Recent Advances in Hydrogel‐Based Soft Bioelectronics and its Convergence with Machine Learning

生物电子学 材料科学 纳米技术 趋同(经济学) 高分子科学 生物传感器 经济增长 经济
作者
Eun Seo Lee,Min Young Lee,Dae‐Hyeong Kim,Ja Hoon Koo
出处
期刊:Advanced Engineering Materials [Wiley]
卷期号:26 (22) 被引量:15
标识
DOI:10.1002/adem.202401432
摘要

Recent advancements in artificial intelligence (AI) technologies, particularly machine learning (ML) techniques, have opened up a promising frontier in the development of intelligent soft bioelectronics, demonstrating unparalleled performance in interfacing with the human body. Hydrogels, owing to their unique combination of biocompatibility, tunable mechanical properties, and high water content, have emerged as a versatile platform for constructing soft bioelectronic devices. Functionalized hydrogels, such as conductive hydrogels, can efficiently capture biosignals from various target tissues while seamlessly forming conformal and reliable interfaces. They can also function as an intermediary layer between biological tissues and soft bioelectronics for diagnosis and therapy purposes. Meanwhile, ML has demonstrated its efficacy in processing extensive datasets collected from the bioelectronics. The convergence of hydrogel‐based soft bioelectronics and ML has unlocked a myriad of possibilities in unprecedented diagnostics, therapeutics, and beyond. In this review, the latest advances in hydrogel‐based soft bioelectronics are introduced. After briefly describing the materials and device strategies for high‐performance hydrogel bioelectronics, how ML can be integrated to augment the functionalities is discussed. Recent examples of ML‐integrated hydrogel bioelectronics are then discussed. Finally, the review is concluded by introducing future potential applications of AI in hydrogel‐based bioelectronics, alongside inherent challenges in this interdisciplinary domain.
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