Skip to main content

Identifying individuals using ECG beats

Palaniappan, Ramaswamy, Krishnan, S.M. (2004) Identifying individuals using ECG beats. In: Proceedings of the 2004 International Conference on Signal Processing and Communications. . pp. 569-572. IEEE ISBN 0-7803-8674-4. (doi:10.1109/SPCOM.2004.1458524) (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/SPCOM.2004.1458524

Abstract

In this paper, we propose a technique to identify individuals using features extracted from QRS segment of electrocardiogram (ECG) signals. A total of 2000 samples from 10 subjects from the Arrhythmia Laboratory at Boston's Beth Israel Hospital (now the Beth Israel Deaconess Medical Center) database were used. These data are available as MIT-BH Normal Sinus Rhythm database and consist of 18 hour long-term recordings with 2 ECG signals. The commonly used features like R-R interval, R amplitude, QRS interval, QR amplitude and RS amplitude were used. In addition to these features, we propose the use of form factor of the QRS segment. Form factor has been used previously in electroencephalogram analysis and it is a measure of the complexity of the signal. These six features were then used by two neural network classifiers: Multilayer Perceptron - Backpropagation (MLP-BP) and Simplified Fuzzy ARTMAP (SFA). The data were split equally for MLP-BP and SFA training and testing. The results gave classification performance up to 97.6%. This indicates that ECG has the potential to be used as a biometric tool.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/SPCOM.2004.1458524
Additional information: Unmapped bibliographic data: LA - English [Field not mapped to EPrints] J2 - Int. Conf. Signal Proces. Commun. [Field not mapped to EPrints] AD - Biomedical Engineering Research Centre, Nanyang Technological University, Singapore, Singapore [Field not mapped to EPrints] DB - Scopus [Field not mapped to EPrints] M3 - Conference Paper [Field not mapped to EPrints] C3 - 2004 International Conference on Signal Processing and Communications, SPCOM [Field not mapped to EPrints]
Uncontrolled keywords: Computational complexity, Data acquisition, Database systems, Feature extraction, Fuzzy control, Signal processing, Electroencephalogram analysis, Simplified Fuzzy ARTMAP (SFA), Electrocardiography
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Data Science
Depositing User: Palaniappan Ramaswamy
Date Deposited: 15 Dec 2018 16:57 UTC
Last Modified: 30 May 2019 08:29 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70753 (The current URI for this page, for reference purposes)
Palaniappan, Ramaswamy: https://orcid.org/0000-0001-5296-8396
  • Depositors only (login required):