Evidence map›Paper›PMID 37292515›Full record

ArticleResearch (Washington, D.C.)2023

A Deep Learning-Enabled Skin-Inspired Pressure Sensor for Complicated Recognition Tasks with Ultralong Life.

Yingxi Xie, Xiaohua Wu, Xiangbao Huang, Qinghua Liang, Shiping Deng, Zeji Wu, Yunpeng Yao, Longsheng Lu

Abstract read
In one paragraph

Article in Research (Washington, D.C.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
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  4. Review
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  9. Article
  10. AI-Driven Sensing Technology: Review.Sensors (Basel, Switzerland) · 2024
    Review
  11. Proximity Sensing Electronic Skin: Principles, Characteristics, and Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  12. Article
  13. Article
  14. Article
  15. 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

8 authors.

Yingxi XieSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China.
Xiaohua WuSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China.
Xiangbao HuangSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China.
Qinghua LiangSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China.
Shiping DengSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China.
Zeji WuSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China.
Yunpeng YaoSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China.
Longsheng LuSchool of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flexible full-textile pressure sensor is able to integrate with clothing directly, which has drawn extensive attention from scholars recently. But the realization of flexible full-textile pressure sensor with high sensitivity, wide detection range, and long working life remains challenge. Complex recognition tasks necessitate intricate sensor arrays that require extensive data processing and are susceptible to damage. The human skin is capable of interpreting tactile signals, such as sliding, by encoding pressure changes and performing complex perceptual tasks. Inspired by the skin, we have developed a simple dip-and-dry approach to fabricate a full-textile pressure sensor with signal transmission layers, protective layers, and sensing layers. The sensor achieves high sensitivity (2.16 kPa

Identifiers

PMID37292515
PMCPMC10246885

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.