• DocumentCode
    174384
  • Title

    Workload prediction and estimation of human mental resources in Helicopter Emergency Medical Service missions

  • Author

    Maiwald, Felix ; Schulte, Axel

  • Author_Institution
    Inst. of Flight Syst., Univ. der Bundeswehr Munchen (UBM), Neubiberg, Germany
  • fYear
    2014
  • fDate
    5-8 Oct. 2014
  • Firstpage
    3900
  • Lastpage
    3905
  • Abstract
    Helicopter Emergency Medical Service (HEMS) missions are associated with high workload for the cockpit crew. Cognitive assistant systems investigated today to counteract high workload issues are proven beneficial in principle, but may also induce additional load for the pilot, especially if the system intervenes when the human operator has little or no free cognitive resources to adopt the offered support. The basis for counteracting such automation induced issues is the automatic, reliable, task-related assessment of the current workload of the human operator. In this article we present a concept and prototype implementation to estimate the usage of mental resources of the human pilot and his current workload level in HEMS missions. Furthermore we describe first evaluation experiments conducted in our research helicopter mission simulator.
  • Keywords
    cognitive systems; digital simulation; emergency services; helicopters; human computer interaction; human factors; medical computing; HEMS missions; cockpit crew; cognitive assistant systems; helicopter emergency medical service missions; helicopter mission simulator; human mental resource estimation; human operator; human pilot; task-related workload assessment; workload prediction; Automation; Brain modeling; Estimation; Helicopters; Resource management; Vectors; Visualization; helicopter emergency medical service; human-machine-interaction; multiple resource model; workload prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
  • Conference_Location
    San Diego, CA
  • Type

    conf

  • DOI
    10.1109/SMC.2014.6974540
  • Filename
    6974540