Evidence map›Paper›PMID 36140085›Full record

ArticleBiosensors2022

Multichannel Acoustic Spectroscopy of the Human Body for Inviolable Biometric Authentication.

Hyung Wook Noh, Chang-Geun Ahn, Seung-Hoon Chae, Yunseo Ku, Joo Yong Sim

Abstract read
In one paragraph

Article in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Hyung Wook NohBio-Medical IT Convergence Research Department, Electronics and Telecommunications Research Institute, Daejeon 34129, Korea.ORCID 0000-0001-6237-0021
Chang-Geun AhnBio-Medical IT Convergence Research Department, Electronics and Telecommunications Research Institute, Daejeon 34129, Korea.
Seung-Hoon ChaeBio-Medical IT Convergence Research Department, Electronics and Telecommunications Research Institute, Daejeon 34129, Korea.ORCID 0000-0002-4115-1345
Yunseo KuDepartment of Biomedical Engineering, College of Medicine, Chungnam National University, Daejeon 35015, Korea.ORCID 0000-0003-2737-4427
Joo Yong SimDepartment of Mechanical Systems Engineering, Sookmyung Women's University, Seoul 04310, Korea.ORCID 0000-0003-3779-7589

Funding

Institute for Information and Communications Technology Promotion 2017-0-00409National Research Foundation of Korea 2019R1F1A1062312National Research Foundation of Korea 2019R1F1A1063037National Research Foundation of Korea 2022R1C1C1008508Sookmyung Women's University 1-2203-2022
6 · The paper itself

Abstract

Specific features of the human body, such as fingerprint, iris, and face, are extensively used in biometric authentication. Conversely, the internal structure and material features of the body have not been explored extensively in biometrics. Bioacoustics technology is suitable for extracting information about the internal structure and biological and material characteristics of the human body. Herein, we report a biometric authentication method that enables multichannel bioacoustic signal acquisition with a systematic approach to study the effects of selectively distilled frequency features, increasing the number of sensing channels with respect to multiple fingers. The accuracy of identity recognition according to the number of sensing channels and the number of selectively chosen frequency features was evaluated using exhaustive combination searches and forward-feature selection. The technique was applied to test the accuracy of machine learning classification using 5,232 datasets from 54 subjects. By optimizing the scanning frequency and sensing channels, our method achieved an accuracy of 99.62%, which is comparable to existing biometric methods. Overall, the proposed biometric method not only provides an unbreakable, inviolable biometric but also can be applied anywhere in the body and can substantially broaden the use of biometrics by enabling continuous identity recognition on various body parts for biometric identity authentication.

Indexed as

Biometric IdentificationHuman BodyAcousticsBiometryHumansSpectrum Analysisaccess controlacousticsanti-spoofingbiometricshuman–machine interactionsmultisensor systemsspectral analysis

Identifiers

PMID36140085
PMCPMC9496529

What OpenQuestion holds

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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.