Application of extension method and chaos theory in ECG identity recognition system
An ECG process based on Einthoven principle was developed for this study. A circuit and DAQ card were incorporated in a human machine interface using LabVIEW to detect the PQRSTpoints in ECG and display the processed ECG signals of the test subjects. The ECG data saved were plotted into dynamical map of chaotic dynamic error using a master-slave chaos system. Chaos eye was selected as the feature and an identity database was built using an element model. Personal identity was identified by categorizing with extension method. Finally, the design was tested on 35 subjects to yield 94.3% of positive identification rate. The results suggested that the identity identification method developed in this study features quick identification, high positive identification rate and good reliability.