Lu Lijun, Hu Guosheng, Liu Jingquan, Yang Bin
Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou, 450001, China.
National Key Laboratory of Science and Technology on Micro/Nano Fabrication, Shanghai Jiao Tong University, Shanghai, 200240, China.
Adv Sci (Weinh). 2024 May;11(18):e2309894. doi: 10.1002/advs.202309894. Epub 2024 Mar 9.
Real-time telemedicine detection can solve the problem of the shortage of public medical resources caused by the coming aging society. However, the development of such an integrated monitoring system is hampered by the need for high-performance sensors and the strict-requirement of long-distance signal transmission and reproduction. Here, a bionic crack-spring fiber sensor (CSFS) inspired by spider leg and cirrus whiskers for stretchable and weavable electronics is reported. Trans-scale conductive percolation networks of multilayer graphene around the surface of outer spring-like Polyethylene terephthalate (PET) fibers and printing Ag enable a high sensitivity of 28475.6 and broad sensing range over 250%. The electromechanical changes in different stretching stages are simulated by Comsol to explain the response mechanism. The CSFS is incorporated into the fabric and realized the human-machine interactions (HMIs) for robot control. Furthermore, the 5G Narrowband Internet of Things (NB-IoT) system is developed for human healthcare data collection, transmission, and reproduction together with the integration of the CSFS, illustrating the huge potential of the approach in human-machine communication interfaces and intelligent telemedicine rehabilitation and diagnosis monitoring.
实时远程医疗检测可以解决即将到来的老龄化社会所导致的公共医疗资源短缺问题。然而,这种集成监测系统的发展受到高性能传感器需求以及长距离信号传输和再现的严格要求的阻碍。在此,报道了一种受蜘蛛腿和触须启发的用于可拉伸和可编织电子产品的仿生裂纹弹簧纤维传感器(CSFS)。外层弹簧状聚对苯二甲酸乙二酯(PET)纤维表面周围的多层石墨烯跨尺度导电渗流网络以及印刷银实现了28475.6的高灵敏度和超过250%的宽传感范围。通过Comsol模拟了不同拉伸阶段的机电变化以解释响应机制。CSFS被整合到织物中并实现了用于机器人控制的人机交互(HMI)。此外,开发了5G窄带物联网(NB-IoT)系统,用于与CSFS集成一起进行人体健康数据的收集、传输和再现,说明了该方法在人机通信接口以及智能远程医疗康复和诊断监测方面的巨大潜力。