Non-invasive healthcare technologies are an important part of research and development nowadays due to the low cost and convenience offered to both healthcare receivers and providers. This work overviews the recent advances in the field of non-invasive electrochemical biosensors operating in secreted human physiological fluids, viz. tears, sweat, saliva, and urine. Described electrochemical devices are based on different electrochemical techniques, viz. amperometry, coulometry, cyclic voltammetry, and impedance spectroscopy. Challenges that confront researchers in this exciting area and key requirements for biodevices are discussed. It is concluded that the field of non-invasive sensing of biomarkers in bodily fluid is highly convoluted. Nonetheless, if the drawbacks are appropriately addressed, and the pitfalls are adroitly circumvented, the approach will most certainly disrupt current clinical and self-monitoring practices.

An electronic tongue is a powerful analytical instrument based on an array of non-selective chemical sensors with a partial specificity for data gathering and advanced pattern recognition methods for data analysis. Connecting electronic tongues with electrochemical techniques for data collection has led to various applications, mostly within sensing for food quality and environmental monitoring, but also in biomedical research for the analyses of different bioanalytes in human physiological fluids. In this paper, an electronic tongue consisting of six electrodes (viz., gold, platinum, palladium, titanium, iridium, and glassy carbon) was designed and tested in authentic (undiluted, unpretreated) human saliva samples from eight volunteers, collected before and during the COVID-19 pandemic. Investigations of 11 samples using differential pulse voltammetry and a principal component analysis allowed us to distinguish between SARS-CoV-2-free and infected authentic human saliva. This work, as a proof-of-principle demonstration, provides a new perspective for the use of electronic tongues in the field of enzyme-free electrochemical biosensing, highlighting their potential for future applications in non-invasive biomedical analyses.

Sweat is a promising biofluid in allowing for non-invasive sampling. Here, we investigate the use of a voltammetric electronic tongue, combining different metal electrodes, for the purpose of non-invasive sample assessment, specifically focusing on sweat. A wearable electronic tongue is presented by incorporating metal electrodes on a flexible circuit board and used to non-invasively monitor sweat on the body. The data obtained from the measurements were treated by multivariate data processing. Using principal component analysis to analyze the data collected by the wearable electronic tongue enabled differentiation of sweat samples of different chemical composition, and when combined with 1H-NMR sample differentiation could be attributed to changing analyte concentrations.

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Background When compared to the general population, socioeconomically disadvantaged communities frequently experience compromised health. Monitoring the divide is challenging since in general, standardized biomedical tests are linguistically and culturally inappropriate. The aim of this study was to develop a novel healthcare technology for its usage in socioeconomically disadvantaged areas.Methods A unique mobile biomedical testbed based on non-invasive analysis, accompanied with the World Health Organization Quality of Life survey, was developed. This healthcare approach was used in Lindängen, a socioeconomically disadvantaged neighborhood in Malmö, which has been listed as one of the twelve most vulnerable neighborhoods in Sweden. Results The less intrusive biomedical approach, compared to conventional setups used, e.g., wrist blood pressure monitoring, bioimpedance analysis and cardiovascular diagnostics, non-invasive determination of blood bioanalytes, was highly appreciated by the participants, i.e., 39 female volunteers of Middle Eastern origin. Surprisingly, the collected biomedical data illustrated that the apparent health of the participants from Lindängen was comparable to the general Swedish population. The Quality of Life-BREF survey, used to gather information regarding subjective health perceptions within the cohort, combined with advanced statistical data analysis, revealed statistically significant correlations between perceived health and biomedical data. Even though the dependences found were complex, the recognition of which is essential in further research. Conclusions Our results validate the potential of non-invasive technologies in combination with advanced statistical analysis, especially when combined with linguistically and culturally appropriate healthcare methodologies, allowing participants to appreciate the significance of the different parameters to evaluate and monitor aspects of health.

When compared to the general population, socioeconomically disadvantaged communities frequently experience compromised health. Monitoring the divide is challenging since standardized biomedical tests are linguistically and culturally inappropriate. The aim of this study was to develop and test a unique mobile biomedical testbed based on non-invasive analysis, as well as to explore the relationships between the objective health measures and subjective health outcomes, as evaluated with the World Health Organization Quality of Life survey. The testbed was evaluated in a socioeconomically disadvantaged neighborhood in Malmö, which has been listed as one of the twelve most vulnerable districts in Sweden. The study revealed that compared to conventional protocols the less intrusive biomedical approach was highly appreciated by the participants. Surprisingly, the collected biomedical data illustrated that the apparent health of the participants from the ethnically diverse low-income neighborhood was comparable to the general Swedish population. Statistically significant correlations between perceived health and biomedical data were disclosed, even though the dependences found were complex, and recognition of the manifest complexity needs to be included in further research. Our results validate the potential of non-invasive technologies in combination with advanced statistical analysis, especially when combined with linguistically and culturally appropriate healthcare methodologies, allowing participants to appreciate the significance of the different parameters to evaluate and monitor aspects of health.