Bacteria concentration and detection is time-consuming in regular microbiology procedures aimed to facilitate the detection and analysis of these cells at very low concentrations. Traditional methods are effective but often require several days to complete. This scenario results in low bioanalytical and diagnostic methodologies with associated increased costs and complexity. In recent years, the exploitation of the intrinsic electrical properties of cells has emerged as an appealing alternative approach for concentrating and detecting bacteria. The combination of dielectrophoresis (DEP) and impedance analysis (IA) in microfluidic on-chip platforms could be key to develop rapid, accurate, portable, simple-to-use and cost-effective microfluidic devices with a promising impact in medicine, public health, agricultural, food control and environmental areas. The present document reviews recent DEP and IA combined approaches and the latest relevant improvements focusing on bacteria concentration and detection, including selectivity, sensitivity, detection time, and conductivity variation enhancements. Furthermore, this review analyses future trends and challenges which need to be addressed in order to successfully commercialize these platforms resulting in an adequate social return of public-funded investments.

We present a small, compact and portable device for point-of-care instantaneous early detection of anemia. The method used is based on direct hematocrit measurement from whole blood samples by means of impedance analysis. This device consists of a custom electronic instrumentation and a plug-and-play disposable sensor. The designed electronics rely on straightforward standards for low power consumption, resulting in a robust and low consumption device making it completely mobile with a long battery life. Another approach could be powering the system based on other solutions like indoor solar cells, or applying energy-harvesting solutions in order to remove the batteries. The sensing system is based on a disposable low-cost label-free three gold electrode commercial sensor for 50 μL blood samples. The device capability for anemia detection has been validated through 24 blood samples, obtained from four hospitalized patients at Hospital Clínic. As a result, the response, effectiveness and robustness of the portable point-of-care device to detect anemia has been proved with an accuracy error of 2.83% and a mean coefficient of variation of 2.57% without any particular case above 5%.

A first approach to a portable and compact device for point-of-care (PoC) early instantaneous detection of anemia is described. This device works directly with whole blood samples relying on hematocrit analysis by means of impedance analysis. This device consists of a custom electronic instrumentation, postprocessing software and plug-and-play disposable sensor. The designed electronics are connected to a remote computer, which allows control of the instrumentation and results displaying with a user friendly software panel. The disposable sensor is based on a low-cost label-free three gold electrode commercial sensor for 50-μL volume samples. Forty-eight whole blood samples, randomly collected from hospitalized patients in Hospital Clínic, were used to validate the device capability for anemia detection. Whole blood samples were distributed in two groups: 10 samples for system calibration, and 38 samples for system validation. To calibrate the device, a complete EIS experiment has been performed to get a full impedance spectrum analysis, defining an accurate frequency working range for hematocrit detection. Afterward, we developed a protocol for instant impedance detection to determine the system detection accuracy, sensitivity, and coefficient of variation. As a result, impedance variations between different samples have been detected with less than 2% accuracy error for both impedance magnitude and phase. A hematocrit detection algorithm, relying on impedance analysis, has been developed based on the previous studies. The response, effectiveness, and robustness of the portable PoC device to detect anemia have been proved with an accuracy error of 1.75% and a coefficient of variation of less than 5%.

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Many sweat-based wearable monitoring systems have been recently proposed, but the data provided by those systems often lack a reliable and meaningful relation to standardized blood values. One clear example is lactate, a relevant biomarker for both sports and health sectors, with a complex sweat−blood bioequivalence. This limitation decreases its individual significance as a sweat-based biomarker. Taking into account the insights of previous studies, a multiparametric methodology has been proposed to predict blood lactate from non-invasive independent sensors: sweat lactate, sweat rate, and heart rate. The bioequivalence study was performed with a large set of volunteers (>30 subjects) in collaboration with sports institutions (Institut Nacional d'EducacióFi ́sica de Catalunya, INEFC, and Centre d'Alt Rendiment, CAR, located in Spain). A neural network algorithm was used to predict blood lactate values from the sensor data and subject metadata. The developed methodology reliably and accurately predicted blood lactate absolute values, only adding 0.3 mM of accumulated error when compared to portable blood lactate meters, the current gold standard for sports clinicians. The approach proposed in this work, along with an integrated platform for sweat monitoring, will have a strong impact on the sports and health fields as an autonomous, real-time, and continuous monitoring tool.