Abstract：
Pursuing high-performance conductive hydrogels is still hot topic in development of advanced flexible wearable devices. Herein, a tough, self-healing, adhesive double network (DN) conductive hydrogel (named as OSA-(Gelatin/PAM)-Ca, O-(G/P)-Ca) was prepared by bridging gelatin and polyacrylamide network with functionalized polysaccharide (oxidized sodium alginate, OSA) through Schiff base reaction. Thanks to the presence of multiple interactions (Schiff base bond, hydrogen bond, and metal coordination) within the network, the prepared hydrogel showed outstanding mechanical properties (tensile strain of 2800 % and stress of 630 kPa), high conductivity (0.72 S/m), repeatable adhesion performance and excellent self-healing ability (83.6 %/79.0 % of the original tensile strain/stress after self-healing). Moreover, the hydrogel-based sensor exhibited high strain sensitivity (GF = 3.66) and fast response time (<0.5 s), which can be used to monitor a wide range of human physiological signals. Based on this, excellent compression sensitivity (GF = 0.41 kPa-1 in the range of 90-120 kPa), a three-dimensional (3D) array of flexible sensor was designed to monitor the intensity of pressure and spatial force distribution. In addition, a gel-based wearable sensor was accurately classified and recognized ten types of gestures, achieving an accuracy rate of >96.33 % both before and after self-healing under three machine learning models (the decision tree, SVM, and KNN). This paper provides a simple method to prepare tough and self-healing conductive hydrogel as flexible multifunctional sensor devices for versatile applications in fields such as healthcare monitoring, human-computer interaction, and artificial intelligence.
摘要：
追求高性能导电水凝胶仍然是先进柔性可穿戴设备开发的热门话题。在这里，一个艰难的，自我修复,粘合剂双网络（DN）导电水凝胶（命名为OSA-（明胶/PAM）-Ca，O-（G/P）-Ca）是通过将明胶和聚丙烯酰胺网络与功能化多糖（氧化海藻酸钠，OSA)通过希夫碱反应。由于存在多种相互作用(希夫碱基键，氢键,和金属协调)在网络内，所制备的水凝胶表现出优异的机械性能(拉伸应变2800%,应力630kPa),高电导率（0.72S/m），可重复的粘附性能和优异的自修复能力(自修复后原始拉伸应变/应力的83.6%/79.0%)。此外，基于水凝胶的传感器表现出高应变灵敏度（GF=3.66）和快速响应时间（<0.5s），可用于监测广泛的人体生理信号。基于此,优异的压缩灵敏度（GF=0.41kPa-1在90-120kPa范围内），设计了三维（3D）柔性传感器阵列来监测压力强度和空间力分布。此外,基于凝胶的可穿戴传感器被准确地分类和识别十种类型的手势，在三种机器学习模型(决策树，SVM,和KNN）。本文提供了一种简单的方法来制备坚韧和自我修复的导电水凝胶作为柔性多功能传感器设备，用于医疗保健监测等领域的多功能应用。人机交互,和人工智能。
