Evidence map›Paper›PMID 39301887›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Intelligent Song Recognition via a Hollow-Microstructure-Based, Ultrasensitive Artificial Eardrum.

Shaopeng Li, Jiangtao Tian, Ke Li, Kemeng Xu, Jiaqi Zhang, Tingting Chen, Yang Li, Hongbo Wang, Qiye Wu, Jinchun Xie and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

15 authors.

Shaopeng LiState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Jiangtao TianSchool of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
Ke LiState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Kemeng XuSchool of Electronics and Information, Xi'an Polytechnic University, Xi'an, 710048, China.
Jiaqi ZhangState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Tingting ChenState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Yang LiState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Hongbo WangState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Qiye WuState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Jinchun XieState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Yongjun MenState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Weiping LiuState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.
Xiaodan ZhangSchool of Electronics and Information, Xi'an Polytechnic University, Xi'an, 710048, China.
Wenhan CaoSchool of Information Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
Zhongjie HuangState Key Laboratory for Modification of Chemical Fibers and Polymer Materials, College of Materials Science and Engineering, Donghua University, Shanghai, 201620, China.ORCID 0000-0001-6739-1577

Funding

Graduate Student Innovation Foundation of Xi'an Polytechnic University chx2024015National Natural Science Foundation of China 62205204National Natural Science Foundation of China 62375172Natural Science Foundation of Shanghai 23ZR1400800Shanghai Pujiang Program 21PJ1400100
6 · The paper itself

Abstract

Artificial ears with intelligence, which can sensitively detect sound-a variant of pressure-and generate consciousness and logical decision-making abilities, hold great promise to transform life. However, despite the emerging flexible sensors for sound detection, most success is limited to very simple phonemes, such as a couple of letters or words, probably due to the lack of device sensitivity and capability. Herein, the construction of ultrasensitive artificial eardrums enabling intelligent song recognition is reported. This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 × 10

Indexed as

Artificial IntelligenceEquipment DesignHumansMachine LearningMusicSoundTympanic Membraneacoustic sensorartificial eardrumhollow microstructurepiezoresistive sensorsong recognition

Identifiers

PMID39301887
PMCPMC11558140

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.