Dual‐Anchored Interfacial Adhesion‐Enhanced Strain‐Insensitive Hydrogels Electronic Skin for Consciousness‐Driven Brain‐Computer Interface
Deliang Li, Hongxing Zhou, Le Liu, Chenxi Jing, Kunpeng Ji, Guanshi Liu, Haoqi Bai, Huilin Yuan 等 13 位
Northeastern University Foshan University
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
Hydrogel‐based flexible circuits demand robust rigid‐soft interfacial adhesion, strain‐insensitive electrical performance, and reliable digital‐analog signal transmission capabilities to enable high‐performance electronic skin (e‐skin) applications. Here, we developed a 3D‐printable AgNSs/AA‐DMAPS hydrogel with tunable viscosity via a dual‐anchoring strategy, where silver nanosheets (AgNSs) create nano‐adhesion by forming dynamic crosslinked hydrogel networks. The resulting hydrogel exhibits strain insensitivity within 500% elongation, high electrical conductivity (>16 × 10 4 S/m), and superior multi‐interfacial adhesion properties. Notably, the dual‐anchoring design enables dynamic bonding with metal surfaces (∼450 kPa), allowing self‐welding to hardware without treatment. Flexible circuits printed with AgNSs/AA‐DMAPS hydrogel demonstrate near‐field communication (NFC) functionality and wireless charging, with flexible printed circuit (FPC) capable of transmitting high‐speed signals up to 8 MHz while maintaining effective image signal transmission under 50% strain. Our printed brain‐computer interface (BCI) e‐skin based on this hydrogel achieves EEG signal monitoring. In consciousness classification tasks using the BCI e‐skin, our proposed CNN‐LSTM model attained 90.8% accuracy across six categories. The classification system was deployed on a local server to drive robotic manipulation, enabling real‐time EEG‐controlled robotic hand movement through locally models. The AgNSs/AA‐DMAPS hydrogel‐based BCI e‐skin opens new possibilities for daily brain monitoring applications and continuous exploration of neuropsychiatric disease progression patterns.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
工程Advanced Sensor and Energy Harvesting Materials
Neuroscience and Neural Engineering · Advanced Materials and Mechanics
参考文献 18
此处列出前 3 条
引用本文 1
按被引量排序,此处列出前 3 条