Factors Influencing Accuracy of Biometrical Personal Identification Based on Cardiograms

Abstract

Factors influencing the efficiency of biometrical personal identification based on cardiograms are studied. We compare the efficiency of cardiogram identification for healthy respondents and for respondents with various dysfunctions in the cardiovascular system. We study how sample size and time of cardiogram recording influence the effectiveness of recognition. Different methods of pattern recognition used in machine learning are compared. We also examine how different methods for cardiogram recording influence recognition accuracy.