Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification
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Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification. / Jekova, Irena; Krasteva, Vessela; Leber, Remo; Schmid, Ramun; Twerenbold, Raphael; Müller, Christian; Reichlin, Tobias; Abächerli, Roger.
In: J ELECTROCARDIOL, Vol. 49, No. 6, 07.09.2016, p. 784-789.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification
AU - Jekova, Irena
AU - Krasteva, Vessela
AU - Leber, Remo
AU - Schmid, Ramun
AU - Twerenbold, Raphael
AU - Müller, Christian
AU - Reichlin, Tobias
AU - Abächerli, Roger
N1 - Copyright © 2016 Elsevier Inc. All rights reserved.
PY - 2016/9/7
Y1 - 2016/9/7
N2 - BACKGROUND: Electrocardiogram (ECG) biometrics is an advanced technology, not yet covered by guidelines on criteria, features and leads for maximal authentication accuracy.OBJECTIVE: This study aims to define the minimal set of morphological metrics in 12-lead ECG by optimization towards high reliability and security, and validation in a person verification model across a large population.METHODS: A standard 12-lead resting ECG database from 574 non-cardiac patients with two remote recordings (>1year apart) was used. A commercial ECG analysis module (Schiller AG) measured 202 morphological features, including lead-specific amplitudes, durations, ST-metrics, and axes. Coefficient of variation (CV, intersubject variability) and percent-mean-absolute-difference (PMAD, intrasubject reproducibility) defined the optimization (PMAD/CV→min) and restriction (CV<30%) criteria for selection of the most stable and distinctive features. Linear discriminant analysis (LDA) validated the non-redundant feature set for person verification.RESULTS AND CONCLUSIONS: Maximal LDA verification sensitivity (85.3%) and specificity (86.4%) were validated for 11 optimal features: R-amplitude (I,II,V1,V2,V3,V5), S-amplitude (V1,V2), Tnegative-amplitude (aVR), and R-duration (aVF,V1).
AB - BACKGROUND: Electrocardiogram (ECG) biometrics is an advanced technology, not yet covered by guidelines on criteria, features and leads for maximal authentication accuracy.OBJECTIVE: This study aims to define the minimal set of morphological metrics in 12-lead ECG by optimization towards high reliability and security, and validation in a person verification model across a large population.METHODS: A standard 12-lead resting ECG database from 574 non-cardiac patients with two remote recordings (>1year apart) was used. A commercial ECG analysis module (Schiller AG) measured 202 morphological features, including lead-specific amplitudes, durations, ST-metrics, and axes. Coefficient of variation (CV, intersubject variability) and percent-mean-absolute-difference (PMAD, intrasubject reproducibility) defined the optimization (PMAD/CV→min) and restriction (CV<30%) criteria for selection of the most stable and distinctive features. Linear discriminant analysis (LDA) validated the non-redundant feature set for person verification.RESULTS AND CONCLUSIONS: Maximal LDA verification sensitivity (85.3%) and specificity (86.4%) were validated for 11 optimal features: R-amplitude (I,II,V1,V2,V3,V5), S-amplitude (V1,V2), Tnegative-amplitude (aVR), and R-duration (aVF,V1).
KW - Discriminant Analysis
KW - Electrocardiography/methods
KW - Europe
KW - Heart Rate/physiology
KW - Heart Rate Determination/methods
KW - Humans
KW - Reproducibility of Results
KW - Sensitivity and Specificity
U2 - 10.1016/j.jelectrocard.2016.07.021
DO - 10.1016/j.jelectrocard.2016.07.021
M3 - SCORING: Journal article
C2 - 27597390
VL - 49
SP - 784
EP - 789
JO - J ELECTROCARDIOL
JF - J ELECTROCARDIOL
SN - 0022-0736
IS - 6
ER -
