Finger ECG signal for user authentication: Usability and performance

Abstract

Over the past few years, the evaluation of Electrocardiographic (ECG) signals as a prospective biometric modality has revealed promising results. Given the vital and continuous nature of this information source, ECG signals offer several advantages to the field of biometrics; yet, several challenges currently prevent the ECG from being adopted as a biometric modality in operational settings. These arise partially due to ECG signal's clinical tradition and intrusiveness, but also from the lack of evidence on the permanence of the ECG templates over time. The problem of intrusiveness has been recently overcome with the "off-theperson" approach for capturing ECG signals. In this paper we provide an evaluation of the permanence of ECG signals collected at the fingers, with respect to the biometric authentication performance. Our experimental results on a small dataset suggest that further research is necessary to account for and understand sources of variability found in some subjects. Despite these limitations, "off-the-person" ECG appears to be a viable trait for multi-biometric or standalone biometrics, low user throughput, real-world scenarios.

Biometrics via Spatial P-QRS-T Loop Features: Effect of Different VCG Transformations

“…We do not find VCG superiority in comparison to ECG-based human verification studies, showing 85.6-90.9% for single leads [3,4], 87.2-94.6% for limb leads [5,7], 91.3% for chest leads [7], 86-96.3% for 12-lead ECG [6,7].…”

“…The electrocardiogram (ECG) has been investigated as an advanced signal for human biometrics, presenting vital signs. The human verification or identification solutions employ a single ECG lead [3,4], limb leads [5] or standard 12-lead ECG [6,7], based on temporal and amplitude ECG features [6], cross-correlation analysis [5,7], PQRST pattern matching [3,4].The spatial features of the cardiac vector represented by the vectorcardiogram (VCG) are expected to be useful for biometric applications, considering the inter-subject differences of the VCG loop orientation and shape, and its independence from the heart rate [8]. However, we could find a few studies based on VCG biometrics, all of them solving the human identification task, using:…”

ECG Signals for Biometric Applications - Are we there yet?

“…While Permanence deals with the question of temporal invariance of the templates, that is, intra-subject variability, Uniqueness pertains to the discernibility of the templates from different subjects, that is, intersubject variability. Studies on the permanence question can already be found in the literature, for instance in (Agrafioti et al, 2011;Silva et al, 2013c). In this paper, we present a preliminary study on the uniqueness question.…”

Check Your Biosignals Here: A new dataset for off-the-person ECG biometrics

“…Using 63 records, and the two temporal separated sessions from the long-term CYBHi dataset, Equal Error Rates (EER) of 11.5% and 12.4% were achieved, revealing that this is a challenging task. More recently in [11], we further evaluated the temporal stability of ECG signals collected at the fingers, reaching an EER of 9.10% using SVMs also for the CYBHi long-term dataset.…”

“…Nonetheless, this approach is highly intrusive for the subjects, thus limiting the potential industrial applications of ECG-based biometrics. More recently, researchers have been pivoting towards the off-the-person approaches [3,6,[10][11][12][13], in an effort to overcome the intrusiveness problems widely criticized in ECG biometrics. Recent work from our team has provided experimental evidence that the signals obtained through the off-the-person approach using dry electrodes, present virtually the same morphology as those obtained at the Lead I derivation of a standard 12-lead medical-grade ECG system [8,14].…”