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

MATEC Web of Conferences. 2017;125:02004 DOI 10.1051/matecconf/201712502004

 

Journal Homepage

Journal Title: MATEC Web of Conferences

ISSN: 2261-236X (Online)

Publisher: EDP Sciences

LCC Subject Category: Technology: Engineering (General). Civil engineering (General)

Country of publisher: France

Language of fulltext: French, English

Full-text formats available: PDF

 

AUTHORS

Matveev Mikhail (Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences)
Christov Ivaylo (Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences)
Krasteva Vessela (Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences)
Bortolan Giovanni (Institute of Neuroscience, IN-CNR)
Simov Dimitar (Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences)
Mudrov Nikolay (Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences)
Jekova Irena (Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences)

EDITORIAL INFORMATION

Editorial review

Editorial Board

Instructions for authors

Time From Submission to Publication: 6 weeks

 

Abstract | Full Text

This study investigates the potential of a set of ECG morphological features for person verification/identification. The measurements are done over 145 pairs of ECG recordings from healthy subjects, acquired 5 years apart (T1, T2 = T1+5 years). Time, amplitude, area and slope descriptors of the QRS-T pattern are analysed in 4 ECG leads, forming quasi-orthogonal lead system (II&III, V1, V5). The correspondence between feature values in T1 and T2 is verified via factor analysis by principal components extraction method; correlation analysis applied over the measurements in T1 and T2; synthesis of regression equations for prediction of features’ values in T2 based on T1 measurements; and cluster analysis for assessment of the correspondence between measured and predicted feature values. Thus, 11 amplitude descriptors of the QRS complex are highlighted as stable, i.e. keeping their strong correlation (≥0.7) within a certain factor, weak correlation (<0.3) with the features from the remaining factors and presenting high correlation in the two measurement periods that is a sign for their person verification/identification potential. The observed coincidence between feature values measured in T2 and predicted via the designed regression models (r=0.93) suggests about the confidence of person identification via the proposed morphological features.