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Achieving stability of ECG biometric features through binaural brain entrainment

Palaniappan, Ramaswamy, Andrews, S. (2014) Achieving stability of ECG biometric features through binaural brain entrainment. In: 2014 International Conference on Contemporary Computing and Informatics (IC3I). . pp. 1208-1210. IEEE E-ISBN 978-1-4799-6629-5. (doi:10.1109/IC3I.2014.7019629) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL
http://dx.doi.org/10.1109/IC3I.2014.7019629

Abstract

In this paper, it is shown that classification of features from heart (electrocardiogram, ECG) signals for biometric purposes (i.e. for individual identification) degrades over a period of time and a method based on binaural brain entrainment is proposed to minimise the variations in the heart signals over time to improve the classification performance. The results indicate that variability of the heart features is reduced by 15.57% using the proposed method and this results in improving the classification accuracy from 90.35% to 95.77% when tested with five subjects with ECG data recorded over a period of six months. This pilot study indicates that binaural brain entrainment can be used to improve the stability of ECG features over time thereby increasing its potential to be used in biometric applications. © 2014 IEEE.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/IC3I.2014.7019629
Additional information: Unmapped bibliographic data: C7 - 7019629 [EPrints field already has value set] LA - English [Field not mapped to EPrints] J2 - Proc. Int. Conf. Contemp. Comput. Informatics, ICI [Field not mapped to EPrints] AD - School of Computing, University of Kent, Chatham Maritime, United Kingdom [Field not mapped to EPrints] AD - Department of Information Technology, Mahendra Engineering College, Namakkal Dt, Tamil Nadu, India [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] A4 - Cycle Pure Agarbathies; et al.; HCL; Research Publishing, Singapore (RPS); Siemens; Zebra Technologies [Field not mapped to EPrints] C3 - Proceedings of 2014 International Conference on Contemporary Computing and Informatics, IC3I 2014 [Field not mapped to EPrints]
Uncontrolled keywords: binaural, biometric, brain entrainment, electrocardiogram, Biometrics, binaural, Biometric applications, Biometric features, Classification accuracy, Classification performance, Heart signal, Individual identification, Pilot studies, Electrocardiography
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
R Medicine > RC Internal medicine > RC667 Diseases of the circulatory (cardiovascular) system
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 06 Dec 2018 17:52 UTC
Last Modified: 30 May 2019 08:28 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70688 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
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