Heartrate-Dependent Heartwave Biometric Identification With Thresholding-Based GMM–HMM Methodology

Lim, Ching Leng Peter, Woo, Wai Lok, Dlay, Satnam and Gao, Bin (2018) Heartrate-Dependent Heartwave Biometric Identification With Thresholding-Based GMM–HMM Methodology. IEEE Transactions on Industrial Informatics, 15 (1). pp. 45-53. ISSN 1551-3203

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Abstract

This paper presents an adaptive heartrate-dependent heartwave-signal-based biometric identification. A reliable and continuous heartwave extraction method featuring the hybridized discrete waveform transform method with heartrate adaptive QT and PR intervals to perform comprehensive heartwave features extractions on more than 35 000 heartwave signal. The size of training data was determined and the hybridized Gaussian-mixture-model-hidden-Markov-model classification method was used in the classification. Dynamic thresholding criterial incorporating user-specific scores and heartrate were adopted. The identification process using dynamic thresholding criterial achieved a remarkable receiver operating characteristic of 0.89 in true positive rate and an equal error rate of 0.11.

Item Type:	Article
Uncontrolled Keywords:	Discrete wavelet transform, Gaussian mixture model (GMM), QT nomogram, electrocardiogram (ECG), heartwave, hidden Markov model (HMM)
Subjects:	H600 Electronic and Electrical Engineering
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	22 Mar 2019 16:40
Last Modified:	10 Oct 2019 20:34
URI:	http://nrl.northumbria.ac.uk/id/eprint/38504

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