Anisotropic hydrogel sensors with muscle-like structures based on high-absorbent alginate fibers

Abstract

Hydrogel sensors have attracted much attention as they play a critical role in health monitoring, multifunctional electronic skin, and human-machine interfaces. However, the isotropic structure makes existing hydrogel sensors exhibit isotropic sensing performance. Therefore, it is a challenge to fabricate hydrogels with human tissue-like structures to achieve anisotropic sensing performance. Herein, we proposed a novel method to prepare anisotropic hydrogel sensors using high-absorbent alginate fibers. The anisotropic hydrogel, HAFG@CNTs, was prepared by adsorbing carbon nanotubes on high-absorbent alginate fibers and immobilized using polyacrylamide bonds. The hydrogel had anisotropic mechanical properties and anisotropic ionic conductivity. The modulus and toughness in the parallel fiber direction were 2.31 and 3.75 times higher than those in the perpendicular fiber direction, respectively, and the sensitivity of the parallel fiber direction was higher than that of the vertical direction when strain occurred. In addition, machine learning algorithms were used to predict and classify different action signals obtained from HAFG@CNTs with an accuracy of up to 98.18 %. These advantages offer great potential for applying HAFG@CNTs to wearable devices and medical monitoring.