ECG Biometric Recognition

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 834)

Abstract

This paper presents a human recognition system using single lead electrocardiogram (ECG). The method corrects the ECG signal from noise as well as other artifacts to it and extracts major features from P-QRS-T waveforms. Finite Impulse Response (FIR) equiripple high pass filter is used for denoising ECG signal. Haar wavelet transform is used to detect the R peaks. By using this novel approach, different extensive information like heart rates, interval features, amplitude features, angle features area features are received among dominant fiducials of ECG waveform. The feasibility of ECG as a new biometric is tested on selected features that report the recognition accuracy to 97.12% on the data size of 100 recordings of PTB database. The results obtained from the proposed approach surpasses the other conventional methods for biometric applications.

Keywords

ECG Heartbeats Biometric recognition 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering, Institute of Engineering and TechnologyDr. A. P. J. Abdul Kalam Technical UniversityLucknowIndia

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