven automation and control at the industrial scale. Impedance-based cellular assays (IBCA) have emerged as an alternative approach to study stem-cell properties and cumulative studies, reviewed here, have shown their potential to monitor stem-cell renewal, differentiation and maturation. They offer a novel method to non-destructively assess and quality-control stem-cell cultures. In addition, when combined with in vitro disease models they provide complementary insights as label-free phenotypic assays. IBCA provide quantitative and very sensitive results that can easily be automated and up-scaled in multi-well format. When facing the emerging challenge of real-time monitoring of three-dimensional cell culture dielectric spectroscopy and electrical impedance tomography represent viable alternatives to two-dimensional impedance sensing. This article is part of the theme issue ‘Designer human tissue: coming to a lab near you’.

Electrochemical impedance spectroscopy is finding increasing use in electrochemical sensors and biosensors, both in their characterisation, including during successive phases of sensor construction, and in application as a quantitative determination technique. Much of the published work continues to make little use of all the information that can be furnished by full physical modelling and analysis of the impedance spectra, and thus does not throw more than a superficial light on the processes occurring. Analysis is often restricted to estimating values of charge transfer resistances without interpretation and ignoring other electrical equivalent circuit components. In this article, the important basics of electrochemical impedance for electrochemical sensors and biosensors are presented, focussing on the necessary electrical circuit elements. This is followed by examples of its use in characterisation and in electroanalytical applications, at the same time demonstrating how fuller use can be made of the information obtained from complete modelling and analysis of the data in the spectra, the values of the circuit components and their physical meaning. The future outlook for electrochemical impedance in the sensing field is discussed.

Accurate forecasting of lithium-ion battery performance is essential for easing consumer concerns about the safety and reliability of electric vehicles. Most research on battery health prognostics focuses on the research and development setting where cells are subjected to the same usage patterns. However, in practical operation, there is great variability in use across cells and cycles, thus making forecasting challenging. To address this challenge, here we propose a combination of electrochemical impedance spectroscopy measurements with probabilistic machine learning methods. Making use of a dataset of 88 commercial lithium-ion coin cells generated via multistage charging and discharging (with currents randomly changed between cycles), we show that future discharge capacities can be predicted with calibrated uncertainties, given the future cycling protocol and a single electrochemical impedance spectroscopy measurement made immediately before charging, and without any knowledge of usage history. The results are robust to cell manufacturer, the distribution of cycling protocols, and temperature. The research outcome also suggests that battery health is better quantified by a multidimensional vector rather than a scalar state of health. Accurate forecasts of lithium-ion battery performance will ease concerns about the reliability of electric vehicles. Here, the authors leverage electrochemical impedance spectroscopy and machine learning to show that future capacity can be predicted amid uneven use, with no historical data requirement.

Transparent ultrasound transducers (TUTs) can seamlessly integrate optical and ultrasound components, but acoustic impedance mismatch prohibits existing TUTs from being practical substitutes for conventional opaque ultrasound transducers. Here, we propose a transparent adhesive based on a silicon dioxide-epoxy composite to fabricate matching and backing layers with acoustic impedances of 7.5 and 4–6 MRayl, respectively. By employing these layers, we develop an ultrasensitive, broadband TUT with 63% bandwidth at a single resonance frequency and high optical transparency ( > 80%), comparable to conventional opaque ultrasound transducers. Our TUT maximises both acoustic power and transfer efficiency with maximal spectrum flatness while minimising ringdowns. This enables high contrast and high-definition dual-modal ultrasound and photoacoustic imaging in live animals and humans. Both modalities reach an imaging depth of > 15 mm, with depth-to-resolution ratios exceeding 500 and 370, respectively. This development sets a new standard for TUTs, advancing the possibilities of sensor fusion. Transparent ultrasound transducers suffer from practical limitations due to acoustic impedance mismatch. By using a transparent adhesive based on silicon dioxide epoxy, the authors demonstrate a broadband, ultrasensitive transparent ultrasound transducer, advancing the possibilities of sensor fusion.

BackgroundBioelectrical impedance analysis (BIA) is a technique widely used for estimating body composition and health-related parameters. The technology is relatively simple, quick, and non-invasive, and is currently used globally in diverse settings, including private clinicians’ offices, sports and health clubs, and hospitals, and across a spectrum of age, body weight, and disease states. BIA parameters can be used to estimate body composition (fat, fat-free mass, total-body water and its compartments). Moreover, raw measurements including resistance, reactance, phase angle, and impedance vector length can also be used to track health-related markers, including hydration and malnutrition, and disease-prognostic, athletic and general health status. Body composition shows profound variability in association with age, sex, race and ethnicity, geographic ancestry, lifestyle, and health status. To advance understanding of this variability, we propose to develop a large and diverse multi-country dataset of BIA raw measures and derived body components. The aim of this paper is to describe the ‘BIA International Database’ project and encourage researchers to join the consortium.MethodsThe Exercise and Health Laboratory of the Faculty of Human Kinetics, University of Lisbon has agreed to host the database using an online portal. At present, the database contains 277,922 measures from individuals ranging from 11 months to 102 years, along with additional data on these participants.ConclusionThe BIA International Database represents a key resource for research on body composition.

