Development of an electrocardiogram based biometric identification system: a case study in the university

This paper focuses on the electrocardiogram (ECG) based biometric identification system in the university scenario as an alternative to the traditional methods being used nowadays. There are a lot of researches and studies about ECG based biometric system where some of them showed positive result. However, ECG based biometric system in the university scenario is under-researched. Therefore, this issue will be the main focus of our study. A total of five subjects were used for experimentation purposes. A bandpass filter is used to remove unwanted portion of the signal. Unique features are extracted from these filtered ECG signals. Later, Multilayer Perceptron and Naïve Bayes are used to classify the subjects using the discriminant features. Based on the experimentation results, classification accuracies of 90% and 80 % were achieved which suggest the capability of our proposed system to identify individuals. The result provides an alternative mechanism to detect a person besides using the traditional methods