Evidence map›Paper›PMID 39840391›Full record

ArticleNanophotonics (Berlin, Germany)2025

Gesture-controlled reconfigurable metasurface system based on surface electromyography for real-time electromagnetic wave manipulation.

Junzai Chen, Weiran Li, Kailuo Gong, Xiaojie Lu, Mei Song Tong, Xiaoyi Wang, Guo-Min Yang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nanophotonics (Berlin, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Junzai ChenCollege of Electronic and Information Engineering, Tongji University, Shanghai 200092, China.ORCID https://orcid.org/0009-0004-0262-4404
Weiran LiKey Laboratory for Information Science of Electromagnetic Waves, School of Information Science and Technology, Fudan University, Shanghai 200433, China.
Kailuo GongCollege of Electronic and Information Engineering, Tongji University, Shanghai 200092, China.
Xiaojie LuCollege of Electronic and Information Engineering, Tongji University, Shanghai 200092, China.
Mei Song TongCollege of Electronic and Information Engineering, Tongji University, Shanghai 200092, China.
Xiaoyi WangCollege of Electronic and Information Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China.ORCID https://orcid.org/0000-0001-5842-3442
Guo-Min YangKey Laboratory for Information Science of Electromagnetic Waves, School of Information Science and Technology, Fudan University, Shanghai 200433, China.ORCID https://orcid.org/0000-0003-0698-9633

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gesture recognition plays a significant role in human-machine interaction (HMI) system. This paper proposes a gesture-controlled reconfigurable metasurface system based on surface electromyography (sEMG) for real-time beam deflection and polarization conversion. By recognizing the sEMG signals of user gestures through a pre-trained convolutional neural network (CNN) model, the system dynamically modulates the metasurface, enabling precise control of the deflection direction and polarization state of electromagnetic waves. Experimental results demonstrate that the proposed system achieves high-precision electromagnetic wave manipulation, in response to different gestures. This system has significant potential applications in intelligent device control, virtual reality systems, and wireless communication technology, and is expected to contribute to the advancement and innovation of HMI technology by integration of more advanced metasurfaces and sEMG processing technologies.

Indexed as

convolutional neural networkgesture recognitionmetasurfacesurface electromyography

Identifiers

PMID39840391
PMCPMC11744455

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.