Assessment of the stability of morphological ECG features and their potential for person verification/identification

Mikhail Matveev; Ivaylo Christov; Vessela Krasteva; Giovanni Bortolan; Dimitar Simov; Nikolay Mudrov; Irena Jekova

doi:10.1051/matecconf/201712502004

All issues

Volume 125 (2017)

MATEC Web Conf., 125 (2017) 02004

References

Open Access

Issue		MATEC Web Conf. Volume 125, 2017 21^st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017)


Article Number		02004
Number of page(s)		4
Section		Systems
DOI		https://doi.org/10.1051/matecconf/201712502004
Published online		04 October 2017

L. Biel, O. Pettersson, L. Philipson, P. Wide, “ECG analysis: a new approach in human identification”, IEEE Trans. Instr. Meas., 50(3): 808–12, (2001) [CrossRef] [Google Scholar]
S. Israel, J. Irvine, A. Cheng, M. Wiederhold, B. Wiederhold, “ECG to identify individuals” Pattern Recognition, 38, 133–42 (2005) [CrossRef] [Google Scholar]
Y. Wang, F. Agrafioti, D. Hatzinakos, K. Plataniotis, “Analysis of human electrocardiogram for biometric recognition”, EURASIP Journal on Advances in Signal Processing, Article ID 148658 (2008) [Google Scholar]
K. Plataniotis, D. Hatzinakos, J. Lee, “ECG biometric recognition without fiducial detection”, Proc. on Biometrics Symposium BSYM’06, 19–21, (2006) [Google Scholar]
F. Agrafioti, D. Hatzinakos, “ECG biometric analysis in cardiac irregularity conditions”, Signal Image & Video Processing, 3, 329–43 (2009) [CrossRef] [Google Scholar]
F. Poree, A. Gallix, G. Carrault, “Biometric identification of individuals based on the ECG. Which conditions?”, Comp. in Cardiol., 38, 761–4, (2011) [Google Scholar]
I. Jekova. “Potential of the peripheral electrocardiogram for personal verification/ identification” Compt. Rend. de l’Acad. Bulg. des Sci., 68(4): 497–504, (2015) [Google Scholar]
I. Jekova, V. Krasteva, R. Leber, R. Schmid, R. Twerenbold, C. Müller, T. Reichlin, R. Abächerli, “Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification”, J. Electrocardiol., 49: 784–9, (2016) [CrossRef] [Google Scholar]
V. Krasteva, I. Jekova, R. Abächerli, “Analysis of QRS Patterns in 15-Lead ECG for Person Verification”, Annual J. Electronics, 9: 10–13, (2015) [Google Scholar]
I. Jekova, G. Bortolan, “Personal verification/ identification via analysis of the peripheral ECG leads. Influence of the personal health status on the accuracy”, Biomed. Research Int., 2015, Article ID 135676, (2015) [CrossRef] [Google Scholar]
I. Jekova, I. Christov, V. Krasteva, G. Bortolan, M. Matveev, “Assessment of the Potential of Morphological ECG Features for Person Identification”, Comput. in Cardiol., 42: 921–4, (2015). [Google Scholar]
S. Maggi, M. Zuchetto, F. Grigoletto, M. Baldereschi, L. Candelise, E. Scarpini, et al., “The Italian Longitudinal Study on Aging (ILSA): design and methods”, Aging Clin. Exp. Res., 6: 464–73 (1994) [CrossRef] [Google Scholar]
G. Bortolan, M. Bressan, F. Golferini, ILSA Study Group, “QT dispersion in the elderly. The ILSA study”, Aging Clin. Exp. Res., 16(5): 342–8, (2004) [CrossRef] [Google Scholar]
G. Bortolan, M. Bressan, F. Golferini, “Serial analysis in the ECG-ILSA database: study of longitudinal modifications”, Comput. In Cardiol., 26: 667–70, (1999) [Google Scholar]
M. Matveev, L. Tomov, I. Tomov, I.. Daskalov, “Lead Selection for ECG Screening”, Adv. Cardiol., 19:148–9, (1977) [Google Scholar]
I. Christov, “Real time electrocardiogram QRS detection using combined adaptive threshold”, Biomed. Eng. Online, 3(28), (2004) [CrossRef] [Google Scholar]
I. Christov, I. Jekova, G. Bortolan, “Premature ventricular contraction classification by the K-th nearest neighbours rule”, Physiol Meas., 26: 123–30, (2005) [CrossRef] [Google Scholar]
I. Christov, I. Simova, “Q-onset and T-end delineation: Assessment of the performance of an automated method with the use of a reference database”, Physiol Meas, 28: 213–21, (2007) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.

