Advances in bioelectronic technologies are transforming healthcare by enabling continuous monitoring and active modulation of physiological functions. However, conventional electronic materials are mechanically mismatched with soft biological tissues, which can lead to poor conformal contact, unstable signal acquisition, and adverse biological responses during long-term operation. This dissertation addresses these challenges through the development of multimodal bioelectronic systems that integrate soft materials, scalable fabrication strategies, and closed-loop therapeutic functionalities for next-generation health monitoring and intervention.
\r\n\r\nFirst, scalable fabrication strategies are developed to construct flexible and multimodal sensing platforms capable of detecting diverse physiological and environmental signals. Inkjet-printed sensor arrays incorporating nanomaterial-based electrochemical and physical sensors enable simultaneous measurement of temperature, pressure, and chemical biomarkers with high sensitivity and spatial resolution. These sensing systems can be integrated onto soft electronic skins and robotic platforms to provide real-time physicochemical perception in complex environments.
\r\n\r\nSecond, conformal bioelectronic interfaces are engineered to enable stable, long-term interactions with biological tissues. By tailoring material properties and device architectures, these interfaces achieve improved mechanical compatibility with soft tissues, facilitating reliable in vivo signal acquisition and stimulation while minimizing interfacial stress and biological reactions.
\r\n\r\nFinally, closed-loop bioelectronic systems are developed that combine continuous biosensing with responsive therapeutic stimulation. Integrated platforms capable of monitoring metabolic signals and triggering neuromodulation demonstrate the potential for automated therapeutic regulation. These systems highlight the feasibility of real-time physiological monitoring coupled with intelligent intervention.
\r\n\r\nTogether, the materials, device architectures, and system-level strategies presented in this dissertation establish a framework for scalable, conformal, and multifunctional bioelectronics. These technologies provide new opportunities for wearable and implantable systems capable of continuous health monitoring, autonomous therapy, and advanced human\u2013machine interfaces.
", "doi": "10.7907/a4af-sw77", "publication_date": "2026", "thesis_type": "phd", "thesis_year": "2026" }, { "id": "thesis:16530", "collection": "thesis", "collection_id": "16530", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:06292024-045659387", "type": "thesis", "title": "Computational Design of Wearable Chemical Sensors for Personalized Healthcare", "author": [ { "family_name": "Mukasa", "given_name": "Daniel", "orcid": "0000-0001-8379-3648", "clpid": "Mukasa-Daniel" } ], "thesis_advisor": [ { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "thesis_committee": [ { "family_name": "Goddard", "given_name": "William A., III", "orcid": "0000-0003-0097-5716", "clpid": "Goddard-W-A-III" }, { "family_name": "Schwab", "given_name": "Keith C.", "orcid": "0000-0001-8216-4815", "clpid": "Schwab-K-C" }, { "family_name": "Kornfield", "given_name": "Julia A.", "orcid": "0000-0001-6746-8634", "clpid": "Kornfield-J-A" }, { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "local_group": [ { "literal": "div_eng" } ], "abstract": "Wearable sweat sensors have the potential to revolutionize precision medicine as they can non-invasively collect molecular information closely associated with an individual\u2019s health status. However, the majority of clinically relevant biomarkers cannot be continuously detected in situ using existing wearable approaches. Molecularly imprinted polymers (MIPs) are a promising candidate to address this challenge but haven\u2019t yet gained widespread use due to their complex design and optimization process yielding variable selectivity. Despite their promise, MIPs have historically been known to be exceedingly difficult to optimize. Changes in the monomer/monomers used, polymerization solvent, and crosslinking agent have been shown to change the performance of MIP sensors significantly. This is particularly a concern in sweat-based sensors where the concentration of analytes is very low and chemical diversity is very high as a drop of sweat can contain vitamins, hormones, and amino acids. Consequentially, any sweat based sensor must exhibit high sensitivity (ability to detect low analyte concentrations) and selectivity (ability to distinguish one analyte from another). Computational methods have been introduced to design MIP sensitivity alone, however these prior methods do not cover all aspects essential for using a sensor in a wearable device such as selectivity optimization, detection of non-electroactive analytes, and scalable manufacturing. Here, we introduce a full computational method that allows for high