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

Jian Zhou, Xinxin Long, Jian Huang, Caixuan Jiang, Fengling Zhou, Chen Guo, Honglang Li, Yongqing Fu, Huigao Duan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
Article number55
Number of pages11
Journalnpj Flexible Electronics
Volume6
Issue number1
DOIs
Publication statusPublished - 5 Jul 2022

Fingerprint

Dive into the research topics of 'Multiscale and Hierarchical Wrinkle Enhanced Graphene/Ecoflex Sensors Integrated with Human-Machine Interfaces and Cloud-Platform'. Together they form a unique fingerprint.

Cite this