[1] L. Biel, O. Pettersson, L. Philipson, P. Wide, “ECG analysis: a new approach in human identification”, IEEE Trans. Instr. Meas., 50(3): 808–12, (2001) [CrossRef] [Google Scholar]

[2] S. Israel, J. Irvine, A. Cheng, M. Wiederhold, B. Wiederhold, “ECG to identify individuals” Pattern Recognition, 38, 133–42 (2005) [CrossRef] [Google Scholar]

[3] Y. Wang, F. Agrafioti, D. Hatzinakos, K. Plataniotis, “Analysis of human electrocardiogram for biometric recognition”, EURASIP Journal on Advances in Signal Processing, Article ID 148658 (2008) [Google Scholar]

[4] K. Plataniotis, D. Hatzinakos, J. Lee, “ECG biometric recognition without fiducial detection”, Proc. on Biometrics Symposium BSYM’06, 19–21, (2006) [Google Scholar]

[5] F. Agrafioti, D. Hatzinakos, “ECG biometric analysis in cardiac irregularity conditions”, Signal Image & Video Processing, 3, 329–43 (2009) [CrossRef] [Google Scholar]

[6] F. Poree, A. Gallix, G. Carrault, “Biometric identification of individuals based on the ECG. Which conditions?”, Comp. in Cardiol., 38, 761–4, (2011) [Google Scholar]

[7] I. Jekova. “Potential of the peripheral electrocardiogram for personal verification/ identification” Compt. Rend. de l’Acad. Bulg. des Sci., 68(4): 497–504, (2015) [Google Scholar]

[8] I. Jekova, V. Krasteva, R. Leber, R. Schmid, R. Twerenbold, C. Müller, T. Reichlin, R. Abächerli, “Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification”, J. Electrocardiol., 49: 784–9, (2016) [CrossRef] [Google Scholar]

[9] V. Krasteva, I. Jekova, R. Abächerli, “Analysis of QRS Patterns in 15-Lead ECG for Person Verification”, Annual J. Electronics, 9: 10–13, (2015) [Google Scholar]

[10] I. Jekova, G. Bortolan, “Personal verification/ identification via analysis of the peripheral ECG leads. Influence of the personal health status on the accuracy”, Biomed. Research Int., 2015, Article ID 135676, (2015) [CrossRef] [Google Scholar]

[11] I. Jekova, I. Christov, V. Krasteva, G. Bortolan, M. Matveev, “Assessment of the Potential of Morphological ECG Features for Person Identification”, Comput. in Cardiol., 42: 921–4, (2015). [Google Scholar]

[12] S. Maggi, M. Zuchetto, F. Grigoletto, M. Baldereschi, L. Candelise, E. Scarpini, et al., “The Italian Longitudinal Study on Aging (ILSA): design and methods”, Aging Clin. Exp. Res., 6: 464–73 (1994) [CrossRef] [Google Scholar]

[13] G. Bortolan, M. Bressan, F. Golferini, ILSA Study Group, “QT dispersion in the elderly. The ILSA study”, Aging Clin. Exp. Res., 16(5): 342–8, (2004) [CrossRef] [Google Scholar]

[14] G. Bortolan, M. Bressan, F. Golferini, “Serial analysis in the ECG-ILSA database: study of longitudinal modifications”, Comput. In Cardiol., 26: 667–70, (1999) [Google Scholar]

[15] M. Matveev, L. Tomov, I. Tomov, I.. Daskalov, “Lead Selection for ECG Screening”, Adv. Cardiol., 19:148–9, (1977) [Google Scholar]

[16] I. Christov, “Real time electrocardiogram QRS detection using combined adaptive threshold”, Biomed. Eng. Online, 3(28), (2004) [CrossRef] [Google Scholar]

[17] I. Christov, I. Jekova, G. Bortolan, “Premature ventricular contraction classification by the K-th nearest neighbours rule”, Physiol Meas., 26: 123–30, (2005) [CrossRef] [Google Scholar]

[18] I. Christov, I. Simova, “Q-onset and T-end delineation: Assessment of the performance of an automated method with the use of a reference database”, Physiol Meas, 28: 213–21, (2007) [CrossRef] [Google Scholar]