Algorithms for Extracting Mental Activity Phases from Heart Beat Rate Streams

  • Alina Dubatovka
  • Elena Mikhailova
  • Mikhail Zotov
  • Boris Novikov
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 615)

Abstract

The paper presents algorithms for automatic detection of non-stationary periods of cardiac rhythm during professional activity. While working and subsequent rest operator passes through the phases of mobilization, stabilization, work, recovery and the rest. The amplitude and frequency of non-stationary periods of cardiac rhythm indicates the human resistance to stressful conditions. We introduce and analyze a number of algorithms for non-stationary phase extraction: the different approaches to phase preliminary detection, thresholds extraction and final phases extraction are studied experimentally. These algorithms are based on local extremum computation and analysis of linear regression coefficient histograms. The algorithms do not need any labeled datasets for training and could be applied to any person individually. The suggested algorithms were experimentally compared and evaluated by human experts.

Keywords

Pattern recognition Signal processing Mental activity phases Data stream Linear regression Phase extraction 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Alina Dubatovka
    • 1
  • Elena Mikhailova
    • 1
  • Mikhail Zotov
    • 1
  • Boris Novikov
    • 1
  1. 1.Saint Petersburg State UniversitySt. PetersburgRussia

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