Evidence map›Paper›PMID 41560400›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

3D-Printed Ion-Conductive Hydrogels with Tunable Mechanical-Electrical Properties for Multimodal Sign Language Recognition.

Quan Hu, Longya Xiao, Peiqi Zhang, Qiurui Zhang, Guangsen Liu, Xinglin Qin, Zhuhui Yin, Xian Li, Yuling Wang, Hongjie Jiang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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. Review
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

10 authors.

Quan HuShien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China.
Longya XiaoShien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China.
Peiqi ZhangShien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China.
Qiurui ZhangSchool of Mechatronic Engineering, Guangdong Polytechnic Normal University, Guangzhou, China.
Guangsen LiuShien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China.
Xinglin QinShien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China.
Zhuhui YinShien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China.
Xian LiDepartment of Rehabilitation Medicine, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Yuling WangDepartment of Rehabilitation Medicine, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
Hongjie JiangShien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China.ORCID https://orcid.org/0000-0002-6756-704X

Funding

National Natural Science Foundation of China 42177440
6 · The paper itself

Abstract

Sign language recognition technology holds significant importance for eliminating communication barriers faced by the hearing-impaired population. To address the limitations of current wearable sensors‒such as complex fabrication or materials incompatibility within an integrated system, this study designed a 3D printed ion-conductive hydrogel with tunable electromechanical performances for versatile wearable sensing. The hydrogel is primarily based on a polyampholyte network interpenetrated with a polyacrylamide (PAAM) framework and synergistically integrated with LiCl and a covalent organic framework (COF) to enhance its electromechanical performance. It exhibits low hysteresis (90.25% recovery ratio) with high elongation (550%) and large compressive strain tolerance (90%) for strain/pressure sensing, while its low modulus (0.09 MPa) and high conductivity (0.23 S m

Indexed as

HydrogelsPrinting, Three-DimensionalSign LanguageWearable Electronic DevicesElectric ConductivityElectromyographyHumansHydrogelsion‐conductive hydrogelslow hysteresismultimodal sensingsign language recognition

Identifiers

PMID41560400
PMCPMC13042474

What OpenQuestion holds

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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.