Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Oct 17;11(42):eadx4518.
doi: 10.1126/sciadv.adx4518. Epub 2025 Oct 15.

A body-scale textile-based electromyogram monitoring system with coaxially shielded conductive yarns

Sunghoon Lee  1   2   3 , Kanta Takano  3 , Wakako Yukita  3 , Yusaku Tagawa  3 , Lulu Sun  1 , Shuxu Wang  2 , Joo Sung Kim  1 , Tomoyuki Yokota  3   4 , Takao Someya  1   2   3
Affiliations

A body-scale textile-based electromyogram monitoring system with coaxially shielded conductive yarns

Sunghoon Lee et al. Sci Adv. .

Abstract

A crucial aim of wearable electronics is to acquire biological signals from the body with high precision. However, obtaining high-accuracy electromyogram (EMG) signals from a large area surrounded by noise sources remains challenging. In this study, we present a body-scale textile-based wireless electromyogram monitoring system with coaxially shielded conductive yarns that can reduce the influence of surrounding noise. The wiring yarns comprise three stretchable components: a conductive signal yarn, polyurethane insulating layer, and shielding conductor. The introduction of the shielding conductor suppresses noise contamination. The noise level remains below 0.1 millivolts, despite the wiring being directly pressed at nominal contact pressures exceeding 30 kilopascals. The muscle activity at various shoulder joint angles is successfully recorded when another person directly touches the arm and wiring for support. Furthermore, EMG monitoring of the lower body is performed during dynamic activities such as countermovement jumps, jogging, and running.

PubMed Disclaimer

Figures

Fig. 1.
Fig. 1.. Textile-based EMG monitoring system with coaxially shielded conductive yarn.
(A) Fabricated lower-body textile-based EMG monitoring system with coaxially shielded conductive yarn connecting wireless EMG module and electrode. Scale bar, 5 cm. (B) Cross-sectional optical image of coaxially shielded conductive yarn comprising three stretchable components: a conductive yarn as the signal wire, polyurethane as the insulator, and a shielding conductor. Scale bar, 200 μm. SEM, scanning electron microscopy.
Fig. 2.
Fig. 2.. Properties of stretchable coaxial yarn.
(A) Optical images of stretchable coaxial yarn for wiring. Scale bars, 1 cm (top), 500 μm (bottom, right), and 100 μm (bottom, left). (B) Force required to stretch coaxial yarn. (C) Relative resistance change in shielding conductor while stretching. (D and E) Noise due to physical contact with the wiring with and without the shielding conductor (N = 5).
Fig. 3.
Fig. 3.. EMG signals during a ROM for the shoulder.
Photographs (A) and EMG signals (B) through active or passive ROM. Scale bar, 10 cm.
Fig. 4.
Fig. 4.. EMG signals during dynamic activities.
(A and B) Photographs during countermovement jumping motions (A) and corresponding EMG signals acquired from the lower legs (B). (C) EMG signals acquired during walking and running.
See this image and copyright information in PMC

References

    1. Kim D., Lu N., Ma R., Kim Y., Kim R.-H., Wang S., Wu J., Won S. M., Tao H., Islam A., Yu K. J., Kim T., Chowdhury R., Ying M., Xu L., Li M., Chung H.-J., Keum H., McCormick M., Liu P., Zhang Y.-W., Omenetto F. G., Huang Y., Coleman T., Rogers J. A., Epidermal electronics. Science 333, 838–843 (2011). - PubMed
    1. Yamada T., Hayamizu Y., Yamamoto Y., Yomogida Y., Izadi-Najafabadi A., Futaba D. N., Hata K., A stretchable carbon nanotube strain sensor for human-motion detection. Nat. Nanotechnol. 6, 296–301 (2011). - PubMed
    1. Quer G., Radin J. M., Gadaleta M., Baca-Motes K., Ariniello L., Ramos E., Kheterpal V., Topol E. J., Steinhubl S. R., Wearable sensor data and self-reported symptoms for COVID-19 detection. Nat. Med. 27, 73–77 (2021). - PubMed
    1. Luo Y., Abidian M. R., Ahn J.-H., Akinwande D., Andrews A. M., Antonietti M., Bao Z., Berggren M., Berkey C. A., Bettinger C. J., Chen J., Chen P., Cheng W., Cheng X., Choi S.-J., Chortos A., Dagdeviren C., Dauskardt R. H., Di C., Dickey M. D., Duan X., Facchetti A., Fan Z., Fang Y., Feng J., Feng X., Gao H., Gao W., Gong X., Guo C. F., Guo X., Hartel M. C., He Z., Ho J. S., Hu Y., Huang Q., Huang Y., Huo F., Hussain M. M., Javey A., Jeong U., Jiang C., Jiang X., Kang J., Karnaushenko D., Khademhosseini A., Kim D.-H., Kim I.-D., Kireev D., Kong L., Lee C., Lee N.-E., Lee P. S., Lee T.-W., Li F., Li J., Liang C., Lim C. T., Lin Y., Lipomi D. J., Liu J., Liu K., Liu N., Liu R., Liu Y., Liu Y., Liu Z., Liu Z., Loh X. J., Lu N., Lv Z., Magdassi S., Malliaras G. G., Matsuhisa N., Nathan A., Niu S., Pan J., Pang C., Pei Q., Peng H., Qi D., Ren H., Rogers J. A., Rowe A., Schmidt O. G., Sekitani T., Seo D.-G., Shen G., Sheng X., Shi Q., Someya T., Song Y., Stavrinidou E., Su M., Sun X., Takei K., Tao X.-M., Tee B. C. K., Thean A. V.-Y., Trung T. Q., Wan C., Wang H., Wang J., Wang M., Wang S., Wang T., Wang Z. L., Weiss P. S., Wen H., Xu S., Xu T., Yan H., Yan X., Yang H., Yang L., Yang S., Yin L., Yu C., Yu G., Yu J., Yu S.-H., Yu X., Zamburg E., Zhang H., Zhang X., Zhang X., Zhang X., Zhang Y., Zhang Y., Zhao S., Zhao X., Zheng Y., Zheng Y.-Q., Zheng Z., Zhou T., Zhu B., Zhu M., Zhu R., Zhu Y., Zhu Y., Zou G., Chen X., Technology roadmap for flexible sensors. ACS Nano 17, 5211–5295 (2023). - PMC - PubMed
    1. De Luca C. J., Gilmore L. D., Kuznetsov M., Roy S. H., Filtering the surface EMG signal: Movement artifact and baseline noise contamination. J. Biomech. 43, 1573–1579 (2010). - PubMed

LinkOut - more resources