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Untangling Operator Monitoring Approaches When Designing Intelligent Adaptive Systems for Operational Environments

  • Ming Hou
  • Cali M. Fidopiastis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8534)

Abstract

An Intelligent Adaptive System (IAS) is a synergy between an intelligent interface and adaptive automation technologies capable of context sensitive interaction with operators. A well-designed IAS should enable flexible task allocation between the operator and the machine. Research suggests that the integration of real-time operator state assessment (e.g., performance, psychophysiology) can create a true ‘human-in-the-loop’ system, thereby minimizing deleterious performance effects such as overlooking automation failures and slowly reorienting to tasks. However, these research approaches apply a variety of methodologies to determine sensors, metrics, and overall system design when applied to real world tasks. This paper seeks to untangle these issues such that a more comprehensive framework for systematically evaluating the utility of cognitive state detection methods is attainable.

Keywords

Intelligent tutoring systems adaptive automation augmented cognition psychophysiological measures cognitive state 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ming Hou
    • 1
  • Cali M. Fidopiastis
    • 2
  1. 1.Defence Research & Development Canada-TorontoTorontoCanada
  2. 2.University of Alabama at BirminghamBirminghamUSA

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