Multifunctional Flexible\nSensor with the Hybrid Staggered-Rib\nConductive Network for Intelligent Recognition of Human Biomechanical\nand Electrophysiological Signals
Flexible sensors as emerging wearable electronics are\nwidely utilized\nin exercise guidance, medical services, intelligent robots, etc.,\nproviding rich data for the Internet of Things and promoting the intelligence\nand convenience of people’s lives. However, it is still difficult\nto design and fabricate multifunctional flexible sensors with excellent\ncomprehensive performance and universality by balancing various sensing\nparameters in a scientific and economical way. Herein, a flexible\nsensor with a synergistic conductive network composed of linear and\nstaggered-rib conductive pathways is prepared by screen printing,\nwhich realizes the improvement of comprehensive sensing performance\nand the expansion of functions. The prepared flexible sensor exhibits\nultrahigh sensitivity, wide response range, excellent stability, and\ndurability and has been successfully applied to detect human biomechanical\nsignals induced by mouth opening, chewing, swallowing, breathing,\nclenching, and various joint movements. The motion pattern recognition\nfor different movements of the knee joint is achieved by artificial\nintelligence with a high accuracy of 93.7%. Furthermore, the portable\nwireless physiological monitoring device assembled by the prepared\nsensor is developed to continuously monitor the electromyography (EMG)\nand electrocardiogram (ECG) signals for a long time, stably, reliably,\nand accurately in a noninvasive and wearable manner, which can provide\nhigh-value big data support for health warning, early disease screening,\nand diagnosis, showing great application potential and commercial\nvalue in the field of intelligent medicine and personalized health\ncare. The innovative and scalable sensing performance optimization\nstrategy proposed in this work promotes the popularization and application\nof high-performance and multifunctional wearable electronics.
Publication Details
- Journal
- Figshare
- Published
- 2024-10-06
- DOI
- https://doi.org/10.1021/acsanm.4c04636.s008
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 0.00