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Symmetry
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Symmetry Applied in Biometrics Technology
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Special Issue "Symmetry Applied in Biometrics Technology"

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: 30 November 2023 | Viewed by 3267

Special Issue Editor

Prof. Dr. Jules-Raymond Tapamo

E-Mail Website
Guest Editor
Professor of Computer Science and Engineering, University of KwaZulu-Natal, Durban, South Africa
Interests: image processing; computer vision; machine learning; biometrics; data science

Special Issue Information

Dear Colleagues,

Advancements in sensor technology and computational power have created opportunites to build systems that mimic some human abilities. Biometric technology has immensely benefited from these developments. There have been several applications in areas, such as border control, banking, access control, etc., that use biometric modalities, such as the iris, face, fingerprint, palm print, ear, etc. The symmetrical nature of many biometric features has been exploited in some existing works to improve the accuracy of biometric systems. This gives research directions for using inner information of the ears  in recognition systems. This Special Issue focuses on the application of symmetry-based biometric solutions. It encourages researchers to submit state-of-the-art theoretical and/or application-based findings, with the use of symmetry to create new biometric-based systems. as well as  models or/and improve existing ones. You are welcome to submit original research or review articles.

Prof. Dr. Jules-Raymond Tapamo
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biometrics
  • identification
  • symmetry
  • pattern recognition
  • soft biometrics
  • safety
  • security

Published Papers (1 paper)

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Research

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Article
Peak Detection and HRV Feature Evaluation on ECG and PPG Signals
by
Filipa Esgalhado
,
Arnaldo Batista
,
Valentina Vassilenko
,
Sara Russo
and
Manuel Ortigueira
Symmetry 2022, 14(6), 1139; https://doi.org/10.3390/sym14061139 - 01 Jun 2022
Cited by 8 | Viewed by 2868
Abstract
Heart Rate Variability (HRV) evaluates the autonomic nervous system regulation and can be used as a monitoring tool in conditions such as cardiovascular diseases, neuropathies and sleep staging. It can be extracted from the electrocardiogram (ECG) and the photoplethysmogram (PPG) signals. Typically, the [...] Read more.
Heart Rate Variability (HRV) evaluates the autonomic nervous system regulation and can be used as a monitoring tool in conditions such as cardiovascular diseases, neuropathies and sleep staging. It can be extracted from the electrocardiogram (ECG) and the photoplethysmogram (PPG) signals. Typically, the HRV is obtained from the ECG processing. Being the PPG sensor widely used in clinical setups for physiological parameters monitoring such as blood oxygenation and ventilatory rate, the question arises regarding the PPG adequacy for HRV extraction. There is not a consensus regarding the PPG being able to replace the ECG in the HRV estimation. This work aims to be a contribution to this research area by comparing the HRV estimation obtained from simultaneously acquired ECG and PPG signals from forty subjects. A peak detection method is herein introduced based on the Hilbert transform: Hilbert Double Envelope Method (HDEM). Two other peak detector methods were also evaluated: Pan-Tompkins and Wavelet-based. HRV parameters for time, frequency and the non-linear domain were calculated for each algorithm and the Pearson correlation, T-test and RMSE were evaluated. The HDEM algorithm showed the best overall results with a sensitivity of 99.07% and 99.45% for the ECG and the PPG signals, respectively. For this algorithm, a high correlation and no significant differences were found between HRV features and the gold standard, for the ECG and PPG signals. The results show that the PPG is a suitable alternative to the ECG for HRV feature extraction. Full article
(This article belongs to the Special Issue Symmetry Applied in Biometrics Technology)
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