Dual‐Anchored Interfacial Adhesion‐Enhanced Strain‐Insensitive Hydrogels Electronic Skin for Consciousness‐Driven Brain‐Computer Interface

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Authors: Deliang Li, Hongxing Zhou, Le Liu, Chenxi Jing, Kunpeng Ji, Guanshi Liu, Haoqi Bai, Huilin Yuan, Hongguo Wei, Wenwen Zhang, Dayu Hu, He Liu
+1 more Ye Tian
Cited by: 6
References: 18

Abstract

ABSTRACT 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.

Fields of Study & Subjects

Advanced Sensor and Energy Harvesting Materials Neuroscience and Neural Engineering Advanced Materials and Mechanics

Publication details

Journal / source
Advanced Functional Materials
Publisher
Wiley
Volume
36
Issue
47
Publication date
24 April 2026
Language
EN