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Arrhythmia disease classification using a higher-order neural unit

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F15%3A00233063" target="_blank" >RIV/68407700:21220/15:00233063 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/FGCT.2015.7300253" target="_blank" >http://dx.doi.org/10.1109/FGCT.2015.7300253</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/FGCT.2015.7300253" target="_blank" >10.1109/FGCT.2015.7300253</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Arrhythmia disease classification using a higher-order neural unit

  • Original language description

    This paper presents a quadratic neural unit with error backpropagation learning algorithm to classify electrocardiogram arrhythmia disease. The electrocardiogram arrhythmia classification scheme consists of data acquisition, feature extraction, feature reduction, and a quadratic neural unit classifier to discriminate three different types of arrhythmia. A total of 44 records were obtained from MIT-BIH arrhythmia database to test the efficiency of arrhythmia disease classification method, the obtained results were a specificity of 97.60 % and a sensitivity of 97.05 %. The best accuracy classification rate obtained using the presented approach has been of 98.16 %.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    The Fourth International Conference on Future Generation Communication Technologies (FGCT 2015)

  • ISBN

    978-1-4799-8267-7

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    85-90

  • Publisher name

    IEE

  • Place of publication

    London

  • Event location

    Luton

  • Event date

    Jul 29, 2015

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000378416600019