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The Measure of Human Vital Signals Complexity by Matrix Analysis

  • Liepa BikulčienėEmail author
  • Eurelija Venskaitytė
  • Liudas Gargasas
  • Vidmantas Jurkonis
Conference paper

Abstract

The subject of investigation is extraction of information from vital signals (ECG, accelerometer, SpO2) and using it in diagnostics and assessment of status of human physiological state and complexity. The aim of this study is presentation of data recording system and the analytical methods designed for analysis of complexity and dynamic interrelations between different signal parameters. The results show that expressing of cardiac signals with Hankel and coherence matrices could be useful for diagnostic purposes.

Keywords

Hankel Matrice Mealy Automaton Moore Automaton False Positive Alarm Real Time Data Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This study was supported by Agency for International Science and Technology Development Programs in Lithuania, project ITEA2 08018 GUARANTEE.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Liepa Bikulčienė
    • 1
    • 2
    Email author
  • Eurelija Venskaitytė
    • 2
    • 3
  • Liudas Gargasas
    • 2
  • Vidmantas Jurkonis
    • 2
  1. 1.Faculty of Fundamental Sciences, Department of Applied MathematicsKaunas University of TechnologyKaunasLithuania
  2. 2.Laboratory for Automation of Cardiovascular Investigations, Institute of CardiologyLithuanian University of Health SciencesKaunasLithuania
  3. 3.Laboratory of KinesiologyLithuanian Academy of Physical EducationKaunasLithuania

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