Title
ECG-based Authentication - Bayesian vs. Nearest Neighbour Classifiers
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%.
Year
Venue
Keywords
2009
BIOSIGNALS 2009: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING
Bayesian,Biometric authentication,ECG,MAP,One-Class,1-NN
Field
DocType
Citations 
Authentication,Nearest neighbour classifiers,Pattern recognition,Computer science,Artificial intelligence,Bayesian probability
Conference
3
PageRank 
References 
Authors
0.40
1
2
Name
Order
Citations
PageRank
Carla Oliveira1143.98
Ana L. N. Fred21317195.30