The use of electrocardiogram as biometric has raised attention in the last decade and a wide variety of ECG features were explored to verify the feasibility of such a signal. In this work the authors aim to describe a simple template based approach to the electrocardiographic biometric identification using the morphology of individual's heartbeat. The developed algorithm was tested on different recordings made available in the Physionet public database Fantasia: two different sets of heartbeats were extracted from individual recordings one was used for the template building while the second for the tests. The performances of the algorithm are encouraging with a true acceptance rate of 99.4%, however, the procedure needs to be tested on different recordings of the same individual, or during the course of a whole day or physical activity.
Individual identification using electrocardiogram morphology / Fratini, Antonio; Sansone, Mario; Bifulco, Paolo; Romano, Maria; Pepino, Alessandro; Cesarelli, Mario; D'Addio, Giovanni. - (2013), pp. 107-110. (Intervento presentato al convegno IEEE International Symposium on Medical Measurements and Applications, MeMeA 2013 tenutosi a Gatineau, QC, Canada nel 4-5 March 2013) [10.1109/MeMeA.2013.6549716].
Individual identification using electrocardiogram morphology
FRATINI, Antonio;SANSONE, MARIO;BIFULCO, PAOLO;ROMANO, MARIA;PEPINO, ALESSANDRO;CESARELLI, MARIO;D'ADDIO, Giovanni
2013
Abstract
The use of electrocardiogram as biometric has raised attention in the last decade and a wide variety of ECG features were explored to verify the feasibility of such a signal. In this work the authors aim to describe a simple template based approach to the electrocardiographic biometric identification using the morphology of individual's heartbeat. The developed algorithm was tested on different recordings made available in the Physionet public database Fantasia: two different sets of heartbeats were extracted from individual recordings one was used for the template building while the second for the tests. The performances of the algorithm are encouraging with a true acceptance rate of 99.4%, however, the procedure needs to be tested on different recordings of the same individual, or during the course of a whole day or physical activity.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.