Abstract
ObjectiveThis study aims to validate the 12-lead electrocardiogram (ECG) as a biometric modality based on two straightforward binary QRS template matching characteristics. Different perspectives of the human verification problem are considered, regarding the optimal lead selection and stability over sample size, gender, age, heart rate (HR).MethodsA clinical 12-lead resting ECG database, including a population of 460 subjects with two-session recordings (>1 year apart) is used. Cost-effective strategies for extraction of personalized QRS patterns (100ms) and binary template matching estimate similarity in the time scale (matching time) and dissimilarity in the amplitude scale (mismatch area). The two-class person verification task, taking the decision to validate or to reject the subject identity is managed by linear discriminant analysis (LDA). Non-redundant LDA models for different lead configurations (I,II,III,aVF,aVL,aVF,V1-V6) are trained on the first half of 230 subjects by stepwise feature selection until maximization of the area under the receiver operating characteristic curve (ROC AUC). The operating point on the training ROC at equal error rate (EER) is tested on the independent dataset (second half of 230 subjects) to report unbiased validation of test-ROC AUC and true verification rate (TVR = 100-EER). The test results are further evaluated in groups by sample size, gender, age, HR.Results and discussionThe optimal QRS pattern projection for single-lead ECG biometric modality is found in the frontal plane sector (60°-0°) with best (Test-AUC/TVR) for lead II (0.941/86.8%) and slight accuracy drop for -aVR (-0.017/-1.4%), I (-0.01/-1.5%). Chest ECG leads have degrading accuracy from V1 (0.885/80.6%) to V6 (0.799/71.8%). The multi-lead ECG improves verification: 6-chest (0.97/90.9%), 6-limb (0.986/94.3%), 12-leads (0.995/97.5%). The QRS pattern matching model shows stable performance for verification of 10 to 230 individuals; insignificant degradation of TVR in women by (1.2–3.6%), adults ≥70 years (3.7%), younger <40 years (1.9%), HR<60bpm (1.2%), HR>90bpm (3.9%), no degradation for HR change (0 to >20bpm).
Highlights
Since the early 2000s, the electrocardiogram (ECG) has been suggested as a biometric modality for human identity recognition [1,2,3,4,5]
The optimal QRS pattern projection for single-lead ECG biometric modality is found in the frontal plane sector (60 ̊-0 ̊) with best (Test-AUC/TVR) for lead II (0.941/86.8%) and slight accuracy drop for -aVR (-0.017/-1.4%), I (-0.01/-1.5%)
The first part of results is focused on statistical evaluation of the introduced QRS pattern matching features, trying to answer the question: “Is there a statistical merit to use any of 12 ECG leads as a biometric modality, regarding high inter-subject differences and low intra-subject differences?”
Summary
Since the early 2000s, the electrocardiogram (ECG) has been suggested as a biometric modality for human identity recognition [1,2,3,4,5]. The multi-lead scenarios for biometric recognition are proposed for improving of the authentication accuracy. We find fewer studies for comparative investigation of the optimal single or multi-lead ECG combination schemes [1, 21,22,23,24,25,26]. It is important to achieve position invariant measurements by recording ECG signals from the three leads fixed to the extremities, according to the Einthoven’s triangular scheme, shown to be widely independent of the actual positioning of the electrodes [27]. Alternative leads from electrodes on the human chest, close to the heart source, are shown to be more informative for the discrimination between individuals [23], not confirmed in [21, 22], probably due to database differences
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