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Analysis of Keystroke Dynamics for Fatigue Recognition

  • Mindaugas Ulinskas
  • Marcin Woźniak
  • Robertas DamaševičiusEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10408)

Abstract

The paper analyses the problem of fatigue recognition using keystroke dynamics data. Keystroke dynamics provides the time data of key typing events (press-press, press-release, release-press and release-release time). We propose using statistical features and k-Nearest Neighbour (KNN) classifier to discriminate between different consecutive key typing sessions. The presented approach allows to recognize the state of increased fatigue with an accuracy of 91% (using key release-release data).

Keywords

Keystroke dynamics Typing behaviour Fatigue recognition 

Notes

Acknowledgements

The authors also would like to acknowledge the contribution of the COST Action IC1303– Architectures, Algorithms and Platforms for Enhanced Living Environments (AAPELE).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Mindaugas Ulinskas
    • 1
  • Marcin Woźniak
    • 2
  • Robertas Damaševičius
    • 1
    Email author
  1. 1.Department of Software EngineeringKaunas University of TechnologyKaunasLithuania
  2. 2.Institute of Mathematics, Faculty of Applied MathematicsSilesian University of TechnologyGliwicePoland

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