Evidence map›Paper›PMID 40073146›Full record

ArticleScience advances2025

A flexible pressure sensor array for self-powered identity authentication during typing.

Tongtong Zhang, Farid Manshaii, Chris R Bowen, Maoyi Zhang, Weiqi Qian, Chaosheng Hu, Yanan Bai, Zhijie Huang, Ya Yang, Jun Chen

Abstract read
In one paragraph

Article in Science advances, 2025. 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. Review
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  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Artificial Intelligence-Driven Soft Bioelectronics for Self-Powered Respiration Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  11. Article
  12. Review
  13. Article
  14. Article
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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.

Tongtong ZhangCAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID 0009-0009-6860-9123
Farid ManshaiiDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA.ORCID 0009-0007-4580-9259
Chris R BowenDepartment of Mechanical Engineering, University of Bath, Bath BA2 7AK, UK.ORCID 0000-0002-5880-9131
Maoyi ZhangCAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Weiqi QianCAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID 0000-0002-0217-1183
Chaosheng HuCAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID 0009-0000-6336-204X
Yanan BaiCAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID 0009-0000-3590-8623
Zhijie HuangCAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Ya YangCAS Center for Excellence in Nanoscience, Beijing Key Laboratory of Micro-Nano Energy and Sensor, Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID 0000-0003-0168-2974
Jun ChenDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA 90095, USA.ORCID 0000-0002-3439-0495

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The keyboard, a staple tool for information entry and human-machine interaction, faces demands for enhanced information security due to evolving internet technologies. This study introduces a self-powered flexible intelligent keyboard (SFIK) that harnesses the giant magnetoelastic effect to convert the mechanical pressure from key presses into electrical signals. The sensor boasts a wide sensing range (35 to 600 kPa) and a rapid response time (∼300 ms), allowing it to record and recognize individual keystroke dynamics. Integrated with machine learning, this keyboard enables identity authentication through both fixed- and dynamic-text inputs. It accurately authenticates fixed passwords of eight characters with a 95.3% success rate and dynamic text from 14 sets of double keys with 100% accuracy. Given its capabilities, the SFIK offers promising applications in artificial intelligence, network security, and access control for computers and networks.

Identifiers

PMID40073146
PMCPMC11900873

What OpenQuestion holds

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LicenceCC BY-NC
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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.