Exploratory Study of the Effects of Cardiac Murmurs on Electrocardiographic-Signal-Based Biometric Systems

  • M. A. BecerraEmail author
  • C. Duque-Mejía
  • C. Zapata-Hernández
  • D. H. Peluffo-Ordóñez
  • L. Serna-Guarín
  • Edilson Delgado-Trejos
  • E. J. Revelo-Fuelagán
  • X. P. Blanco Valencia
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11314)


The process of distinguishing among human beings through the inspection of acquired data from physical or behavioral traits is known as biometric identification. Mostly, fingerprint- and iris-based biometric techniques are used. Nowadays, since such techniques are highly susceptible to be counterfeited, new biometric alternatives are explored mainly based on physiological signals and behavioral traits -which are useful not only for biometric identification purposes, but may also play a role as a vital signal indicator. In this connection, the electrocardiographic (ECG) signals have shown to be a suitable approach. Nonetheless, their informative components (morphology, rhythm, polarization, and among others) can be affected by the presence of a cardiac pathology. Even more, some other cardiac diseases cannot directly be detected by the ECG signal inspection but still have an effect on their waveform, that is the case of cardiac murmurs. Therefore, for biometric purposes, such signals should be analyzed submitted to the effects of pathologies. This paper presents a exploratory study aimed at assessing the influence of the presence of a pathology when analyzing ECG signals for implementing a biometric system. For experiments, a data base holding 20 healthy subjects and 20 pathological subjects (diagnosed with different types of cardiac murmurs) are considered. The proposed signal analysis consists of preprocessing, characterization (using wavelet features), feature selection and classification (five classifiers as well as a mixture of them are tested). As a result, through the performed comparison of the classification rates when testing pathological and normal ECG signals, the cardiac murmurs’ undesired effect on the identification mechanism performance is clearly unveiled.


Biometric identification Cardiac murmur Electrocardiographic signal Signal processing 



The authors acknowledge to the research project “Desarrollo de una metodología de visualización interactiva y eficaz de información en Big Data” supported by Agreement No. 180 November 1st, 2016 by VIPRI from Universidad de Nariño. As well, authors thank the valuable support given by the SDAS Research Group (


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • M. A. Becerra
    • 1
    • 2
    Email author
  • C. Duque-Mejía
    • 1
  • C. Zapata-Hernández
    • 1
  • D. H. Peluffo-Ordóñez
    • 3
  • L. Serna-Guarín
    • 4
  • Edilson Delgado-Trejos
    • 4
  • E. J. Revelo-Fuelagán
    • 5
  • X. P. Blanco Valencia
    • 3
  1. 1.Institución Universitaria Pascual BravoMedellínColombia
  2. 2.Universidad de MedellínMedellínColombia
  3. 3.SDAS Research GroupYachay TechUrcuquíEcuador
  4. 4.Instituto Tecnológico MetropolitanoMedellínColombia
  5. 5.Universidad de NariñoPastoColombia

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