材料科学
纳米技术
桥接(联网)
仿生学
杰纳斯
信号(编程语言)
共形矩阵
微流控
聚合物
粘附
生物电子学
纳米尺度
计算机科学
干扰(通信)
弹性体
人体运动
杰纳斯粒子
粘弹性
运动(物理)
生物系统
作者
Baijie Cheng,Yexi Jin,Ruixue Wang,Peipei Xu,Xueying Wu,Nan Wang,Hongyao Xu,Shanyi Guang
摘要
ABSTRACT The recording of high‐fidelity electrophysiological signals is the cornerstone of bioelectronics development. However, overcoming signal interference caused by motion artifacts and unintended adhesion during daily activities remains a challenge. This paper introduces a biomimetic Janus eutectogels with dynamic compliance, in which the adhesive matrix contains hierarchical physical interactions composed of hydrogen bonds and ion‐dipole interactions, allowing the polymer network to remain in a gel point state where viscosity and elasticity are nearly equivalent within the deformation frequency range of human skin (0.01‐100 Hz). The anti‐adhesive top surface at the nanoscale is formed by the self‐aggregation of amphiphilic polyhedral oligomeric silsesquioxane (POSS) acting as a giant surfactant at the liquid‐air interface. The adhesion strength difference between the top and bottom surfaces reaches up to 52‐fold. The eutectogel can avoid signal interference induced by motion artifacts and unintended adhesion under various physiological conditions, enabling high‐fidelity acquisition of diverse electrophysiological signals (including electromyography, electrocardiography, and electroencephalography). We further integrated device integration and deep learning technology to construct an intelligent motion monitoring system, which conducts hierarchical evaluation of motion states and achieves a classification accuracy of up to 92.4%, demonstrating the potential of the material for physiological monitoring in real‐world motion scenarios.
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