throughput materials discovery for wearable devices. We will describe how to design novel sensing materials with QuantumDock, an automated computational framework for universal MIP development toward wearable applications. Then we delve into further technical details on signal transduction and scalable manufacturing approaches for these wearable devices. We present a number of novel devices designed with these computational methods including a wearable non-invasive phenylalanine monitoring system (the first of its kind), a wearable nutritional tracker \u2018Nutritrek\u2019 capable of monitoring a range of metabolic disorders, and an implantable pharmaceutical drug monitoring system for cancer patients.", "doi": "10.7907/r46k-sw73", "publication_date": "2025", "thesis_type": "phd", "thesis_year": "2025" }, { "id": "thesis:16751", "collection": "thesis", "collection_id": "16751", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:09222024-230441454", "primary_object_url": { "basename": "HeatherLukas_PhDThesis.pdf", "content": "final", "filesize": 48618608, "license": "other", "mime_type": "application/pdf", "url": "/16751/1/HeatherLukas_PhDThesis.pdf", "version": "v7.0.0" }, "type": "thesis", "title": "Engineering Bioaffinity Sensors toward Continuous Electrochemical Biosensing", "author": [ { "family_name": "Lukas", "given_name": "Heather Lauren", "orcid": "0000-0002-8160-9066", "clpid": "Lukas-Heather-Lauren" } ], "thesis_advisor": [ { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "thesis_committee": [ { "family_name": "Lester", "given_name": "Henry A.", "orcid": "0000-0002-5470-5255", "clpid": "Lester-H-A" }, { "family_name": "Emami", "given_name": "Azita", "orcid": "0000-0002-6945-9958", "clpid": "Emami-A" }, { "family_name": "Shapiro", "given_name": "Mikhail G.", "orcid": "0000-0002-0291-4215", "clpid": "Shapiro-M-G" }, { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "local_group": [ { "literal": "div_eng" } ], "abstract": "The rise of wearable sensing through smartwatches and continuous glucose monitors has made health data more widely accessible. Advances in machine learning have also been pivotal in identifying personalized health insights from biometric data streams. However, continuous biochemical data has been limited in sensor design by the availability of oxidoreductases (e.g., glucose oxidase, lactate dehydrogenase) to a given target. The challenge in engineering diverse oxidoreductase enzymes has led to the exploration of other generalized approaches to continuous electrochemical biosensing. To meet this need, we have explored a variety of bioaffinity sensing schemes using broad bioreceptor classes including antibodies, nucleic acids, and periplasmic binding proteins. We present a case study in electrochemical sensor design utilizing high-affinity antibodies for the rapid diagnosis of COVID-19 disease states. We then investigate the potential of nucleic acid-based electrochemical sensors for continuous sensing with a focus on structure-switching nucleic acid aptamers. The utility of aptamer sensors is demonstrated in the development of a serotonin aptamer sensor embedded in an ingestible capsule for continuous biosensing in the gastrointestinal tract. Applying the principles of electrochemical aptamer-based sensing, we explored the development of an electrochemical protein-based sensor for nicotine, which exploits the hinge-like binding motion of periplasmic binding proteins while also capitalizing on decades of protein evolution and characterization research. With the goal of continuous, noninvasive biochemical sensing, we evaluate the design considerations and translatability of these sensors for wearable sweat analysis. These biosensing techniques may enable the future hardware necessary to expand accessible biomedical data for the next wave of personalized health monitoring.", "doi": "10.7907/2c89-k924", "publication_date": "2025", "thesis_type": "phd", "thesis_year": "2025" }, { "id": "thesis:17069", "collection": "thesis", "collection_id": "17069", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:03172025-234845488", "type": "thesis", "title": "Smart Masks for in situ Exhaled Breath Condensate Harvesting and Analysis", "author": [ { "family_name": "Heng", "given_name": "Wenzheng", "orcid": "0009-0009-5278-0727", "clpid": "Heng-Wenzheng" } ], "thesis_advisor": [ { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "thesis_committee": [ { "family_name": "Tai", "given_name": "Yu-Chong", "orcid": "0000-0001-8529-106X", "clpid": "Tai-Yu-Chong" }, { "family_name": "Yang", "given_name": "Changhuei", "orcid": "0000-0001-8791-0354", "clpid": "Yang-Changhuei" }, { "family_name": "Zhang", "given_name": "Anqi", "orcid": "0000-0001-6121-8095", "clpid": "Zhang-Anqi" }, { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "local_group": [ { "literal": "div_eng" } ], "abstract": "With the growing focus on personalized breath health management and early detection of chronic pulmonary diseases, there