Evidence map›Paper›PMID 34451105›Full record

ArticleSensors (Basel, Switzerland)2021

Transcending Conventional Biometry Frontiers: Diffusive Dynamics PPG Biometry.

Javier de Pedro-Carracedo, David Fuentes-Jimenez, Ana María Ugena, Ana Pilar Gonzalez-Marcos

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  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

4 authors.

Javier de Pedro-CarracedoDepartamento de Tecnología Fotónica y Bioingeniería, ETSI Telecomunicación, Universidad Politécnica de Madrid (UPM), E-28040 Madrid, Spain.ORCID 0000-0002-2844-1858
David Fuentes-JimenezDepartamento de Electrónica, Universidad de Alcalá (UAH), Escuela Politécnica Superior, Alcalá de Henares (Madrid), E-28871 Alcalá de Henares, Spain.ORCID 0000-0001-6424-4782
Ana María UgenaDepartamento de Matemática Aplicada a las Tecnologías de la Información, ETSI Telecomunicación, Universidad Politécnica de Madrid (UPM), E-28040 Madrid, Spain.ORCID 0000-0001-7596-6756
Ana Pilar Gonzalez-MarcosDepartamento de Tecnología Fotónica y Bioingeniería, ETSI Telecomunicación, Universidad Politécnica de Madrid (UPM), E-28040 Madrid, Spain.ORCID 0000-0002-0757-2445

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents the first photoplethysmographic (PPG) signal dynamic-based biometric authentication system with a Siamese convolutional neural network (CNN). Our method extracts the PPG signal's biometric characteristics from its diffusive dynamics, characterized by geometric patterns in the (p,q)-planes specific to the 0-1 test. PPG signal diffusive dynamics are strongly dependent on the vascular bed's biostructure, unique to each individual. The dynamic characteristics of the PPG signal are more stable over time than its morphological features, particularly in the presence of psychosomatic conditions. Besides its robustness, our biometric method is anti-spoofing, given the complex nature of the blood network. Our proposal trains using a national research study database with 40 real-world PPG signals measured with commercial equipment. Biometric system results for input data, raw and preprocessed, are studied and compared with eight primary biometric methods related to PPG, achieving the best equal error rate (ERR) and processing times with a single attempt, among all of them.

Indexed as

Biometric IdentificationBiometryDatabases, FactualDiffusionNeural Networks, Computer0–1 testbiometric systemCNN architecturepattern analysisPPG signal dynamic

Identifiers

PMID34451105
PMCPMC8402390

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.