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ECG Based Biometric by Superposition Matrix in Unrestricted Status

  • Gang Zheng
  • Xiaoxia Sun
  • Shengzhen Ji
  • Min Dai
  • Ying Sun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10996)

Abstract

The paper proposed an Electrocardiogram (ECG) feature extraction method for biometric. It relied on ECG superposition number matrix built by several single heartbeat ECG data. The target of the study was to find stable features of the ECG signal under unrestricted status for biometric. By matrix segmentation and similarity comparison, the stable feature distribution was gotten, and stable feature sets were also constructed. 13 volunteers’ ECG data collected by self-made ECG device in different status were gotten, the collecting period was lasting for half year; 28 healthy individuals’ ECG data under calm status were also collected; Besides that, 14 subjects’ ECG data in MIT-BIH were also involved in study. From the result of experiments, the average True Positive Rate (TPR) reached 83.21%, 83.93% and 80% on MIT data set, ECG data set in calm status and ECG data in different status respectively. It is also found that along with the increasing amount of ECG single heartbeat used to build superposition matrix, the stable features of one’s ECG were gradually revealed and this helped ECG based biometric effectively.

Keywords

ECG biometric Unrestricted status Identity authentication Superposition matrix 

Notes

Acknowledgment

The paper is supported by TianJin National Science Foundation 16JCYBJC15300 (2016.04-2019.03).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Gang Zheng
    • 1
  • Xiaoxia Sun
    • 1
  • Shengzhen Ji
    • 1
  • Min Dai
    • 1
  • Ying Sun
    • 1
  1. 1.TianJin Key Laboratory of Intelligence Computing and Novel Software TechnologyTianjin University of TechnologyTianjinPeople’s Republic of China

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