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All-printed nanomembrane wireless bioelectronics using a biocompatible solderable graphene for multimodal human-machine interfaces

Author

Listed:
  • Young-Tae Kwon

    (George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology)

  • Yun-Soung Kim

    (George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology)

  • Shinjae Kwon

    (George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology)

  • Musa Mahmood

    (George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology)

  • Hyo-Ryoung Lim

    (George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology)

  • Si-Woo Park

    (Hanyang University)

  • Sung-Oong Kang

    (Hanyang University)

  • Jeongmoon J. Choi

    (School of Biological Sciences, Georgia Institute of Technology)

  • Robert Herbert

    (George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology)

  • Young C. Jang

    (School of Biological Sciences, Georgia Institute of Technology
    Wallace H. Coulter Department of Biomedical Engineering, Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology)

  • Yong-Ho Choa

    (Hanyang University)

  • Woon-Hong Yeo

    (George W. Woodruff School of Mechanical Engineering, Institute for Electronics and Nanotechnology, Georgia Institute of Technology
    Wallace H. Coulter Department of Biomedical Engineering, Parker H. Petit Institute for Bioengineering and Biosciences, Georgia Institute of Technology
    Neural Engineering Center, Flexible and Wearable Electronics Advanced Research, Institute for Materials, Institute for Robotics and Intelligent Machines, Georgia Institute of Technology)

Abstract

Recent advances in nanomaterials and nano-microfabrication have enabled the development of flexible wearable electronics. However, existing manufacturing methods still rely on a multi-step, error-prone complex process that requires a costly cleanroom facility. Here, we report a new class of additive nanomanufacturing of functional materials that enables a wireless, multilayered, seamlessly interconnected, and flexible hybrid electronic system. All-printed electronics, incorporating machine learning, offers multi-class and versatile human-machine interfaces. One of the key technological advancements is the use of a functionalized conductive graphene with enhanced biocompatibility, anti-oxidation, and solderability, which allows a wireless flexible circuit. The high-aspect ratio graphene offers gel-free, high-fidelity recording of muscle activities. The performance of the printed electronics is demonstrated by using real-time control of external systems via electromyograms. Anatomical study with deep learning-embedded electrophysiology mapping allows for an optimal selection of three channels to capture all finger motions with an accuracy of about 99% for seven classes.

Suggested Citation

  • Young-Tae Kwon & Yun-Soung Kim & Shinjae Kwon & Musa Mahmood & Hyo-Ryoung Lim & Si-Woo Park & Sung-Oong Kang & Jeongmoon J. Choi & Robert Herbert & Young C. Jang & Yong-Ho Choa & Woon-Hong Yeo, 2020. "All-printed nanomembrane wireless bioelectronics using a biocompatible solderable graphene for multimodal human-machine interfaces," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-17288-0
    DOI: 10.1038/s41467-020-17288-0
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    Cited by:

    1. Taemin Kim & Yejee Shin & Kyowon Kang & Kiho Kim & Gwanho Kim & Yunsu Byeon & Hwayeon Kim & Yuyan Gao & Jeong Ryong Lee & Geonhui Son & Taeseong Kim & Yohan Jun & Jihyun Kim & Jinyoung Lee & Seyun Um , 2022. "Ultrathin crystalline-silicon-based strain gauges with deep learning algorithms for silent speech interfaces," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Yuzhou Shao & Lusong Wei & Xinyue Wu & Chengmei Jiang & Yao Yao & Bo Peng & Han Chen & Jiangtao Huangfu & Yibin Ying & Chuanfang John Zhang & Jianfeng Ping, 2022. "Room-temperature high-precision printing of flexible wireless electronics based on MXene inks," Nature Communications, Nature, vol. 13(1), pages 1-8, December.

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