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New Diagnostic Tool for Patients Suffering from Noncommunicable Diseases (NCDs)

  • Wojciech Oleksy
  • Zbigniew Budzianowski
  • Ewaryst Tkacz
  • Małgorzata Garbacik
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 721)

Abstract

Electrocardiography, technique, which is an essential tool in the diagnosis of heart disease, as well as other organs, is used by doctors for over 100 years. It is used to measure electrical activity of the heart as a function of time and present it in digital or analogue form. Whilst the standard 12 lead ECG is the basic clinical method of heart diagnosis it has its drawbacks. Measuring all 12 leads is often difficult and impractical, most of all it restricts patient movement. In 1988, Gordon Dower developed a system of quasi-orthogonal lead called EASI, which uses only 5 electrodes in order to register standard 12 lead ECG signals. The main goal of this work is to present a new tool using machine learning algorithms which transforms electrocardiographic signals (ECG) performed by EASI into a standard 12-channel ECG, which therefore could be an ideal tool for diagnose of NCDs.

Keywords

EASI ECG Regression Machine learning 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Wojciech Oleksy
    • 1
  • Zbigniew Budzianowski
    • 1
  • Ewaryst Tkacz
    • 1
  • Małgorzata Garbacik
    • 1
  1. 1.Department of Biosensors and Processing of Biomedical Signals, Faculty of Biomedical EngineeringSilesian University of TechnologyGliwicePoland

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