SNU CBE

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

2024 · Advanced Engineering Materials

저자

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

연구주제

Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Hydrogels: synthesis, properties, applications

NTIS 과학기술표준분류

가장 가까운 분류(재료 > 고분자재료 > 의료용 소재기술)가 화학·화공 범위 밖이다. 배정 근거: AI 키워드가 잡은 NTIS 과제의 분류.

AI 연구 키워드·방법

전도성 하이드로젤 hydrogel bioelectronics 연성 생체전자소자

기계학습

키워드 (OpenAlex)

machine learning integration conductive hydrogels

초록

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 bioelect…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

연도과제부처사업수행기관NTIS 분류(1순위)
2024나노입자의 합성과 의료, 에너지 분야 응용과학기술정보통신부기초과학연구원연구운영비지원(주요사업비)기초과학연구원–

인접 그래프

노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동

이 문서와 연결된 페이지

교수 1

김대형

연구주제 1

Advanced Sensor and Energy Harvesting Materials

키워드 2

연성 생체전자소자 · 전도성 하이드로젤

방법 1

기계학습