is an urgent demand for noninvasive wearable technologies capable of continuous breath molecular monitoring during daily activities. Existing respiratory monitoring systems remain limited to physical signal tracking and lack the capability for real-time biochemical analysis of exhaled biomarkers. To address this critical gap, we developed EBCare, a fully integrated smart mask platform for automated in situ analysis of exhaled breath condensate (EBC) biomarkers. The system combines tandem passive cooling strategies (hydrogel evaporation and radiative metamaterials) with bioinspired microfluidics to enable sustainable breath condensation and efficient sample transport under real-world conditions. A multiplexed electrochemical sensor array functionalized with nanoengineered interfaces achieves selective detection of key inflammatory markers (nitrite, pH) and metabolic indicators (ammonia, alcohol), while an embedded wireless module facilitates continuous data transmission. System validation through controlled breathing experiments and field trials demonstrates reliable operation across diverse environments (10-35\u00b0C, 30-80% humidity). Clinical evaluations involving healthy subjects, COPD/asthma patients, and post-COVID cohorts reveal EBCare's ability to dynamically track airway inflammation patterns and metabolic shifts during daily tasks. This wearable EBC analysis platform bridges the gap between laboratory-based breath testing and real-world respiratory monitoring, offering a scalable solution for home-based management of chronic respiratory conditions and post-infection recovery tracking. The modular design and automated operation framework further support future expansion to monitor airborne pathogens and systemic metabolic disease biomarkers through exhaled breath.", "doi": "10.7907/7kzx-ee44", "publication_date": "2025", "thesis_type": "phd", "thesis_year": "2025" }, { "id": "thesis:17212", "collection": "thesis", "collection_id": "17212", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:05082025-224903418", "type": "thesis", "title": "A Path Towards Wearable Affective General Intelligence", "author": [ { "family_name": "Solomon", "given_name": "Samuel Aaron", "orcid": "0000-0001-7199-6659", "clpid": "Solomon-Samuel-Aaron" } ], "thesis_advisor": [ { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "thesis_committee": [ { "family_name": "Emami", "given_name": "Azita", "orcid": "0000-0002-6945-9958", "clpid": "Emami-A" }, { "family_name": "Anandkumar", "given_name": "Anima", "orcid": "0000-0002-6974-6797", "clpid": "Anandkumar-A" }, { "family_name": "Perona", "given_name": "Pietro", "orcid": "0000-0002-7583-5809", "clpid": "Perona-P" }, { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "local_group": [ { "literal": "div_eng" } ], "abstract": "Artificial intelligence continues to support our daily decision-making tasks yet remains disconnected from our dynamic emotions driving these behaviors. Wearable technologies can supplement interactions with continuous emotion biofeedback, but existing models struggle to generalize across emerging biomarkers, platforms, and affective expressions. Here, we introduce a meta-analysis into embedding concurrent fragmented biosignals across 15 medical platforms, spanning five bodily locations, within a single profile that enables efficient and generalizable downstream affective analysis. We achieved this through a Lie manifold neural architecture that simultaneously reconstructs over 118,000 missing biometric details in 205 biomarkers and accurately forecasts 100 affective states across cohorts, questionnaires, and activities. We validated this framework across five datasets to propose a new skin-conformal, soft bioelectronic, affective computing platform that demonstrates closed-loop emotion modulation within thermal, audio, and visual interventions delivered through virtual, holographic, and conversational agents. Our framework establishes a new foundational bidirectional architecture for scalable, interpretable, and emotionally intelligent human-computer interactions.", "doi": "10.7907/2s0x-qq57", "publication_date": "2025", "thesis_type": "phd", "thesis_year": "2025" }, { "id": "thesis:16255", "collection": "thesis", "collection_id": "16255", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:12052023-185529151", "primary_object_url": { "basename": "Thesis - Jihong Min.pdf", "content": "final", "filesize": 9341850, "license": "other", "mime_type": "application/pdf", "url": "/16255/11/Thesis - Jihong Min.pdf", "version": "v6.0.0" }, "type": "thesis", "title": "Innovations in Wireless Bioelectronics for Precision Medicine, from Sustainable Sweat Sensing to Ingestible Gut Monitoring", "author": [ { "family_name": "Min", "given_name": "Jihong", "orcid": "0000-0002-5788-1473", "clpid": "Min-Jihong" } ], "thesis_advisor": [ { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "thesis_committee": [ { "family_name": "Emami", "given_name": "Azita", "orcid": "0000-0002-6945-9958", "clpid": "Emami-A" }, { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" }, { "family_name": "Shapiro", "given_name": "Mikhail G.", "orcid": "0000-0002-0291-4215", "clpid": "Shapiro-M-G" }, { "family_name": "Lester", "given_name": "Henry A.", "orcid": "0000-0002-5470-5255", "clpid": "Lester-H-A" } ], "local_group": [ { "literal": "div_eng" } ], "abstract": "Biofluids, constituting about 60% of the human body, serve as treasure troves of biomarkers such as metabolites and electrolytes, shedding light on individual health conditions. Although blood and urine tests have been routinely utilized, they are limited by their invasive and episodic nature. However, the promise of continuous and noninvasive access to other biofluids like sweat, GI fluids, and saliva paves the way for real-time, onsite health monitoring. This thesis delves into the untapped potential of wearable sensors and noninvasive biofluid analysis, emphasizing the importance of continuous and sustainable monitoring for predictive personal healthcare. Chapter 1 introduces the paradigm of biofluid sensing, focusing on sweat as a key candidate for personalized healthcare applications. Chapter 2 delves into the physiology of sweat glands, highlighting the composition of sweat and the mechanisms behind sweat extraction, either through natural exercise or iontophoretic stimulation. Chapter 3 embarks on the development of innovative sensors designed for detecting clinically pertinent biomarkers in sweat, a step forward in predictive health analytics. In Chapter 4, the spotlight is on system integration, as the study emphasizes the need for miniaturized and reliable wireless sensor devices that ensure minimal discomfort and maximum reliability. Chapters 5 and 6 delve into strategies for sustainably powering wearable devices from energy harvested from body motions and from ambient light, respectively. The final chapter, Chapter 7, extrapolates the aforementioned technologies for the realm of ingestible devices, adapting them for electrochemical sensing in alternate media, primarily gastrointestinal fluids. This allows for enhanced detection of gastrointestinal diseases and a deeper understanding of the intricate gut-brain axis. The ultimate vision of this research is to equip individuals with wearable and ingestible sensors that can seamlessly monitor a broad spectrum of clinically relevant biomarkers. This continuous monitoring, coupled with data analytics, will potentially catalyze a shift from reactive to predictive healthcare, ushering in an era of personalized therapeutic interventions. As wearable sweat and ingestible sensors become mainstream, a confluence of biosensing mechanisms, materials science, and flexible electronics is anticipated enable continuous and unobtrusive acquisition of clinically relevant biomarkers over prolonged periods and large populations, further refining the nexus between health monitoring and precision medicine.", "doi": "10.7907/kcm7-wz71", "publication_date": "2024-06-14", "thesis_type": "phd", "thesis_year": "2024" }, { "id": "thesis:16297", "collection": "thesis", "collection_id": "16297", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:02182024-070645738", "primary_object_url": { "basename": "changhao_xu_2024_thesis.pdf", "content": "final", "filesize": 61292483, "license": "other", "mime_type": "application/pdf", "url": "/16297/1/changhao_xu_2024_thesis.pdf", "version": "v4.0.0" }, "type": "thesis", "title": "Electronic Skin in Robotics and Healthcare: Towards Multimodal Sensing and Intelligent Analysis", "author": [ { "family_name": "Xu", "given_name": "Changhao", "orcid": "0000-0002-6817-3341", "clpid": "Xu-Changhao" } ], "thesis_advisor": [ { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "thesis_committee": [ { "family_name": "Gharib", "given_name": "Morteza", "orcid": "0000-0003-0754-4193", "clpid": "Gharib-M" }, { "family_name": "Yue", "given_name": "Yisong", "orcid": "0000-0001-9127-1989", "clpid": "Yue-Yisong" }, { "family_name": "Tai", "given_name": "Yu-Chong", "orcid": "0000-0001-8529-106X", "clpid": "Tai-Yu-Chong" }, { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "local_group": [ { "literal": "div_eng" } ], "abstract": "Skin-interfaced electronics is gradually transforming robotic and medical fields by enabling noninvasive and continuous monitoring of physiological and biochemical information. Despite their promise, current wearable technologies face challenges in several disciplines: Physical sensors are prone to motion-induced noise and lack the capability for effective disease detection, while existing wearable biochemical sensors suffer from operational instability in biofluids, limiting their practicality. Conventional electronic skin contains only a limited category of sensors that are not sufficient for practical applications, and conventional data processing methods for these wearables necessitate manual intervention to filter noise and decipher health-related information.
