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Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures
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 electromechan...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198512/ https://www.ncbi.nlm.nih.gov/pubmed/32366821 http://dx.doi.org/10.1038/s41467-020-15990-7 |
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author | Cai, Pingqiang Wan, Changjin Pan, Liang Matsuhisa, Naoji He, Ke Cui, Zequn Zhang, Wei Li, Chengcheng Wang, Jianwu Yu, Jing Wang, Ming Jiang, Ying Chen, Geng Chen, Xiaodong |
author_facet | Cai, Pingqiang Wan, Changjin Pan, Liang Matsuhisa, Naoji He, Ke Cui, Zequn Zhang, Wei Li, Chengcheng Wang, Jianwu Yu, Jing Wang, Ming Jiang, Ying Chen, Geng Chen, Xiaodong |
author_sort | Cai, Pingqiang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7198512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-71985122020-05-06 Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures Cai, Pingqiang Wan, Changjin Pan, Liang Matsuhisa, Naoji He, Ke Cui, Zequn Zhang, Wei Li, Chengcheng Wang, Jianwu Yu, Jing Wang, Ming Jiang, Ying Chen, Geng Chen, Xiaodong Nat Commun Article 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. Nature Publishing Group UK 2020-05-04 /pmc/articles/PMC7198512/ /pubmed/32366821 http://dx.doi.org/10.1038/s41467-020-15990-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Cai, Pingqiang Wan, Changjin Pan, Liang Matsuhisa, Naoji He, Ke Cui, Zequn Zhang, Wei Li, Chengcheng Wang, Jianwu Yu, Jing Wang, Ming Jiang, Ying Chen, Geng Chen, Xiaodong Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures |
title | Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures |
title_full | Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures |
title_fullStr | Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures |
title_full_unstemmed | Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures |
title_short | Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures |
title_sort | locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198512/ https://www.ncbi.nlm.nih.gov/pubmed/32366821 http://dx.doi.org/10.1038/s41467-020-15990-7 |
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