IDEAS home Printed from https://ideas.repec.org/a/hin/jnljam/904905.html
   My bibliography  Save this article

Personal Identification Based on Vectorcardiogram Derived from Limb Leads Electrocardiogram

Author

Listed:
  • Jongshill Lee
  • Youngjoon Chee
  • Inyoung Kim

Abstract

We propose a new method for personal identification using the derived vectorcardiogram (dVCG), which is derived from the limb leads electrocardiogram (ECG). The dVCG was calculated from the standard limb leads ECG using the precalculated inverse transform matrix. Twenty-one features were extracted from the dVCG, and some or all of these 21 features were used in support vector machine (SVM) learning and in tests. The classification accuracy was 99.53%, which is similar to the previous dVCG analysis using the standard 12-lead ECG. Our experimental results show that it is possible to identify a person by features extracted from a dVCG derived from limb leads only. Hence, only three electrodes have to be attached to the person to be identified, which can reduce the effort required to connect electrodes and calculate the dVCG.

Suggested Citation

  • Jongshill Lee & Youngjoon Chee & Inyoung Kim, 2012. "Personal Identification Based on Vectorcardiogram Derived from Limb Leads Electrocardiogram," Journal of Applied Mathematics, Hindawi, vol. 2012, pages 1-12, February.
    • Handle: RePEc:hin:jnljam:904905
    DOI: 10.1155/2012/904905
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/JAM/2012/904905.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/JAM/2012/904905.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2012/904905?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnljam:904905. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.