Feasibility of single-arm single-lead ECG biometrics

This work analyses the feasibility of electrocardiogram (ECG) biometrics using signals from a novel single arm single-lead acquisition methodology. These new signals are used and analysed in a biometric recognition system in verification mode for validation of a person's identity enrolled in a system database. The algorithm used for recognition in the proposed system is the Autocorrelation/Linear Discriminant Analysis (AC/LDA), which is combined with preprocessing stages tuned to the characteristics for ECG from the single arm. The signal is collected from 23 subjects in three scenarios and performance of the proposed scheme is evaluated. Considerably low Equal Error Rate of 4.34% is obtained using the described method, establishing the utility of these signals as viable candidates for ECG Biometrics.