ECG based biometric authentication-a novel data modelling approach

Use of ECG for biometric authentication is a relatively new approach for in security and restricted access methodologies. Here an ECG based technique for biometric analysis is proposed for a group of 20 persons. The method is based on first accurate extraction of characteristic features from each ECG and then design of a classifier for authentication. The feature data set is dimensionally reduced before classification. Classification is based on a simple comparison of the signature matrix elements for stored and testing data. In this work it is shown that the classification accuracy greatly improves if the reduced data set is modelled by a quadratic polynomial based on least square.