UCLA

Diagnostic platforms are becoming increasingly sophisticated in their ability to monitor a variety of biomarkers across different biofluids. Current laboratory gold standard techniques including liquid chromatography/mass spectrometry (LC/MS), enzyme-linked immunosorbent assays (ELISA), and polymerase chain reaction (PCR) typically require costly instrumentation, complex protocols, and long time-to-results. Point-of-care (POC) devices seek to simplify sample processing and analysis using more compact and automated devices. Point-of-care approaches have already revolutionized the healthcare landscape by enabling more rapid and decentralized diagnosis while reducing costs and the requirement for trained personnel. Nonetheless, there is a significant push to take diagnostic devices beyond POC directly to the level of the individual. Wearable, or point-of-person (POP) devices, have made their way into the mainstream with products like the Apple Watch, Fitbit, and Oura Ring.While wearable devices have been met with commercial success and interest from the healthcare community and the public, they are mostly limited to monitoring physiological markers such as heart rate, temperature, and sleep activity. There is great interest in advancing wearable devices to monitor a variety biochemical species including metabolites, proteins, nucleic acids, neurotransmitters, and hormones. The ability to detect biochemical biomarkers in readily sampled biofluids like saliva, sweat, tears, and interstitial fluid has the potential to enable continuous and minimally invasive monitoring. Wearable devices can also facilitate personalized medicine, whereby there is an ever-increasing shift to provide feedback and therapies tailored to individuals based on their specific biometrics, as opposed to the long-standing one-size-fits-all approach to modern medicine. My dissertation details four projects I focused on during my doctoral research that seek to address four different primary challenges in the field of wearable monitoring. Specifically, I investigated strategies to reduce fabrication costs and improve lab-to-market commercialization, novel energy harvesting approaches to realize self-powered sensors, materials design strategies to improve the sensor-biology interface, and finally, new sensor architectures to enable highly sensitive and selective quantification of low-abundance analytes. The resulting technologies span the gamut from monitoring biophysical to biochemical signals including metabolites and hormones. Ultimately, I aim to demonstrate the breadth of physiological information that can be acquired using wearable devices.