ECG modelling using wavelet networks: application to biometrics
by Samer Chantaf, Amine Nait-Ali, Patrick Karasinski, Mohamad Khalil
International Journal of Biometrics (IJBM), Vol. 2, No. 3, 2010

Abstract: This paper deals with human identification using normal ECGs. Precisely, we would like to highlight how one can achieve human identification by considering only the most significant parameters extracted from a model. In this work, parameters are extracted by modelling the ECG using wavelet networks. The radial basis neural network method is then used to classify these parameters. Thus, a useful analysis is performed to evaluate the robustness of the identification. For each recording condition, the proposed technique has been evaluated on a set of ECG signals corresponding to normal subjects. Consequently, very encouraging results have been obtained.

Online publication date: Tue, 01-Jun-2010

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