Multiplexed Comprehensive Design and Characterization of an Electrochemical Interface Accessing Non-invasive Bodily Fluids Towards Quality-of-life Monitoring

The research presented in this thesis outlines the design and development of novel biosensing platforms for monitoring biomarkers by the non-invasive sampling of body fluids with emphasis on self-health and disease management. The purpose of this work is to demonstrate the efficacy of two combinatorial biosensors – Continuous awareness through sweat platform (CLASP) and Exhaled breath condensate scanning using rapid electro analytics (EBC-SURE) for the detection of metabolic and inflammatory biomarkers towards integration onto low-power internet of things (IoT) platforms for wearable and point-of-care diagnostic applications. First, this work demonstrated the technical utility of a lancet-free, label-free platform for the combinatorial, and continuous monitoring of alcohol and glucose in perspired human sweat produced without external sweat induction strategies. The motivation of this study was to develop a sweat-based wearable platform for alcohol and glucose management to monitor glucose levels on moderate consumption of alcohol of diabetic social drinkers. A nanotextured sensor stack was embedded into a flexible nanoporous substrate to achieve sensitive and specific affinity-based biomarker detection within physiologically relevant ranges in ultralow volumes of sweat. Non-faradaic EIS is employed as the signal transduction mechanism for biomarker detection to give an insight into the binding events occurring at the sensor interface. Additionally, the CLASP platform was benchmarked against commercially available hand-held devices to establish a one-to-one performance correlation. Furthermore, this platform was employed to demonstrate the epidermal functionality and sensor performance of CLASP for the on-body detection of sweat lactate to monitor restricted oxygen supply in sedentary populations. The successful implementation of CLASP in detecting metabolic biomarkers for health monitoring led to the transition of assessing the performance metrics of this platform for the detection of inflammatory biomarkers such as cortisol and TNF-α for chronic disease monitoring. The important highlight of this work was to establish the longterm temporal stability of the CLASP in detecting a simulated rise and fall in cortisol levels over a 6-hour sleep cycle. The last effort was focused on developing a point-of-care aid platform- EBCSURE for the trace detection of inflammatory biomarkers in exhaled breath condensate for monitoring respiratory disorders. Exhaled breath condensate is considered a promising source of inflammatory biomarkers that can determine the pathophysiological processes underlying lung inflammation in a simple and non-invasive manner. EBC-SURE displayed a stable performance after rigorous testing enabling its integration onto diagnostic platforms for rapid quantification of biomarkers related to a healthy and acute inflammatory disease condition.