Laser-Engraved Wearable Sweat Sensor for Metabolic Monitoring

Author: Yang, Yiran (Isabella)

Year: 2023

Degree: Dissertation (Ph.D.)

Advisor: Gao, Wei

Committee Members: Tai, Yu-Chong; Emami, Azita; Gharib, Morteza; Gao, Wei

Option: Medical Engineering

DOI: 10.7907/5yfm-tt16

Abstract

Wearable sensors have shown great potential in health diagnostics and monitoring. Continuous monitoring of metabolites in sweat could potentially offer great insight into a person’s health, but current sweat sensing technology faces challenges in different realms: The sensing strategies are limited and there is a need to achieve high sensitivity for low-concentration targets and widen the detection spectrum of chemical targets. The lack of efficient sweat sampling creates inaccurate sensing results from sweat mixing with skin contaminants or sensing byproducts. Moreover, the lack of evaluation of sweat metabolites with respect to relevant clinical conditions and the lack of scalable fabrication technique pose hurdles in the eventual applications of non-invasive sweat monitoring. In this thesis, efforts advancing progress in these fronts are presented. Chapter 1 establishes a brief topical overview of the sweat-sensing background. In Chapter 2, we demonstrate how to utilize laser-engraving technique to achieve high-performance graphene sensors for electroactive metabolite sensing and vital signs detection. Chapter 3 describes subsequent efforts built on laser-engraved graphene sensors to improve sensing selectivity and widen the detection spectrum to detect non-electroactive targets in sweat. In Chapter 4, design and performance of our laser-engraved microfluidics are described and shown to improve sweat sampling in both exercise-induced and iontophoresis-induced sweating individuals. Chapter 5 presents our endeavors in evaluating sweat biomarkers with clinical conditions in pilot studies involving individuals with gout and metabolic syndrome. In total, the works summarized here expand biology, chemistry, material science, and mechanical engineering, and could potentially facilitate future applications in precision nutrition.

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