journal article·2024-11Open access

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

Eun Seo Lee, Min Young Lee, Dae‐Hyeong Kim, Ja Hoon Koo

Advanced Engineering Materials· Volume 26· Issue 22

Abstract

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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Advanced Memory and Neural Computing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Intelligent Mechatronics Engineering Sejong University Seoul 05006 Republic of Korea

Department of Electronics and Information Engineering Sejong University Seoul 05006 Republic of Korea

Center for Nanoparticle Research Institute for Basic Science Seoul 08826 Republic of Korea

School of Chemical and Biological Engineering Institute of Chemical Processes Seoul National University (SNU) Seoul 08826 Republic of Korea

Department of Materials Science and Engineering SNU Seoul 08826 Republic of Korea

Interdisciplinary Program for Bioengineering SNU Seoul 08826 Republic of Korea

Department of Semiconductor Systems Engineering Sejong University Seoul 05006 Republic of Korea

Institute of Semiconductor and System IC Sejong University Seoul 05006 Republic of Korea

Funding

National Research Foundation of Korea

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