Alertness assessment using data fusion and discrimination ability of LVQ-networks

  • Authors:
  • Udo Trutschel;David Sommer;Acacia Aguirre;Todd Dawson;Bill Sirois

  • Affiliations:
  • Circadian Technologies, Inc., Stoneham, MA;University of Applied Sciences Schmalkalden, Schmalkalden, Germany;Circadian Technologies, Inc., Stoneham, MA;Circadian Technologies, Inc., Stoneham, MA;Circadian Technologies, Inc., Stoneham, MA

  • Venue:
  • KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
  • Year:
  • 2006

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Abstract

To track the alertness changes of 14 subjects during a night driving simulation study traditional alertness measures such Visual Analog Sleepiness Scale, Alpha Attenuation Test (AAT), and number of Microsleep events per driving session were used. The aim of the paper is to assess these traditional alertness measures regarding their mutual correlations, revise one of them (AAT) and introduce new more general methods to capture changes in human alertness without too many constraints attached. The applied methods are utilizing data fusion methods and data discrimination capabilities via Learning Vector Quantification networks. The advantage of using more general data analysis methods which allows one to assess the validity of proposed alertness measures and opens possibilities to get a more comprehensive knowledge of obtained results.