Evidence map›Paper›PMID 40832479›Full record

ArticleResearch (Washington, D.C.)2025

Fabric-Based Flexible Pressure Sensor Arrays with Ultra-Wide Pressure Range for Lower Limb Motion Capture System.

Xiaohua Wu, Yuxuan Liang, Longsheng Lu, Shu Yang, Zhanbo Liang, Feilong Liu, Xiaoyu Lu, Bowen Xiao, Yilin Zhong, Yingxi Xie

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. [Research progress on flexible wearable sensors for health monitoring].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025
    Review
  7. 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.

Xiaohua WuSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0000-0002-0977-0728
Yuxuan LiangSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0009-0002-3513-2735
Longsheng LuSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0000-0003-3879-4224
Shu YangSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0000-0001-9928-2762
Zhanbo LiangSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0009-0002-5679-4615
Feilong LiuSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0009-0000-4105-5188
Xiaoyu LuSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0009-0003-5421-7352
Bowen XiaoSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0009-0008-1262-3324
Yilin ZhongSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0009-0004-9408-7887
Yingxi XieSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510641, China.ORCID https://orcid.org/0000-0002-7961-3883

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The lower limb motion capture technology has garnered significant attention as a pivotal enabler in extended reality, sports science, film production, and medical rehabilitation. However, existing mature systems face critical challenges, including restricted operational environments, interference with natural activities, and cumbersome wearability. Here, a flexible insole pressure sensor array with an ultra-wide sensing range is developed using dip coating, laser cutting, and hot pressing, enabling lower limb motion capture. The developed fabric-based flexible pressure sensor exhibited an ultra-wide pressure range (3,770.9 kPa), high sensitivity (2.68 kPa

Identifiers

PMID40832479
PMCPMC12358749

What OpenQuestion holds

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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.