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Arrhythmias Classification Using Singular Value Decomposition and Support Vector Machine

  • Tomáš Peterek
  • Lukáš Zaorálek
  • Pavel Dohnálek
  • Petr Gajdoš
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 298)

Abstract

The main aim of this work is to recognize arrhythmias in ECG records. Many algorithms for this task have been proposed in the past, but in our solution we try to reduce redundancy of information in the signals by Singular Value Decomposition. The reduced dataset is classified by Support Vector Machine. Our approach gives very satisfactory results which can be used in medical practice. This expert system should offer automated recognition between physiological beat and one of the three basic pathological beats: Premature ventricular contractions, Right bundle branch block and Left bundle branch block.

Keywords

SVD SVM Arrhythmias PVC LDA 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Tomáš Peterek
    • 1
  • Lukáš Zaorálek
    • 1
    • 2
  • Pavel Dohnálek
    • 1
    • 2
  • Petr Gajdoš
    • 1
    • 2
  1. 1.IT4innovationsVSB - Technical Univesity of OstravaOstravaCzech republic
  2. 2.Department of Computer ScienceFEECS, VSB - Technical Univesity of OstravaOstravaCzech republic

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