用于机器学习辅助高灵敏传感生物电极的柔性可愈合电磁干扰屏蔽生物弹性水凝胶纳米复合材料

IF 13.9 Q1 CHEMISTRY, MULTIDISCIPLINARY
Yunfei Zhang, Zehui Li, Zhishan Xu, Mingyue Xiao, Yue Yuan, Xiaolong Jia, Rui Shi, Liqun Zhang, Pengbo Wan
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引用次数: 0

摘要

如今,基于导电水凝胶的皮肤传感器的蓬勃发展正吸引着人们的极大关注。然而,如何在水凝胶皮肤传感器中同时集成优异的机械强度、理想的导电性、令人赞叹的传感性能和出色的可愈合性,使其既能用于高性能医疗诊断传感和可穿戴人机界面,又能具有强大的光热性能,以便在医疗诊断后及时进行智能光热治疗,还能具有出色的电磁干扰(EMI)屏蔽性能,保护个人安全,这仍然是一个巨大的挑战。本文通过 MXene(Ti3C2Tx)纳米片网络与聚合物网络的巧妙结合,制备了一种基于 MXene 水凝胶的柔性可愈合皮肤传感器。制备出的皮肤传感器具有显著增强的机械、导电和传感性能,同时具有强大的自愈性、良好的生物相容性和可靠的注射性,可实现超灵敏人体运动监测和微弱电生理信号传感。作为人工智能领域的前沿技术,机器学习可以高效、精确地识别各种人体运动(如手指的各种手势)产生的肌电信号,准确率高达 99.5%,这充分证明了机器学习辅助手势识别的可靠性,在智能个性化医疗和人机交互领域具有巨大潜力。此外,基于 MXene 水凝胶的皮肤传感器还具有出色的电磁干扰屏蔽性能,为有效的个人防护带来了巨大希望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Flexible healable electromagnetic-interference-shielding bioelastic hydrogel nanocomposite for machine learning-assisted highly sensitive sensing bioelectrode

Flexible healable electromagnetic-interference-shielding bioelastic hydrogel nanocomposite for machine learning-assisted highly sensitive sensing bioelectrode

Flexible healable electromagnetic-interference-shielding bioelastic hydrogel nanocomposite for machine learning-assisted highly sensitive sensing bioelectrode

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 (Ti3C2Tx) 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.

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