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ECG Biometric Recognition

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Mathematics and Computing (ICMC 2018)

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

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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.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Institute of Engineering and Technology, Dr. A. P. J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India

    Anita Pal & Yogendra Narain Singh

Authors
  1. Anita Pal
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  2. Yogendra Narain Singh
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Correspondence to Anita Pal .

Editor information

Editors and Affiliations

  1. Department of Mathematical Sciences, Indian Institute of Technology BHU, Varanasi, Uttar Pradesh, India

    Debdas Ghosh

  2. Haldia Institute of Technology, Haldia, India

    Debasis Giri

  3. University of Central Florida, Orlando, Florida, USA

    Ram N. Mohapatra

  4. Istanbul Commerce University, Istanbul, Turkey

    Ekrem Savas

  5. Kyushu University, Fukuoka, Japan

    Kouichi Sakurai

  6. Indian Institute of Technology (BHU), Varanasi, India

    L. P. Singh

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Pal, A., Singh, Y.N. (2018). ECG Biometric Recognition. In: Ghosh, D., Giri, D., Mohapatra, R., Savas, E., Sakurai, K., Singh, L. (eds) Mathematics and Computing. ICMC 2018. Communications in Computer and Information Science, vol 834. Springer, Singapore. https://doi.org/10.1007/978-981-13-0023-3_7

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  • DOI: https://doi.org/10.1007/978-981-13-0023-3_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0022-6

  • Online ISBN: 978-981-13-0023-3

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