ECG-BASED AUTHENTICATION: Bayesian vs. Nearest Neighbour Classifiers
Fred, A. L. N.
ECG-BASED AUTHENTICATION: Bayesian vs. Nearest Neighbour Classifiers, Proc International Conf. on Bio-inspired Systems and Signal Processing - Biosignals - INSTICC, Porto, Portugal, Vol. -, pp. - - -, January, 2009.
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This paper presents an approach for human authentication based on electrocardiogram (ECG) waveforms. ECG data was collected from 24 individuals during the realization of cognitive tests, where subjects held a surface mount triode placed on the V2 pre cordial derivation. Authentication is based on MAP, One-Class and 1-NN classifiers. Results show that ECG-based authentication may be a feasible tool for biometric systems. The One-Class classifier with class normalization has presented enhanced performance, with an equal error rate of 3.5%.