1. A Flexible Smart Healthcare Platform Conjugated with Artificial Epidermis Assembled by Three-Dimensionally Conductive MOF Network for Gas and Pressure Sensing.
- Author
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Zhou, Qingqing, Ding, Qihang, Geng, Zixun, Hu, Chencheng, Yang, Long, Kan, Zitong, Dong, Biao, Won, Miae, Song, Hongwei, Xu, Lin, and Kim, Jong Seung
- Subjects
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MACHINE learning , *FLEXIBLE printed circuits , *FLEXIBLE electronics , *LOGIC circuit design , *MOBILE apps - Abstract
The rising flexible and intelligent electronics greatly facilitate the noninvasive and timely tracking of physiological information in telemedicine healthcare. Meticulously building bionic-sensitive moieties is vital for designing efficient electronic skin with advanced cognitive functionalities to pluralistically capture external stimuli. However, realistic mimesis, both in the skin's three-dimensional interlocked hierarchical structures and synchronous encoding multistimuli information capacities, remains a challenging yet vital need for simplifying the design of flexible logic circuits. Herein, we construct an artificial epidermal device by in situ growing Cu3(HHTP)2 particles onto the hollow spherical Ti3C2Tx surface, aiming to concurrently emulate the spinous and granular layers of the skin's epidermis. The bionic Ti3C2Tx@Cu3(HHTP)2 exhibits independent NO2 and pressure response, as well as novel functionalities such as acoustic signature perception and Morse code-encrypted message communication. Ultimately, a wearable alarming system with a mobile application terminal is self-developed by integrating the bimodular senor into flexible printed circuits. This system can assess risk factors related with asthmatic, such as stimulation of external NO2 gas, abnormal expiratory behavior and exertion degrees of fingers, achieving a recognition accuracy of 97.6% as assisted by a machine learning algorithm. Our work provides a feasible routine to develop intelligent multifunctional healthcare equipment for burgeoning transformative telemedicine diagnosis. Highlights: A smart wearable alarming system integrated artificial epidermal device for pluralistically identifying asthmatic attack risk factors, achieving a 97.6% classification accuracy as assisted by machine learning algorithm. A meticulous mimicry both in the advanced structural attributes and encoding information abilities of the skin was adopted to design a novel artificial epidermal device by integrating conductive Cu3(HHTP)2 coupled with spherical Ti3C2Tx. The bioinspired Ti3C2Tx@Cu3(HHTP)2 sensors can independently perceive NO2 gas and pressure-triggered stimuli. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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