\r\n\r\nThis thesis presents advances in electronic skin within robotics and healthcare, emphasizing multimodal sensing and data analysis through machine intelligence. Chapter 1 introduces the concept of electronic skin, outlining the emerging sensor technologies and a general machine learning pipeline for data processing. Chapter 2 details the development of multimodal physiological and biochemical sensors that enable long-term continuous monitoring with high sensitivity and stability. Chapter 3 explores the application of integrated electronic skin in robotics, prosthetics, and human machine interactions. Chapter 4 showcases practical implementations of integrated electronic skin with robust sensors for wound monitoring and treatment. Chapter 5 highlights the transformative deployment of artificial intelligence in deconvoluting health profiles on mental health. The last chapter, Chapter 6, delves into the challenges and prospects of artificial intelligence-powered electronic skins, offering predictions for the evolution of smart electronic skins. We envision that multimodal sensing and machine intelligence in electronic skin could significantly advance the field of human machine interactions and personalized healthcare.
", "doi": "10.7907/en0a-ep72", "publication_date": "2024", "thesis_type": "phd", "thesis_year": "2024" }, { "id": "thesis:16239", "collection": "thesis", "collection_id": "16239", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:11062023-050222447", "type": "thesis", "title": "Wearable Sweat Sensors for Disease Monitoring and Management", "author": [ { "family_name": "Tu", "given_name": "Jiaobing", "orcid": "0000-0002-7653-6640", "clpid": "Tu-Jiaobing" } ], "thesis_advisor": [ { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "thesis_committee": [ { "family_name": "Shapiro", "given_name": "Mikhail G.", "orcid": "0000-0002-0291-4215", "clpid": "Shapiro-M-G" }, { "family_name": "Emami", "given_name": "Azita", "orcid": "0000-0002-6945-9958", "clpid": "Emami-A" }, { "family_name": "Dabiri", "given_name": "John O.", "orcid": "0000-0002-6722-9008", "clpid": "Dabiri-J-O" }, { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "local_group": [ { "literal": "div_eng" } ], "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\u2010free 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.", "doi": "10.7907/7jdg-z479", "publication_date": "2024", "thesis_type": "phd", "thesis_year": "2024" }, { "id": "thesis:15102", "collection": "thesis", "collection_id": "15102", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:02082023-162753604", "primary_object_url": { "basename": "Thesis-YiranYang-final.pdf", "content": "final", "filesize": 31535477, "license": "other", "mime_type": "application/pdf", "url": "/15102/1/Thesis-YiranYang-final.pdf", "version": "v6.0.0" }, "type": "thesis", "title": "Laser-Engraved Wearable Sweat Sensor for Metabolic Monitoring", "author": [ { "family_name": "Yang", "given_name": "Yiran (Isabella)", "orcid": "0000-0001-8770-8746", "clpid": "Yang-Yiran-Isabella" } ], "thesis_advisor": [ { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "thesis_committee": [ { "family_name": "Tai", "given_name": "Yu-Chong", "orcid": "0000-0001-8529-106X", "clpid": "Tai-Yu-Chong" }, { "family_name": "Emami", "given_name": "Azita", "orcid": "0000-0002-6945-9958", "clpid": "Emami-A" }, { "family_name": "Gharib", "given_name": "Morteza", "orcid": "0000-0003-0754-4193", "clpid": "Gharib-M" }, { "family_name": "Gao", "given_name": "Wei", "orcid": "0000-0002-8503-4562", "clpid": "Gao-Wei" } ], "local_group": [ { "literal": "div_eng" } ], "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\u2019s 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.", "doi": "10.7907/5yfm-tt16", "publication_date": "2023", "thesis_type": "phd", "thesis_year": "2023" } ]