Evidence map›Paper›PMID 41614583›Full record

ReviewSmall methods2026

Wearable Sensors Fabricated by 3D-Printed Composite Hydrogel with 2D Fillers.

Yaxuan Li, Sheng Pei, Jun Wang, Chuhan Zhang, Beichao Shi, Zhengtang Luo

Abstract readReview
In one paragraph

Review in Small methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Yaxuan LiDepartment of Chemical and Biological Engineering, Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology, William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction, The Hong Kong University of Science and Technology, Kowloon, Hong Kong, P. R. China.ORCID https://orcid.org/0009-0007-6041-428X
Sheng PeiDepartment of Chemical and Biological Engineering, Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology, William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction, The Hong Kong University of Science and Technology, Kowloon, Hong Kong, P. R. China.
Jun WangDepartment of Chemical and Biological Engineering, Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology, William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction, The Hong Kong University of Science and Technology, Kowloon, Hong Kong, P. R. China.
Chuhan ZhangKey Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, School of Mechanical Engineering, Tianjin University, Tianjin, China.
Beichao ShiDepartment of Chemical and Biological Engineering, Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology, William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction, The Hong Kong University of Science and Technology, Kowloon, Hong Kong, P. R. China.
Zhengtang LuoDepartment of Chemical and Biological Engineering, Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology, William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction, The Hong Kong University of Science and Technology, Kowloon, Hong Kong, P. R. China.ORCID https://orcid.org/0000-0002-5134-9240

Funding

HK-RGC and the European Union (EU) Co-Funding Mechanism E-HKUST601/23Horizon 2022 Research and Innovation Program 101131106-LESIAInnovation and Technology Commission ITC-CNERC14SC01International Science and Technology Cooperation projects of Science and Technological Bureau of Guangzhou Huangpu District 2022GH05Research Grants Council of the Hong Kong Special Administrative Region, China F-HKUST602/23
6 · The paper itself

Abstract

Flexible sensors demonstrate exceptional adaptability across human-computer interaction, health monitoring, and robotic systems. However, sensing materials suffer from inadequate conformation capability and microstructural inaccuracies, resulting in function deficiencies. This review examines composite hydrogel formulations that incorporate conductive nanofillers, with particular emphasis on 2D nanomaterials, whose functional tunability enables precise regulation of electrical and interfacial properties. The strategic integration of microstructures further improves sensor sensitivity, durability, and environmental adaptability. We also examine implementation of flexible sensors based on 3D-printed hydrogel in emerging applications including pH monitoring, glucose detection, and food safety assessment. We suggest that future development prioritize elucidating sensing mechanisms, achieving multifunctional integration, advancing material engineering, and refining precision manufacturing. Particularly promising research directions include developing intelligent tactile feedback systems for humanoid robots and creating capsule robot-integrated platforms for gastrointestinal disease monitoring.

Indexed as

Biosensing TechniquesHydrogelsPrinting, Three-DimensionalWearable Electronic DevicesHumansNanostructuresHydrogels3D printingconductive materialflexible sensorhydrogelmicrostructure

Identifiers

PMID41614583
PMCPMC12929939

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.