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Multifunctional and Reconfigurable Electronic Fabrics Assisted by Artificial Intelligence for Human Augmentation

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Abstract

Noninvasive human augmentation, namely a desirable approach for enhancing the quality of life, can be achieved through wearable electronic devices that interact with the external environment. Wearable electronic devices endure limitations, such as unreliable signal interaction when bent or deformed, excessive wiring requirements, and lack of programmability and multifunctionality. Herein, we report an intelligent and programmable (IP) fabric sensor with bending insensitivity that overcomes these challenges associated with a rapid response time (< 400 μs) and exceptional durability (> 20,000 loading–unloading cycles). A single-layer parallel electrical bilateral structure is utilized to design the IP fabric sensor with reconfigurability and only two electrodes, which caters to the requirement of stable interactions and simple wiring. The multifunctionality of the IP fabric sensor is demonstrated by designing a closed-loop interactive entertainment system, a smart home system, and a user identification and verification system. This integrated system reveals the potential of combining Internet of Things technology and artificial intelligence (AI). Hopefully, the integration of the noninvasive IP fabric sensor with AI will facilitate the advancement of interactive systems for human augmentation.

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Acknowledgements

This work was supported by National Natural Science Foundation of China (52202117), Natural Science Foundation of Fujian Province of China (2022J01065), Collaborative Innovation Platform Project of Fu-Xia-Quan National Independent Innovation Demonstration Zone (3502ZCQXT2022005), and Fundamental Research Funds for the Central Universities (20720220075).

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Authors and Affiliations

  1. Department of Electronic Science, Xiamen University, Xiamen, 361005, China

    Zihan Chen, Wansheng Lin, Cuirong Zhang, Yijing Xu, Chao Wei, Xinqin Liao & Zhong Chen

  2. College of Photonic and Electronic Engineering, Fujian Normal University, Fuzhou, 350007, China

    Zihan Chen & Huanqiang Hu

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  1. Zihan Chen
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  2. Wansheng Lin
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  3. Cuirong Zhang
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  7. Xinqin Liao
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Correspondence to Xinqin Liao or Zhong Chen.

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Chen, Z., Lin, W., Zhang, C. et al. Multifunctional and Reconfigurable Electronic Fabrics Assisted by Artificial Intelligence for Human Augmentation. Adv. Fiber Mater. 6, 229–242 (2024). https://doi.org/10.1007/s42765-023-00350-z

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  • DOI: https://doi.org/10.1007/s42765-023-00350-z

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