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ECG Biometric Analysis Using Walsh–Hadamard Transform

  • Ranjeet Srivastva
  • Yogendra Narain Singh
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 38)

Abstract

The electrocardiogram (ECG) signal expresses unique cardiac features among individuals. This paper proposes a novel method to human identification using ECG. The proposed method utilizes a band-pass filter for quality check and autocorrelation (AC) for feature extraction. Furthermore, the Walsh–Hadamard transform (WHT) is used for feature transformation. To get cost- and time-efficient classification performance, the dimensionality of feature vector is reduced using linear discriminant analysis (LDA). Experimental results show the best identification rate of 95 and 97% over MIT-BIH arrhythmia database and QT database, respectively.

Keywords

Human identification Electrocardiogram Walsh–Hadamard transform Discriminant analysis 

Notes

Acknowledgements

The authors would like to thank the anonymous reviewers and the editor for their feedback and useful suggestions.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Information TechnologyBabu Banarasi Das Northern India Institute of TechnologyLucknowIndia
  2. 2.Department of Computer Science and EngineeringInstitute of Engineering and TechnologyLucknowIndia

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