The accurate determination of the post-dilution concentration of biological buffers is essential for retaining the necessary properties and effectiveness of the buffer to maintain stable cellular environments and optimal conditions for biochemical reactions. In this work, we introduce a silicon-based impedance chip, which offers a rapid and reagent-free approach for monitoring the buffer concentrations after dilution with deionized (DI) water. The impedance of the impedance chip is measured, and the impedance data are modeled using a multiparameter equivalent circuit model. We investigated six aqueous biological buffers with pH values above and below the physiological pH for most tissues (pH ~ 7.2–7.4) following dilution with DI water by factors of 2.0, 10.0, 20.0, 100.0, and 200.0. The impedance measurement is then performed for the frequency spectrum of 40 Hz to 1 MHz. From the interpretation of the impedance measurement using the multiparameter equivalent circuit model, we report a buffer-sensitive equivalent circuit parameter RAu/Si of the silicon-based impedance chip showing a linear trend on a logarithmic scale with the buffer concentration change after dilution. The parameter RAu/Si is independent of the buffer pH and the added volume. The results demonstrate the efficacy of the silicon-based impedance chip as a versatile tool for precise post-dilution concentration determination of diverse biologically relevant buffers. The presented impedance chip offers rapid, accurate, and reliable monitoring, making it highly suitable for integration into automated liquid-handling systems to enhance the efficiency and precision of biological and chemical processes.

Background Prolonged weaning from mechanical ventilation is associated with poor clinical outcome. Therefore, choosing the right moment for weaning and extubation is essential. Electrical Impedance Tomography (EIT) is a promising innovative lung monitoring technique, but its role in supporting weaning decisions is yet uncertain. We aimed to evaluate physiological trends during a T-piece spontaneous breathing trail (SBT) as measured with EIT and the relation between EIT parameters and SBT success or failure. Methods This is an observational study in which twenty-four adult patients receiving mechanical ventilation performed an SBT. EIT monitoring was performed around the SBT. Multiple EIT parameters including the end-expiratory lung impedance (EELI), delta Tidal Impedance (ΔZ), Global Inhomogeneity index (GI), Rapid Shallow Breathing Index (RSBI EIT ), Respiratory Rate (RR EIT ) and Minute Ventilation (MV EIT ) were computed on a breath-by-breath basis from stable tidal breathing periods. Results EELI values dropped after the start of the SBT ( p  < 0.001) and did not recover to baseline after restarting mechanical ventilation. The ΔZ dropped ( p  < 0.001) but restored to baseline within seconds after restarting mechanical ventilation. Five patients failed the SBT, the GI ( p  = 0.01) and transcutaneous CO 2 ( p  < 0.001) values significantly increased during the SBT in patients who failed the SBT compared to patients with a successful SBT. Conclusion EIT has the potential to assess changes in ventilation distribution and quantify the inhomogeneity of the lungs during the SBT. High lung inhomogeneity was found during SBT failure. Insight into physiological trends for the individual patient can be obtained with EIT during weaning from mechanical ventilation, but its role in predicting weaning failure requires further study.

Cellular heterogeneity is of significance in cell-based assays for life science, biomedicine and clinical diagnostics. Electrical impedance sensing technology has become a powerful tool, allowing for rapid, non-invasive, and label-free acquisition of electrical parameters of single cells. These electrical parameters, i.e., equivalent cell resistance, membrane capacitance and cytoplasm conductivity, are closely related to cellular biophysical properties and dynamic activities, such as size, morphology, membrane intactness, growth state, and proliferation. This review summarizes basic principles, analytical models and design concepts of single-cell impedance sensing devices, including impedance flow cytometry (IFC) to detect flow-through single cells and electrical impedance spectroscopy (EIS) to monitor immobilized single cells. Then, recent advances of both electrical impedance sensing systems applied in cell recognition, cell counting, viability detection, phenotypic assay, cell screening, and other cell detection are presented. Finally, prospects of impedance sensing technology in single-cell analysis are discussed.

•Hand grip strength (HGS) correlated with raw bioelectrical impedance analysis (BIA) variables in adolescents as well as young adults.•Raw BIA variables were effective predictors of HGS.•The relationships between HGS and raw BIA variables vary with age.•Raw BIA variables may be used along with HGS for assessing muscle quality. Musculoskeletal fitness and body composition are major components of health-related physical fitness that are expected to be linked to each other. The aim of this study was to explore the association of musculoskeletal fitness (expressed as hand grip strength [HGS]) and raw bioelectrical impedance analysis (BIA) variables and other predictors in the second and third decades of life. Four groups of healthy normal-weight and overweight participants were studied: 130 male adolescents (age 16.0 ± 1.1 y), 143 female adolescents (16.0 ± 0.9 y), 141 young men (25.5 ± 2.0 y), and 141 young women (25.2 ± 1.9 y). Raw BIA variables (impedance [Z] and phase angle [PhA]) for the whole body were measured at four frequencies (5, 50, 100, and 250 kHz), and HGS was measured in both upper limbs. HGS was higher in males than females and higher in young men than male adolescents. A fairly strong correlation emerged in both genders between HGS and raw BIA variables—that is, bioimpedance index (height2/Z), PhA, and impedance ratios (Z at high frequency/Z at low frequency). In multiple regression analysis, bioimpedance index, PhA, and impedance ratio were more effective predictors of HGS than BIA-derived estimates of body composition or anthropometric variables such as height, weight, and body mass index. In both genders, HGS was significantly higher in young adults than in adolescents for the same PhA or impedance ratio. This study provides some insight into the use of raw BIA variables and HGS in the first decades of life, suggesting a new approach for a reliable assessment of muscle quality in terms of both muscle structure and strength.