title: Personal Verification/Identification via Analysis of the Peripheral ECG Leads: Influence of the Personal Health Status on the Accuracy.
abstract: Traditional means for identity validation (PIN codes, passwords), and physiological and behavioral biometric characteristics (fingerprint, iris, and speech) are susceptible to hacker attacks and/or falsification. This paper presents a method for person verification/identification based on correlation of present-to-previous limb ECG leads: I (r I), II (r II), calculated from them first principal ECG component (r PCA), linear and nonlinear combinations between r I, r II, and r PCA. For the verification task, the one-to-one scenario is applied and threshold values for r I, r II, and r PCA and their combinations are derived. The identification task supposes one-to-many scenario and the tested subject is identified according to the maximal correlation with a previously recorded ECG in a database. The population based ECG-ILSA database of 540 patients (147 healthy subjects, 175 patients with cardiac diseases, and 218 with hypertension) has been considered. In addition a common reference PTB dataset (14 healthy individuals) with short time interval between the two acquisitions has been taken into account. The results on ECG-ILSA database were satisfactory with healthy people, and there was not a significant decrease in nonhealthy patients, demonstrating the robustness of the proposed method. With PTB database, the method provides an identification accuracy of 92.9% and a verification sensitivity and specificity of 100% and 89.9%.
authors.affiliation: Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Street Bl 105, 1113 Sofia, Bulgaria.
authors.forename: Irena
authors.initials: I
authors.lastname: Jekova
authors.affiliation: Institute of Neuroscience (IN), CNR, 35127 Padova, Italy.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Bortolan
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D004562:Electrocardiography / Q000379:methods*; D005260:Female; D006304:Health Status; D006331:Heart Diseases / Q000175:diagnosis / Q000503:physiopathology*; D006339:Heart Rate; D006801:Humans; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D011996:Records; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity