Developing and Validating Practical Eye Metrics for the Sense-Assess-Augment Framework

Abstract

The present chapter examines eye measurements that could potentially inform the machine side of the human-machine system about the level of mental workload experienced by the human operator, boosting the machines ability to aid the human adaptively. To realize this potential, the present work describes algorithms that were developed to detect eye blinks and saccades during real-time mission performance.

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Document Details

Document Type
Technical Report
Publication Date
Sep 29, 2015
Accession Number
AD1015588

Entities

People

  • Christina Gruenwald
  • Matthew Middendorf
  • Michael Vidulich
  • Scott Galster

Organizations

  • 711th Human Performance Wing
  • Oak Ridge Institute for Science and Education

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Acquisition
  • Air Force
  • Air Force Research Laboratories
  • Artificial Intelligence
  • Cartesian Coordinates
  • Cognitive Workload
  • Electroencephalography
  • Feature Extraction
  • Frequency
  • Health Services
  • Human-Machine Systems
  • Machine Learning
  • Military Research
  • Neurology
  • Psychology
  • Signal Processing

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.