Evidence map›Paper›PMID 41984945›Full record

ArticleScience advances2026

Drawn-on-skin electronic tattoo as a closed-loop sensing-stimulation system for the muscles.

Ya Huang, Zhenlin Chen, Jingkun Zhou, Huiling Jia, Lung Chow, Yu Zhou, Shengxin Jia, Binbin Zhang, Faheem Ershad, Shubham Patel and 12 more

Abstract read
In one paragraph

Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Ya HuangState Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai, China.ORCID 0000-0002-0965-8226
Zhenlin ChenDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0003-2100-1363
Jingkun ZhouDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0001-5394-4388
Huiling JiaDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.
Lung ChowDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0001-5670-1031
Yu ZhouCollege of Future Information Technology, Fudan University, Shanghai, China.ORCID 0000-0001-7233-4649
Shengxin JiaDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0002-6998-3872
Binbin ZhangDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0001-8796-2592
Faheem ErshadDepartment of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.ORCID 0000-0002-3353-9606
Shubham PatelMaterials Research Laboratory, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.ORCID 0000-0002-0046-9031
Chun Ki YiuDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0003-3841-5327
Yuyu GaoDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0002-2000-5410
Qiang ZhangDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0002-2707-0258
Xingcan HuangDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0003-4210-2470
Jian LiDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0002-9768-0932
Kuanming YaoDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0001-8744-8892
Guangyao ZhaoDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0002-5664-4898
Peining ChenState Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai, China.ORCID 0000-0003-0566-1660
Huisheng PengState Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, and Laboratory of Advanced Materials, Fudan University, Shanghai, China.ORCID 0000-0002-2142-2945
Dong SunDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0003-3945-4037
Cunjiang YuDepartment of Electrical and Computer Engineering, University of Illinois Urbana-Champaign, Urbana, IL 61801, USA.ORCID 0000-0002-0155-0368
Xinge YuDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, China.ORCID 0000-0003-0522-1171

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simultaneous electromyography (EMG) sensing and closed-loop electrical stimulation (ES) could enable interactive muscle training, motor rehabilitation, and kinesthetic feedback. However, current systems often suffer from nonconformal device/skin interfaces, poor wearability, and anatomical variability among users, limiting signal fidelity and stimulation precision. Here, we present a fully wireless, skin-integrated electronic tattoo platform that records high-quality EMG and delivers closed-loop ES through custom drawn-on-skin, conformal electrodes with strong adhesion and high spatial accuracy. The system supports closed-loop muscle interactions across body regions and even between individuals. Machine learning models classify EMG patterns from different hand gestures with >90% accuracy and adapt ES parameters to stimulate specific muscle groups. In a heavy object holding task, users reached the required grip behavior substantially faster than unassisted controls, indicating improved neuromuscular efficiency. This closed-loop framework not only supports personalized muscle control but also supports coordinated activation across multiple sites or users, unlocking possibilities in interactive motor training, remote rehabilitation, and virtual reality environments.

Indexed as

Electric StimulationElectromyographyMuscle, SkeletalTattooingHumansMachine LearningSkin

Identifiers

PMID41984945
PMCPMC13082325

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.