IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-15990-7.html
   My bibliography  Save this article

Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures

Author

Listed:
  • Pingqiang Cai

    (Nanyang Technological University)

  • Changjin Wan

    (Nanyang Technological University)

  • Liang Pan

    (Nanyang Technological University)

  • Naoji Matsuhisa

    (Nanyang Technological University)

  • Ke He

    (Nanyang Technological University)

  • Zequn Cui

    (Nanyang Technological University)

  • Wei Zhang

    (Nanyang Technological University)

  • Chengcheng Li

    (Nanyang Technological University)

  • Jianwu Wang

    (Nanyang Technological University)

  • Jing Yu

    (Nanyang Technological University)

  • Ming Wang

    (Nanyang Technological University)

  • Ying Jiang

    (Nanyang Technological University)

  • Geng Chen

    (Nanyang Technological University)

  • Xiaodong Chen

    (Nanyang Technological University)

Abstract

Coupling myoelectric and mechanical signals during voluntary muscle contraction is paramount in human–machine interactions. Spatiotemporal differences in the two signals intrinsically arise from the muscular excitation–contraction process; however, current methods fail to deliver local electromechanical coupling of the process. Here we present the locally coupled electromechanical interface based on a quadra-layered ionotronic hybrid (named as CoupOn) that mimics the transmembrane cytoadhesion architecture. CoupOn simultaneously monitors mechanical strains with a gauge factor of ~34 and surface electromyogram with a signal-to-noise ratio of 32.2 dB. The resolved excitation–contraction signatures of forearm flexor muscles can recognize flexions of different fingers, hand grips of varying strength, and nervous and metabolic muscle fatigue. The orthogonal correlation of hand grip strength with speed is further exploited to manipulate robotic hands for recapitulating corresponding gesture dynamics. It can be envisioned that such locally coupled electromechanical interfaces would endow cyber–human interactions with unprecedented robustness and dexterity.

Suggested Citation

  • Pingqiang Cai & Changjin Wan & Liang Pan & Naoji Matsuhisa & Ke He & Zequn Cui & Wei Zhang & Chengcheng Li & Jianwu Wang & Jing Yu & Ming Wang & Ying Jiang & Geng Chen & Xiaodong Chen, 2020. "Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15990-7
    DOI: 10.1038/s41467-020-15990-7
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-15990-7
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-020-15990-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shun An & Hanrui Zhu & Chunzhi Guo & Benwei Fu & Chengyi Song & Peng Tao & Wen Shang & Tao Deng, 2022. "Noncontact human-machine interaction based on hand-responsive infrared structural color," Nature Communications, Nature, vol. 13(1), pages 1-9, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15990-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.