Key points are not available for this paper at this time.
Abstract The prosperous evolution of conductive hydrogel‐based skin sensors is attracting tremendous attention nowadays. Nevertheless, it remains a great challenge to simultaneously integrate excellent mechanical strength, desirable electrical conductivity, admirable sensing performance, and brilliant healability in hydrogel‐based skin sensors for high‐performance diagnostic healthcare sensing and wearable human‐machine interface, as well as robust photothermal performance for promptly intelligent photothermal therapy followed by the medical diagnosis and superior electromagnetic interference (EMI) shielding performance for personal protection. Herein, a flexible healable MXene hydrogel‐based skin sensor is prepared through a delicate combination of MXene (Ti 3 C 2 T x ) nanosheets network with the polymeric network. The as‐prepared skin sensor is featured with significantly enhanced mechanical, conducting, and sensing performances, along with robust self‐healability, good biocompatibility, and reliable injectability, enabling ultrasensitive human motion monitoring and teeny electrophysiological signals sensing. As a frontier technology in artificial intelligence, machine learning can facilitate to efficiently and precisely identify the electromyography signals produced by various human motions (such as variable finger gestures) with up to 99.5% accuracy, affirming the reliability of the machine learning‐assisted gesture identification with great potential in smart personalized healthcare and human‐machine interaction. Moreover, the MXene hydrogel‐based skin sensor displays prominent EMI shielding performance, demonstrating the great promise of effective personal protection.
Zhang et al. (Mon,) studied this question.