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Updated: Jul 1, 2025

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A Silicon-tipped Fiber-optic Sensing Platform with High Resolution and Fast Response
Published on: January 7, 2019
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5G NB-IoT System Integrated with High-Performance Fiber Sensor Inspired by Cirrus and Spider Structures
Lijun Lu1,2,3, Guosheng Hu2,3, Jingquan Liu2
1Key Laboratory of Materials Physics of Ministry of Education, School of Physics and Microelectronics, Zhengzhou University, Zhengzhou, 450001, China.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|March 9, 2024
Summary
A novel bionic crack-spring fiber sensor (CSFS) offers high sensitivity for telemedicine applications. This stretchable and weavable sensor integrates with 5G NB-IoT for remote healthcare monitoring and human-machine interactions.
Area of Science:
- Materials Science
- Biomedical Engineering
- Electronics
Background:
- Aging societies face public medical resource shortages, necessitating advanced telemedicine solutions.
- Developing integrated monitoring systems is challenging due to high-performance sensor requirements and signal transmission limitations.
Purpose of the Study:
- To develop a bionic crack-spring fiber sensor (CSFS) for stretchable electronics.
- To enable high-performance, real-time telemedicine detection and human-machine interactions.
Main Methods:
- Fabrication of CSFS using multilayer graphene and printed Ag on PET fibers.
- Electromechanical characterization and Comsol simulation of sensor response.
- Integration of CSFS with a 5G Narrowband Internet of Things (NB-IoT) system.
Main Results:
- Achieved high sensitivity (28475.6) and a broad sensing range (>250%).
- Demonstrated CSFS's incorporation into fabric for human-machine interactions (HMIs).
- Successfully developed a 5G NB-IoT system for healthcare data transmission.
Conclusions:
- The bionic CSFS shows significant potential for intelligent telemedicine and rehabilitation.
- The integrated system facilitates advanced human-machine communication interfaces.
- This technology addresses challenges in remote healthcare monitoring and diagnosis.

