Executive Summary: Advances in tissue-like soft bioelectronics have shown great potential to transform hospital-based healthcare into human-centered precision healthcare. Our research addresses a central challenge in this transition: how to reliably measure evolving biological states and use this information to guide timely, personalized, adaptive treatment. As illustrated in the figure above, our long-term vision is to develop soft bioelectronic systems that continuously monitor physiological and biochemical signals, use machine learning (ML) to assess health status and predict emerging risks, and guide interventions that adapt to individual needs and evolving body states. To advance this vision, we develop multifunctional porous biointerfaces for long-term tissue compatibility and reliable biosensing during motion; integrate multimodal sensing, ML-enabled interpretation, and programmable therapeutic delivery and stimulation; and pursue cost-effective, scalable manufacturing of customized soft bioelectronics. Our work spans applications in cardiovascular monitoring, biofilm theranostics, tissue regeneration, periodontitis treatment, and elderly care. By connecting biological information with responsive interventions, we aim to advance personalized healthcare that supports early diagnosis, timely intervention, and proactive disease management.
Multifunctional Porous Biointerfaces for Long-Term Biocompatibility and Dynamic Reliability: Our research in this direction focuses on understanding device–biology interactions and developing multifunctional porous biointerfaces to improve long-term biocompatibility and reliability under dynamic bodily conditions. Over the past decade, substantial progress has been made in developing soft bioelectronics with high flexibility and stretchability and integrating electronic components into wireless systems. However, achieving reliable operation over weeks to months remains challenging for many devices because of limited long-term biocompatibility, material degradation, and artifacts caused by dynamic bodily and environmental conditions. As illustrated in the figure above, soft bioelectronics must meet several critical criteria to enable long-term, real-world applications. Our SMBE Lab has pioneered the development of multifunctional porous biointerfaces to address these challenges. In recent studies, we have created porous bioelectronic materials with features that include ultrasoftness, high breathability, antimicrobial properties, and strain-insensitive electrical conductance (Advanced Materials 2018, 30, 1804327; PNAS 2020, 117, 205; ACS Nano 2022, 16, 5874; Science Advances 2023, 9, eadf0575; Advanced Functional Materials 2023, 2302681; Nature Nanotechnology 2024, 19, 1158-1167; Advanced Materials 2024, 36, 2411587; Materials Today 2025, 82, 123-138; and Science Advances 2025, 44, eadt4923). Our future work will focus on developing porous biointerfaces with additional features, including adaptive adhesion, noise damping, immunomodulation, on-demand biodegradability, and strain-insensitive electrochemical and semiconducting properties, through molecular and structural engineering and ML-driven materials discovery. We will investigate their interactions with various biological tissues through animal and human studies. Through these advances, we aim to develop soft bioelectronics that maintain tissue compatibility and reliable function over extended periods and under dynamic conditions, advancing personalized healthcare and beyond.
Advancing Bio-Manufacturing of Soft Bioelectronics: Our research in this area focuses on developing cutting-edge bio-manufacturing techniques for rapid prototyping and large-scale production of soft bioelectronics with customized functions. These devices, designed for direct contact with the skin or other organs, play a critical role in physiological monitoring and therapeutic interventions. Ideally, they should be disposable (one-time use) to minimize infection risks. Moreover, fabricating soft bioelectronics with customized functions is essential to meet the diverse needs of individuals based on their unique physiological conditions, lifestyles, and environments, ultimately advancing precision healthcare. Currently, the predominant method for fabricating bioelectronics relies on cleanroom-based nano/microfabrication techniques, such as electron-beam or photolithography, vacuum deposition, etching, and transfer printing. While effective, these methods are costly, labor-intensive, and lack design flexibility. To address these limitations, our SMBE lab has been pioneering innovative bio-manufacturing approaches—including pencil drawing, laser scribing, and solution printing (PNAS 2020, 117, 18292; Science Advances 2022, 8, eabp9734; and Advanced Materials 2024, 36, 2411587)—to enable cost-effective, customizable, high-throughput production of soft bioelectronics. Our ultimate vision is to develop autonomous, AI-powered, closed-loop bio-manufacturing systems capable of producing high-quality, multimaterial, multilayer soft bioelectronics on demand. Imagine a future where bioelectronic printers, akin to standard office printers, are readily available in clinical settings. Healthcare providers could use these systems to fabricate patient-specific bioelectronics in real time, optimizing diagnostics and treatment while enhancing accessibility and affordability. We believe our efforts will drive transformative advancements in precision healthcare, making it more personalized and cost-effective.
Intelligent Multimodal Biosensing and Responsive Therapies: Our research in this area focuses on developing customized soft bioelectronic systems that connect multimodal biosensing with adaptive treatment. We seek to answer a central question: How can continuous, multimodal measurements guide interventions that respond to changing physiological conditions and treatment responses? To address this question, we integrate physiological and biochemical sensing with machine learning to assess health status and predict emerging risks. We also develop programmable therapeutic delivery and stimulation strategies that can be guided by these measurements. Our approach follows a cycle of sensing, interpretation, intervention, and evaluation of treatment response. Our recent cardiovascular research combines electrical and mechanical measurements with machine learning to classify cardiac conditions during movement, laying the groundwork for more comprehensive cardiovascular monitoring and timely intervention for acute cardiac events, such as heart attacks (Science Advances 2025, 11, eadv2406). We are also exploring applications in chronic wound care, tissue regeneration, periodontitis treatment, neural interfaces, and healthcare for older adults. Looking ahead, we aim to integrate sensing and therapeutic capabilities into closed-loop systems that adapt to individual needs, supporting early diagnosis, timely intervention, and proactive disease management.