Adaptive Aiding Implemented by Psychophysiologically Determined Operator Functional State

Abstract

Psychophysiological monitoring of operator state has been developed over the past decades as measures of mental workload, fatigue, and inattention. This paper provides examples of the application of these measures to classify operator functional state (OFS) and further to implement adaptive aiding. Examples using several levels of mental workload are presented to show that combinatorial classifiers can utilize the information from several psychophysiological measures to provide highly accurate correct classification of OFS. An example of adaptive aiding, using on-line assessment of OFS, demonstrated that highly accurate classification could be achieved and that using this information to control adaptive aiding enhanced performance of a complex task. A model of how psychophysiological and performance data could be used to provide continuous OFS monitoring and adaptive aiding is presented. (16 refs.)

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2003
Accession Number
ADA422255

Entities

People

  • Glenn F. Wilson

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Air Traffic
  • Air Traffic Controllers
  • Automation
  • Classification
  • Closed Loop Systems
  • Cognitive Workload
  • Control Systems
  • Human Factors Engineering
  • Machine Learning
  • Neural Networks
  • Psychology
  • Resource Management
  • Signal Processing
  • Task Performance And Analysis
  • Test Methods
  • Workload

Fields of Study

  • Psychology

Readers

  • Neural Network Machine Learning.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.