Evidence map›Paper›PMID 33579699›Full record

ArticleScience advances2021

Biomimetic and flexible piezoelectric mobile acoustic sensors with multiresonant ultrathin structures for machine learning biometrics.

Hee Seung Wang, Seong Kwang Hong, Jae Hyun Han, Young Hoon Jung, Hyun Kyu Jeong, Tae Hong Im, Chang Kyu Jeong, Bo-Yeon Lee, Gwangsu Kim, Chang D Yoo and 1 more

Abstract read
In one paragraph

Article in Science advances, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Capacitive piezotronics.Nature communications · 2026
    Article
  6. Ultrasensitive Diamond Cantilever-Based Optical Microphone.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Emerging Wearable Acoustic Sensing Technologies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  15. Article
  16. Bio-Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  17. Article
  18. Article
  19. Article
  20. 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.

Hee Seung WangDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.ORCID 0000-0001-9236-4466
Seong Kwang HongDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Jae Hyun HanDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Young Hoon JungDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Hyun Kyu JeongSchool of Computing, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Tae Hong ImDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
Chang Kyu JeongDivision of Advanced Materials Engineering, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju, Jeonbuk 54896, Republic of Korea.ORCID 0000-0001-5843-7609
Bo-Yeon LeeDepartment of Nature-Inspired Nano-convergence System, Korea Institute of Machinery and Materials (KIMM), 156 Gajeongbuk-Ro, Yuseong-gu, Daejeon 34103, Republic of Korea.ORCID 0000-0002-2150-1803
Gwangsu KimDepartment of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.ORCID 0000-0001-8357-1025
Chang D YooDepartment of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.ORCID 0000-0002-0756-7179
Keon Jae LeeDepartment of Materials Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea. keonlee@kaist.ac.kr.ORCID 0000-0001-7500-3079

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Flexible resonant acoustic sensors have attracted substantial attention as an essential component for intuitive human-machine interaction (HMI) in the future voice user interface (VUI). Several researches have been reported by mimicking the basilar membrane but still have dimensional drawback due to limitation of controlling a multifrequency band and broadening resonant spectrum for full-cover phonetic frequencies. Here, highly sensitive piezoelectric mobile acoustic sensor (PMAS) is demonstrated by exploiting an ultrathin membrane for biomimetic frequency band control. Simulation results prove that resonant bandwidth of a piezoelectric film can be broadened by adopting a lead-zirconate-titanate (PZT) membrane on the ultrathin polymer to cover the entire voice spectrum. Machine learning-based biometric authentication is demonstrated by the integrated acoustic sensor module with an algorithm processor and customized Android app. Last, exceptional error rate reduction in speaker identification is achieved by a PMAS module with a small amount of training data, compared to a conventional microelectromechanical system microphone.

Identifiers

PMID33579699
PMCPMC7880591

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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.