Evidence map›Paper›PMID 39660568›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Meso Hybridized Silk Fibroin Watchband for Wearable Biopotential Sensing and AI Gesture Signaling.

Xiao Wang, Changsheng Lu, Zerong Jiang, Guangwei Shao, Jingzhe Cao, Xiang Yang Liu

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, 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

6 authors.

Xiao WangState Key Laboratory of Marine Environmental Science (MEL), College of Ocean and Earth Sciences, Xiamen University, Xiamen, Fujian, 361102, P. R. China.
Changsheng LuState Key Laboratory of Marine Environmental Science (MEL), College of Ocean and Earth Sciences, Xiamen University, Xiamen, Fujian, 361102, P. R. China.
Zerong JiangState Key Laboratory of Marine Environmental Science (MEL), College of Ocean and Earth Sciences, Xiamen University, Xiamen, Fujian, 361102, P. R. China.
Guangwei ShaoEngineering Research Center of Technical Textiles, Ministry of Education, College of Textiles, Donghua University, Shanghai, 201620, P. R. China.
Jingzhe CaoCollege of Textile and Garment, Shaoxing University, Shaoxing, Zhejiang, 312000, P. R. China.
Xiang Yang LiuState Key Laboratory of Marine Environmental Science (MEL), College of Ocean and Earth Sciences, Xiamen University, Xiamen, Fujian, 361102, P. R. China.ORCID https://orcid.org/0000-0002-5592-6885

Funding

Fundamental Research Funds for the Central Universities 2232024D-09National Natural Science Foundation of China 12074322Postdoctoral Fellowship Program of China Postdoctoral Science Foundation GZC20231401
6 · The paper itself

Abstract

Human biopotential signals, such as electrocardiography, are closely linked to health and chronic conditions. Electromyography, corresponds to muscle actions and is pertinent to human-machine interactions. Here, we present a type of smart and flexible watchband that includes a mini flexible electrode array based on Mo-Au filament mesh, combined with mesoscopic hybridized silk fibroin films. As the layer in contact with the skin, waterborne polyurethane and SF create a highly flexible and permeable meso-hybridized SF/WPU layer, ensuring skin-friendliness and comfortable wearing. The flexible FM electrodes are created by integrating Mo-Au FM into 2D-interconnected networks. Molybdenum filaments provide high rigidity and are coated with Aurum to enhance conductivity. The use of Mo-Au FMs in warp-knitted patterns results in high SNR (43.22 dB), high sensitivity (44.43 mV/kg), and significant motion noise reduction due to the pattern's elastic deformability and skin-gripping properties. Leveraging these unique technologies, these smart watchbands excel in prolonged sensing operation, grasping force detection, and gesture recognition. Through smart raining via deep learning, we achieved an unparalleled recognition rate (96% across 20 volunteers of different genders) among other EMG sensing devices. These results have significant implications for human-machine interaction, including applications in underwater robot control, drone operation, and autonomous vehicle control.

Indexed as

FibroinsGesturesWearable Electronic DevicesElectromyographyHumansFibroinsflexible AI watchbandmeso dry electrodeMo‐Au filament networksilk fibroin

Identifiers

PMID39660568
PMCPMC11792041

What OpenQuestion holds

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LicenceCC BY
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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.