Evidence map›Paper›PMID 40333989›Full record

ArticleScience advances2025

Piezoelectric nanofiber-based intelligent hearing system.

Jinke Chang, Thomas Maltby, Amirbahador Moineddini, Daqian Shi, Lei Wu, Jishizhan Chen, Jianshu Yu, Jeffrey Hung, Giuseppe Viola, Antonio Vilches and 1 more

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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. 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

11 authors.

Jinke ChangUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.ORCID 0000-0002-8335-1337
Thomas MaltbyUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.
Amirbahador MoineddiniUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.ORCID 0000-0002-7234-8749
Daqian ShiThe UCL Institute of Health Informatics, University College London, 222 Euston Rd., London NW1 2DA, UK.ORCID 0000-0003-2183-1957
Lei WuUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.ORCID 0000-0002-0268-6304
Jishizhan ChenUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.ORCID 0000-0002-1784-319X
Jianshu YuUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.ORCID 0000-0003-3862-5156
Jeffrey HungUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.
Giuseppe ViolaUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.ORCID 0000-0001-9320-2872
Antonio VilchesUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.
Wenhui SongUCL Centre for Biomaterials in Surgical Reconstruction and Regeneration, Department of Surgical Biotechnology, Division of Surgery & Interventional Science, University College London, London NW3 2PF, UK.ORCID 0000-0001-8406-472X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hearing loss, affecting individuals of all ages, can impair education, social function, and quality of life. Current treatments, such as hearing aids and implants, aim to mitigate these effects but often fall short in addressing the critical issue of accurately pinpointing sound sources. We report an intelligent hearing system inspired by the human auditory system: asymmetric well-aligned piezoelectric nanofibers combined with neural networks to mimic natural auditory processes. Piezoelectric nanofibers with spirally varying lengths and directions transmit and convert acoustic sound into mechanoelectrical signals, mimicking the complex cochlear dynamics. These signals are then encoded by digital neural networks, enabling accurate sound direction recognition. This intelligent hearing system surpasses human directional hearing, accurately recognizing sound directions horizontally and vertically. The advancement represents a substantial stride toward next-generation artificial hearing, harmonizing transduction and perception with a nature-inspired design. It promises for applications in hearing aids, wearable devices, and implants, offering enhanced auditory experiences for those with hearing impairments.

Indexed as

HearingHearing AidsNanofibersHearing LossHumansNeural Networks, Computer

Identifiers

PMID40333989
PMCPMC12057686

What OpenQuestion holds

Textmetadata
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.