Wearable Sweat Sensors for Disease Monitoring and Management

Citation

Tu, Jiaobing (2024) Wearable Sweat Sensors for Disease Monitoring and Management. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/7jdg-z479. https://resolver.caltech.edu/CaltechTHESIS:11062023-050222447

Abstract

With the emphasis of healthcare shifting towards prevention and early detection of diseases and monitoring of chronic conditions, there is a growing need for hassle‐free telemedicine sensor technologies that can be seamlessly integrated into daily life. While significant progress has been made in the development of wearable sweat and salivary biosensors to meet this need for rapid, real-time collection of physiological information, the majority of current epidermal sensing systems are unable to detect trace-level disease-relevant biomarkers accurately in biofluids and cannot be mass produced. To meet this demand for low-cost, mass-producible mHealth devices for at-home settings, we developed several fully integrated laser-engraved graphene-based biosensors for the detection of low-concentration sweat and saliva analytes including hormones (cortisol) and proteins (C-reactive protein). Several graphene surface engineering strategies are investigated for the sensitive and selective detection of targets. System-level engineering and microfluidic designs are explored to achieve on-demand sweat induction and harvesting under sedentary settings and automated sweat and reagent routing and in situ signal correction and analysis for facile operation on the skin. The utility of these fully integrated flexible mHealth systems is evaluated through multiple human studies involving healthy and various patient subgroups towards stress assessment, as well as the monitoring and management of various chronic conditions including chronic obstructive pulmonary disease, heart failure, and inflammatory bowel diseases. These fully integrated mHealth devices demonstrate a technology that can be easily adapted to monitor a broad spectrum of disease-specific proteins, cytokines, and hormones, thus advancing future applications in personalized disease diagnosis, management, and prevention.

Thesis Files