Multiscale and Hierarchical Wrinkle Enhanced Graphene/Ecoflex Sensors Integrated with Human-Machine Interfaces and Cloud-Platform

Zhou, Jian, Long, Xinxin, Huang, Jian, Jiang, Caixuan, Zhou, Fengling, Guo, Chen, Li, Honglang, Fu, Yong Qing and Duan, Huigao (2022) Multiscale and Hierarchical Wrinkle Enhanced Graphene/Ecoflex Sensors Integrated with Human-Machine Interfaces and Cloud-Platform. npj Flexible Electronics, 6 (1). p. 55. ISSN 2397-4621

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Abstract

Current state-of-the-art stretchable/flexible sensors have received stringent demands on sensitivity, flexibility, linearity, and wide-range measurement capability. Herein, we report a methodology of strain sensors based on graphene/Ecoflex composites by modulating multiscale/hierarchical wrinkles on flexible substrates. The sensor shows an ultra-high sensitivity with a gauge factor of 1078.1, a stretchability of 650, a response time of ~140 ms, and a superior cycling durability . It can detect wide-range physiological signals including vigorous body motions, pulse monitoring and speech recognition, and be used for monitoring of human respirations in realtime using a cloud platform, showing a great potential for healthcare internet of things. Complex gestures/sign languages can be precisely detected. Human-machine interface is demonstrated by using a sensor-integrated glove to remotely control an external manipulator to remotely defuse a bomb. This study provides strategies for real-time/long-range medical diagnosis and remote assistance to perform dangerous tasks in industry and military fields.

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