Electrocardiogram authentication method robust to dynamic morphological conditions
- Author(s): Jeehoon Kim 1 ; Dongsuk Sung 2 ; MyungJun Koh 3 ; Jason Kim 4 ; Kwang Suk Park 1, 5
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View affiliations
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Affiliations:
1:
Interdisciplinary Program in Bioengineering , Seoul National University , Seoul , Republic of Korea ;
2: Electrical and Computer Engineering , Georgia Institute of Technology , Atlanta, GA , USA ;
3: Non-Destructive Testing , Dresden International University GmbH , Dresden , Germany ;
4: Korea Internet and Security Agency , Naju , Republic of Korea ;
5: Department of Biomedical Engineering , College of Medicine, Seoul National University , Seoul , Republic of Korea
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Affiliations:
1:
Interdisciplinary Program in Bioengineering , Seoul National University , Seoul , Republic of Korea ;
- Source:
Volume 8, Issue 6,
November
2019,
p.
401 – 410
DOI: 10.1049/iet-bmt.2018.5183 , Print ISSN 2047-4938, Online ISSN 2047-4946
This study proposes a human authentication framework based on electrocardiogram signals that are robust to dynamic cardiac morphological conditions. The proposed method incorporates a stationary wavelet transform, an infinite feature selection, and a linear discriminant analysis. Evaluation experiments were conducted under three modulated situations: temporal variation, postural variation, and heart rate variation when exercising. Compared with three state-of-the-art methods, the performance of the proposed method was shown to be better overall, with an equal error rate (EER) of 1.48% under time-varying situations, 1.74% under posture changes, and 5.47% after exercise. These results indicate that the proposed method achieves a highly increased performance compared with state-of-the-art techniques. Further evaluation of the identification performance of the proposed method on two public databases shows that it performs better than previously proposed methods.
Inspec keywords: statistical analysis; wavelet transforms; medical signal processing; electrocardiography; feature extraction; feature selection; cardiology
Other keywords: human authentication framework; infinite feature selection; equal error rate; time-varying situations; dynamic cardiac morphological conditions; exercising; heart rate variation; electrocardiogram signals; postural variation; stationary wavelet transform; posture changes; exercise; temporal variation; identification performance; evaluation experiments; linear discriminant analysis; electrocardiogram authentication method
Subjects: Integral transforms; Function theory, analysis; Biology and medical computing; Electrodiagnostics and other electrical measurement techniques; Probability theory, stochastic processes, and statistics; Signal processing and detection; Bioelectric signals; Other topics in statistics; Electrical activity in neurophysiological processes; Other topics in statistics; Integral transforms; Digital signal processing
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