TY - JOUR
T1 - Multiscale and Hierarchical Wrinkle Enhanced Graphene/Ecoflex Sensors Integrated with Human-Machine Interfaces and Cloud-Platform
AU - Zhou, Jian
AU - Long, Xinxin
AU - Huang, Jian
AU - Jiang, Caixuan
AU - Zhou, Fengling
AU - Guo, Chen
AU - Li, Honglang
AU - Fu, Yongqing
AU - Duan, Huigao
N1 - Funding information:
This work was supported by the NSFC (No.52075162), The Program of New and High-tech Industry of Hunan Province(2020GK2015), The Joint Fund Project of the Ministry of Education, The Excellent Youth Fund of Hunan Province (2021JJ20018), the Key Research & Development Program of Guangdong Province (2020B0101040002), the Natural Science Foundation of Changsha (kq2007026), the Engineering Physics and Science Research Council of UK (EPSRC EP/P018998/1) and International Exchange Grant (IEC/NSFC/201078) through Royal Society and the NSFC
PY - 2022/7/5
Y1 - 2022/7/5
N2 - 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 real-time using a cloud platform, showing a great potential for the 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.
AB - 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 real-time using a cloud platform, showing a great potential for the 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.
KW - Wrinkle
KW - Flexible strain sensor
KW - Cloud platform monitoring
KW - Human-Machine Interface
UR - http://www.scopus.com/inward/record.url?scp=85133430261&partnerID=8YFLogxK
U2 - 10.1038/s41528-022-00189-1
DO - 10.1038/s41528-022-00189-1
M3 - Article
SN - 2397-4621
VL - 6
JO - npj Flexible Electronics
JF - npj Flexible Electronics
IS - 1
M1 - 55
ER -
