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A Gaussian mixture models approach to human heart signal verification using different feature extraction algorithms

Citation

Wahid, R and Ghali, NI and Own, HS and Kim, T-H and Hassanien, AE, A Gaussian mixture models approach to human heart signal verification using different feature extraction algorithms, Computer Applications for Bio-technology, Multimedia and Ubiquitous City, FGIT 2012, 16-19 December 2012, Gangneug, South Korea, pp. 16-24. ISSN 1865-0929 (2012) [Refereed Conference Paper]

Copyright Statement

Copyright 2012 Springer-Verlag Berlin Heidelberg.

DOI: doi:10.1007/978-3-642-35521-9_3

Abstract

In this paper the possibility of using the human heart signal feature for human verification is investigated. The presented approach consists of two different robust feature extraction algorithms with a specified configuration in conjunction with Gaussian mixture modeling. The similarity of two samples is estimated by measuring the difference between their negative log-likelihood of the features. To evaluate the performance and the uniqueness of the presented approach tests using a high resolution auscultation digital stethoscope are done for nearly 80 heart sound samples. The experimental results obtained show that the accuracy offered by the employed Gaussian mixture modeling reach up to 100% for 7 samples using the first feature extraction algorithm and 6 samples using the second feature extraction algorithm and varies with average 85%.

Item Details

Item Type:Refereed Conference Paper
Keywords:feature extraction, Gaussian mixture models, heart sounds, human verification
Research Division:Mathematical Sciences
Research Group:Statistics
Research Field:Stochastic Analysis and Modelling
Objective Division:Health
Objective Group:Clinical Health (Organs, Diseases and Abnormal Conditions)
Objective Field:Cardiovascular System and Diseases
Author:Kim, T-H (Dr Tai Kim)
ID Code:118133
Year Published:2012
Deposited By:Computing and Information Systems
Deposited On:2017-07-05
Last Modified:2017-09-04
Downloads:0

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