Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
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
_version_ 1783529001078226944
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
work_keys_str_mv AT caipingqiang locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT wanchangjin locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT panliang locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT matsuhisanaoji locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT heke locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT cuizequn locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT zhangwei locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT lichengcheng locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT wangjianwu locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT yujing locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT wangming locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT jiangying locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT chengeng locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures
AT chenxiaodong locallycoupledelectromechanicalinterfacesbasedoncytoadhesioninspiredhybridstoidentifymuscularexcitationcontractionsignatures