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...

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Main Authors: 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
Other Authors: School of Materials Science and Engineering
Format: Article
Language:English
Published: 2021
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Online Access:https://hdl.handle.net/10356/147436
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1474362023-07-14T15:47:32Z 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 School of Materials Science and Engineering Innovative Centre for Flexible Devices Engineering::Materials Bioelectronics Electronic Devices 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. Agency for Science, Technology and Research (A*STAR) National Research Foundation (NRF) Published version The project was supported by the Agency for Science, Technology and Research (A*STAR) under its AME Programmatic Funding Scheme (A18A1b0045), the National Research Foundation (NRF), Prime Minister’s office, Singapore, under its NRF Investigatorship (NRF-NRFI2017-07), and Singapore Ministry of Education Tier 2 (MOE2017- T2-2-107). N.M. was supported by Japan Society for the Promotion of Science Overseas Research Fellowships. 2021-04-07T02:04:14Z 2021-04-07T02:04:14Z 2020 Journal Article Cai, P., Wan, C., Pan, L., Matsuhisa, N., He, K., Cui, Z., Zhang, W., Li, C., Wang, J., Yu, J., Wang, M., Jiang, Y., Chen, G. & Chen, X. (2020). Locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures. Nature Communications, 11(1), 2183-. https://dx.doi.org/10.1038/s41467-020-15990-7 2041-1723 0000-0002-2665-5932 0000-0002-3210-6673 0000-0001-7437-0125 0000-0002-5978-2778 0000-0003-1937-1760 0000-0002-4389-4214 0000-0003-1223-4536 0000-0003-1167-9808 0000-0002-8985-1180 0000-0001-5628-1727 0000-0002-6135-000X 0000-0002-3312-1664 https://hdl.handle.net/10356/147436 10.1038/s41467-020-15990-7 32366821 2-s2.0-85084238091 1 11 2183 en Nature communications © 2020 The Author(s). 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/. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Materials
Bioelectronics
Electronic Devices
spellingShingle Engineering::Materials
Bioelectronics
Electronic Devices
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
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.
author2 School of Materials Science and Engineering
author_facet School of Materials Science and Engineering
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
format Article
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_sort Cai, Pingqiang
title 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_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_sort locally coupled electromechanical interfaces based on cytoadhesion-inspired hybrids to identify muscular excitation-contraction signatures
publishDate 2021
url https://hdl.handle.net/10356/147436
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