Authors:
Carla Oliveira
1
and
Ana Fred
2
Affiliations:
1
Instituto de Telecomunicações, Portugal
;
2
Instituto Superior Técnico, Portugal
Keyword(s):
Bayesian, Biometric authentication, ECG, MAP, One-Class, 1-NN.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Biometrics
;
Biometrics and Pattern Recognition
;
Computer Vision, Visualization and Computer Graphics
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Multimedia
;
Multimedia Signal Processing
;
Pattern Recognition
;
Telecommunications
Abstract:
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%.