Intelligent Person Recognition System Based on ECG Signal

Abstract

Automated recognition based on ECG signal is now preferable to identify the person for security monitoring work. This approach is gradually replacing manual techniques that claimed to be outdated. However, it is challenging task to execute the automated system since it is in the infant stage. In this paper, an intelligent person recognition system based on ECG signal is proposed. Here, 79 recorded signals from 79 subjects are used. Three processes are i.e. pre-processing, feature extraction and classification is discussed. A combination of enhanced start and end point detection namely short time energy (STE) and short time average zero crossing rate (STAZCR) is employed in the pre-processing. Subsequently, an autocorrelation method is applied in feature extraction. Finally, support vector machine (SVM) is implemented to evaluate the performance of the system. The experimental demonstrate that 0.93% to 0.97% equal error rate (EER) is achieved when the training data is set to 35.