Title :
ECG personal identification in subspaces using radial basis neural networks
Author :
Boumbarov, Ognian ; Velchev, Yuliyan ; Sokolov, Strahil
Author_Institution :
Tech. Univ. of Sofia, Sofia, Bulgaria
Abstract :
In this paper an approach for personal biometric identification is presented based on extraction of ECG features and classification with RBFNN. We perform denoising and segmentation on the input signal, after which we realize dimensionality reduction and feature extraction based on PCA transform. The separability of the selected features is improved by applying LDA. The final stage of the proposed approach is classification and recognition of the extracted features with classifier score fusion.
Keywords :
biometrics (access control); electrocardiography; feature extraction; hidden Markov models; medical signal processing; principal component analysis; radial basis function networks; signal classification; signal denoising; transforms; ECG classification; ECG feature extraction; ECG personal biometric identification; HMM; LDA; PCA transform; RBFNN; classifier score fusion; dimensionality reduction; extracted feature recognition; hidden Markov model; linear discriminant analysis; radial basis neural network; signal denoising; signal segmentation; Autocorrelation; Biometrics; Discrete cosine transforms; Electrocardiography; Feature extraction; Humans; Linear discriminant analysis; Neural networks; Noise reduction; Principal component analysis; ECG personal identification; HMM; LDA; PCA; neural networks;
Conference_Titel :
Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2009. IDAACS 2009. IEEE International Workshop on
Conference_Location :
Rende
Print_ISBN :
978-1-4244-4901-9
Electronic_ISBN :
978-1-4244-4882-1
DOI :
10.1109/IDAACS.2009.5342942
